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R. Binnekamp
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1
Improvement in rail asset safety, comfortability and serviceability is gaining importance. This requires effective service life management by incorporating multi-stakeholder desires in the early design stage. Typical stakeholders are asset owners, train users and maintenance service providers. To allow for this change, the traditional single-sided engineering mechanics track design approach requires a shift towards an integrative design approach that best fits for common purpose while assuring continuous rail asset performance. Within the current paper, a multi-objective simulation-based optimization methodology that combines finite element modeling with preference function modeling is proposed to integrate multi-stakeholder preferences into the service life design. The applicability of the methodology is demonstrated in a design case for level crossings. It is shown that integrating specific stakeholders’ preferences will substantially influence the optimal track design configuration, allowing the level crossing design to be managed focusing on best fit for common purpose rather than on mechanical behavior only.
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Improvement in rail asset safety, comfortability and serviceability is gaining importance. This requires effective service life management by incorporating multi-stakeholder desires in the early design stage. Typical stakeholders are asset owners, train users and maintenance service providers. To allow for this change, the traditional single-sided engineering mechanics track design approach requires a shift towards an integrative design approach that best fits for common purpose while assuring continuous rail asset performance. Within the current paper, a multi-objective simulation-based optimization methodology that combines finite element modeling with preference function modeling is proposed to integrate multi-stakeholder preferences into the service life design. The applicability of the methodology is demonstrated in a design case for level crossings. It is shown that integrating specific stakeholders’ preferences will substantially influence the optimal track design configuration, allowing the level crossing design to be managed focusing on best fit for common purpose rather than on mechanical behavior only.
Conference paper
(2023)
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H.J. van Heukelum, A.C. Steenbrink, O. Colomes, R. Binnekamp, A.R.M. Wolfert
Floating wind farms are a promising solution for offshore wind energy production in deep waters. However, the design optimisation process of these farms is difficult due to their complex and multidisciplinary nature. Furthermore, current optimisation methods: 1) ignore and/or provide no insight into the dynamic interplay between the preference-dominated management domain and the object-performance-dominated engineering domain; 2) are limited to evaluating potentially sub-optimal design alternatives; 3) contain fundamental aggregation modelling errors; 4) do not return a single optimal design point. This paper presents an optimisation framework that overcomes these shortcomings and enables truly integrative multi-objective design optimisation. It includes a surrogate model that interacts with the wind turbine simulation tool OpenFAST to enable preliminary design of the structure’s mooring system. Applied to a demonstration project and validated against real projects in a maritime contractor environment, the workflow shows improvements in tender performance and added value over single-sided cost optimisations.
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Floating wind farms are a promising solution for offshore wind energy production in deep waters. However, the design optimisation process of these farms is difficult due to their complex and multidisciplinary nature. Furthermore, current optimisation methods: 1) ignore and/or provide no insight into the dynamic interplay between the preference-dominated management domain and the object-performance-dominated engineering domain; 2) are limited to evaluating potentially sub-optimal design alternatives; 3) contain fundamental aggregation modelling errors; 4) do not return a single optimal design point. This paper presents an optimisation framework that overcomes these shortcomings and enables truly integrative multi-objective design optimisation. It includes a surrogate model that interacts with the wind turbine simulation tool OpenFAST to enable preliminary design of the structure’s mooring system. Applied to a demonstration project and validated against real projects in a maritime contractor environment, the workflow shows improvements in tender performance and added value over single-sided cost optimisations.
Socio-technical systems integration and design
A multi-objective optimisation method based on integrative preference maximisation
Current systems design optimisation methodologies are one-sided, as these ignore the socio-technical integration between stakeholder preferences (‘what a human wants’) and the capability of technical assets (‘what a system can deliver’). Moreover, classical multi-objective optimisation methods contain fundamental mathematical flaws. Also, the often-used classical Pareto front does not provide a single best-fit design configuration, but rather a set of design alternatives. This leaves designers without a unique solution to their problems. Finally, current multi-objective optimisation processes are not well aligned with design practices, because they do not sufficiently involve decision makers and do not translate their interests into a single common preference domain to find an overall group optimum. This paper introduces a new Open Design Systems (Odesys) methodology and a new Integrative Maximisation of Aggregated Preferences (IMAP) method, implemented in the Preferendus tool. Its added value and use are exemplified in two infrastructure design applications, which show how to achieve the pure best-fit for common-purpose design results.
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Current systems design optimisation methodologies are one-sided, as these ignore the socio-technical integration between stakeholder preferences (‘what a human wants’) and the capability of technical assets (‘what a system can deliver’). Moreover, classical multi-objective optimisation methods contain fundamental mathematical flaws. Also, the often-used classical Pareto front does not provide a single best-fit design configuration, but rather a set of design alternatives. This leaves designers without a unique solution to their problems. Finally, current multi-objective optimisation processes are not well aligned with design practices, because they do not sufficiently involve decision makers and do not translate their interests into a single common preference domain to find an overall group optimum. This paper introduces a new Open Design Systems (Odesys) methodology and a new Integrative Maximisation of Aggregated Preferences (IMAP) method, implemented in the Preferendus tool. Its added value and use are exemplified in two infrastructure design applications, which show how to achieve the pure best-fit for common-purpose design results.
Best Fit for Common Purpose
A Multi-Stakeholder Design Optimization Methodology for Construction Management
Within traditional design processes, decisions are often made based on individualistic values and late-stage assessments conducted on a predefined set of design alternatives potentially leading to suboptimal design decisions and conflicts. The issues are further amplified by the growing complexity of construction project management where an increasing number of stakeholders are involved. To address those issues, a shift is needed towards a collaborative early stage optimization-based design process. The current optimization-based design approaches are not appropriately integrating stakeholders and their preferences in the optimization process and thereby not reflecting the real-life design and construction process. In this study, we present a pioneering multi-stakeholder design methodology combining preference function modeling theory and a priori optimization enabling stakeholders to find the group-optimal design fairly representing their preferences. The application of the developed methodology is demonstrated on a real-life multi-storey building design case. The study provides a novel approach for managing design and construction projects for academic and industry stakeholders. It also sets the foundation for the further development of stakeholder-oriented optimization-based design.
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Within traditional design processes, decisions are often made based on individualistic values and late-stage assessments conducted on a predefined set of design alternatives potentially leading to suboptimal design decisions and conflicts. The issues are further amplified by the growing complexity of construction project management where an increasing number of stakeholders are involved. To address those issues, a shift is needed towards a collaborative early stage optimization-based design process. The current optimization-based design approaches are not appropriately integrating stakeholders and their preferences in the optimization process and thereby not reflecting the real-life design and construction process. In this study, we present a pioneering multi-stakeholder design methodology combining preference function modeling theory and a priori optimization enabling stakeholders to find the group-optimal design fairly representing their preferences. The application of the developed methodology is demonstrated on a real-life multi-storey building design case. The study provides a novel approach for managing design and construction projects for academic and industry stakeholders. It also sets the foundation for the further development of stakeholder-oriented optimization-based design.
Construction project management requires dynamic mitigation control to ensure a project's timely completion. Current mitigation approaches are usually performed by an iterative Monte Carlo (MC) analysis which does not reflect (1) the project manager's goal-oriented behavior, (2) contractual project completion performance schemes, and (3) stochastic dependence between construction activities. Therefore, the development statement within this paper is to design a method and implementation tool that properly dissolves all of the aforementioned shortcomings ensuring the project's completion date by finding the most effective and efficient mitigation strategy. For this purpose, the Mitigation Controller (MitC) has been developed using an integrative approach of nonlinear stochastic optimization techniques and probabilistic Monte Carlo analysis. MitC's applicability is demonstrated using a recent Dutch large infrastructure construction project showing its added value for dynamic control on-the-run. It is shown that the MitC is a state-of-the-art decision support tool that a-priori automates and optimizes the search for the best set of mitigation strategies on-the-run rather than a-posteriori evaluating the potentially sub-optimal and over-designed mitigation strategies (as commonly done with modern software such as Primavera P6).
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Construction project management requires dynamic mitigation control to ensure a project's timely completion. Current mitigation approaches are usually performed by an iterative Monte Carlo (MC) analysis which does not reflect (1) the project manager's goal-oriented behavior, (2) contractual project completion performance schemes, and (3) stochastic dependence between construction activities. Therefore, the development statement within this paper is to design a method and implementation tool that properly dissolves all of the aforementioned shortcomings ensuring the project's completion date by finding the most effective and efficient mitigation strategy. For this purpose, the Mitigation Controller (MitC) has been developed using an integrative approach of nonlinear stochastic optimization techniques and probabilistic Monte Carlo analysis. MitC's applicability is demonstrated using a recent Dutch large infrastructure construction project showing its added value for dynamic control on-the-run. It is shown that the MitC is a state-of-the-art decision support tool that a-priori automates and optimizes the search for the best set of mitigation strategies on-the-run rather than a-posteriori evaluating the potentially sub-optimal and over-designed mitigation strategies (as commonly done with modern software such as Primavera P6).
Building Information Models (BIM) should reflect all aspects and phases of the construction projects life cycle. However, in current contractor practices, a proliferation of different information systems has arisen, each of which in turn illuminates a different information model dimension (nD) for usually only one construction project management purpose. To solve this problem it seems obvious to build a unique overarching system based on a single prescribed data modelling structure. We argue that this attempt is unrealistic, will not serve industrial practitioners and has failed already several times. We propose to link BIM to the concept of Systems Integration (SI), to develop tailormade and integrative information systems for its intended multidimensional (nD) modelling and construction projects management purpose: i.e. a targeted BIMSI fit for nD purpose enhancing better construction projects management. In this paper this nD BIMSI concept is introduced and demonstrated by a number of grassroot projects, which have been developed and validated in close cooperation with the AEC industrial practice and construction management and (civil) engineering master student projects at TU Delft. An overview of these grass root development projects is provided. These projects show how the BIMSI concept improves construction project management in areas such as generative design, safety during construction, and AI applications for effective budgeting. The focus of these projects is not on extending or evaluating BIM knowledge and theory, but rather on transforming BIM concepts into integrative information systems to solve real life problems. Finally, a state of the art education concept developed at the TU Delft is presented to demonstrate its unique position in master education on information systems for the construction industry. This so-called Open Design Learning (ODL) education integrates the nD BIMSI concept to better prepare students for both industrial and R&D construction project management practices.
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Building Information Models (BIM) should reflect all aspects and phases of the construction projects life cycle. However, in current contractor practices, a proliferation of different information systems has arisen, each of which in turn illuminates a different information model dimension (nD) for usually only one construction project management purpose. To solve this problem it seems obvious to build a unique overarching system based on a single prescribed data modelling structure. We argue that this attempt is unrealistic, will not serve industrial practitioners and has failed already several times. We propose to link BIM to the concept of Systems Integration (SI), to develop tailormade and integrative information systems for its intended multidimensional (nD) modelling and construction projects management purpose: i.e. a targeted BIMSI fit for nD purpose enhancing better construction projects management. In this paper this nD BIMSI concept is introduced and demonstrated by a number of grassroot projects, which have been developed and validated in close cooperation with the AEC industrial practice and construction management and (civil) engineering master student projects at TU Delft. An overview of these grass root development projects is provided. These projects show how the BIMSI concept improves construction project management in areas such as generative design, safety during construction, and AI applications for effective budgeting. The focus of these projects is not on extending or evaluating BIM knowledge and theory, but rather on transforming BIM concepts into integrative information systems to solve real life problems. Finally, a state of the art education concept developed at the TU Delft is presented to demonstrate its unique position in master education on information systems for the construction industry. This so-called Open Design Learning (ODL) education integrates the nD BIMSI concept to better prepare students for both industrial and R&D construction project management practices.
MitC
Open-source software for construction project control and delay mitigation
Journal article
(2022)
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Omar Kammouh, M. W.A.(Maurits) Kok, Maria Nogal, Ruud Binnekamp, A. R.M.(Rogier) Wolfert
Changes in a construction project schedule can impact the project's planned duration, resulting in penalties. A manual trial-and-error probabilistic approach is usually conducted to find an appropriate set of corrective measures to mitigate delays of the overall project. However, this approach does not capture the actual goal-oriented behavior of project managers who react to the actual scenarios causing delays, leading to a fundamental modeling error. Moreover, it does not employ control and automation concepts when finding the optimal mitigation strategy. To remove this modeling error and to automate the mitigation process, the Mitigation Controller (MitC) software is developed. The MitC searches for the most cost-effective set of mitigation measures considering risk events and durations uncertainties of activities. Moreover, the MitC captures activity correlations and enables contractual penalty/reward schemes in the simulation. As a result, it returns the most effective mitigation strategy that minimizes the mitigation cost and penalty and maximizes the reward potential. The Mitigation Controller introduced here constitutes an open-source code written in Matlab
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Changes in a construction project schedule can impact the project's planned duration, resulting in penalties. A manual trial-and-error probabilistic approach is usually conducted to find an appropriate set of corrective measures to mitigate delays of the overall project. However, this approach does not capture the actual goal-oriented behavior of project managers who react to the actual scenarios causing delays, leading to a fundamental modeling error. Moreover, it does not employ control and automation concepts when finding the optimal mitigation strategy. To remove this modeling error and to automate the mitigation process, the Mitigation Controller (MitC) software is developed. The MitC searches for the most cost-effective set of mitigation measures considering risk events and durations uncertainties of activities. Moreover, the MitC captures activity correlations and enables contractual penalty/reward schemes in the simulation. As a result, it returns the most effective mitigation strategy that minimizes the mitigation cost and penalty and maximizes the reward potential. The Mitigation Controller introduced here constitutes an open-source code written in Matlab
Mitigation Controller
Adaptive Simulation Approach for Planning Control Measures in Large Construction Projects
Probabilistic Monte Carlo simulations are often used to determine a project's completion time given a required probability level. During project execution, schedule changes negatively affect the probability of meeting the project's completion time. A manual trial and error approach is then conducted to find a set of mitigation measures to again arrive at the required probability level. These are then implemented as scheduled activities. The mitigation controller (MitC) proposed in this paper automates the search for finding the most cost-effective set of mitigation measures using multiobjective linear optimization so that the probability of timely completion remains at the required level. It considers different types of uncertainties and risk events in the probabilistic simulation. Moreover, it removes the fundamental modeling error that exists in the traditional probabilistic approach by incorporating human control and adaptive behavior in the simulation. Its usefulness is demonstrated using an illustrative example derived from a recent Dutch construction project in which delay is not permitted. It is shown that the MitC is capable of identifying the most effective mitigation strategies allowing for substantial cost savings.
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Probabilistic Monte Carlo simulations are often used to determine a project's completion time given a required probability level. During project execution, schedule changes negatively affect the probability of meeting the project's completion time. A manual trial and error approach is then conducted to find a set of mitigation measures to again arrive at the required probability level. These are then implemented as scheduled activities. The mitigation controller (MitC) proposed in this paper automates the search for finding the most cost-effective set of mitigation measures using multiobjective linear optimization so that the probability of timely completion remains at the required level. It considers different types of uncertainties and risk events in the probabilistic simulation. Moreover, it removes the fundamental modeling error that exists in the traditional probabilistic approach by incorporating human control and adaptive behavior in the simulation. Its usefulness is demonstrated using an illustrative example derived from a recent Dutch construction project in which delay is not permitted. It is shown that the MitC is capable of identifying the most effective mitigation strategies allowing for substantial cost savings.
The wellbeing of modern societies is dependent upon the functioning of their infrastructure networks. This paper introduces the 3C concept, an integrative multi-system and multi-stakeholder optimization approach for managing infrastructure interventions (e.g., maintenance, renovation, etc.). The proposed approach takes advantage of the benefits achieved by grouping (i.e., optimizing) intervention activities. Intervention optimization leads to substantial savings on both direct intervention costs (operator) and indirect unavailability costs (society) by reducing the number of system interruptions. The proposed optimization approach is formalized into a structured mathematical model that can account for the interactions between multiple infrastructure networks and the impact on multiple stakeholders (e.g., society and infrastructure operators), and it can accommodate different types of intervention, such as maintenance, removal, and upgrading. The different types of interdependencies, within and across infrastructures, are modeled using a proposed interaction matrix (IM). The IM allows integrating the interventions of different infrastructure networks whose interventions are normally planned independently. Moreover, the introduced 3C concept accounts for central interventions, which are those that must occur at a pre-established time moment, where neither delay nor advance is permitted. To demonstrate the applicability of the proposed approach, an illustrative example of a multi-system and multi-actor intervention planning is introduced. Results show a substantial reduction in the operator and societal costs. In addition, the optimal intervention program obtained in the analysis shows no predictable patterns, which indicates it is a useful managerial decision support tool.
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The wellbeing of modern societies is dependent upon the functioning of their infrastructure networks. This paper introduces the 3C concept, an integrative multi-system and multi-stakeholder optimization approach for managing infrastructure interventions (e.g., maintenance, renovation, etc.). The proposed approach takes advantage of the benefits achieved by grouping (i.e., optimizing) intervention activities. Intervention optimization leads to substantial savings on both direct intervention costs (operator) and indirect unavailability costs (society) by reducing the number of system interruptions. The proposed optimization approach is formalized into a structured mathematical model that can account for the interactions between multiple infrastructure networks and the impact on multiple stakeholders (e.g., society and infrastructure operators), and it can accommodate different types of intervention, such as maintenance, removal, and upgrading. The different types of interdependencies, within and across infrastructures, are modeled using a proposed interaction matrix (IM). The IM allows integrating the interventions of different infrastructure networks whose interventions are normally planned independently. Moreover, the introduced 3C concept accounts for central interventions, which are those that must occur at a pre-established time moment, where neither delay nor advance is permitted. To demonstrate the applicability of the proposed approach, an illustrative example of a multi-system and multi-actor intervention planning is introduced. Results show a substantial reduction in the operator and societal costs. In addition, the optimal intervention program obtained in the analysis shows no predictable patterns, which indicates it is a useful managerial decision support tool.
Conference paper
(2020)
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O. Kammouh, M. Nogal Macho, M.L.C. de Bruijne, R. Binnekamp, A.R.M. Wolfert
Despite widespread attention for the governance of infrastructures and improvements of the way infrastructure assets are maintained, the interdependency of infrastructures is not often considered from a systemic maintenance and renovation perspective. In this context, the issue of unforeseen intervention delays is of particular relevance because its impact on cost and hindrance might be too costly for infrastructure operators. Building upon the 3C concept (Centralize, Cluster, and Calculate) for intervention scheduling and optimization, this paper investigates the effect of unforeseen intervention delays on the intervention costs and the corresponding closure cost of the affected interdependent systems. A stochastic approach has been proposed to deal with the uncertainty of such delays. Uncertain intervention times are combined by Monte Carlo simulations to obtain the probabilistic distribution of the total cost at the end of the timeline of an intervention program affecting multiple interdependent infrastructures. Also, the change in the statistical deviation over time of the total cost with respect to the planned (optimal) cost during the entire program is obtained. This analysis yields interesting conclusions, such as the need for specific mitigation plans conducted during the course of the program to reduce the cost generated by the cumulative delays, and the need for enhanced communication between infrastructure managers, which could bring significant (economic) benefits to all stakeholders by jointly planning their intervention activities.
...
Despite widespread attention for the governance of infrastructures and improvements of the way infrastructure assets are maintained, the interdependency of infrastructures is not often considered from a systemic maintenance and renovation perspective. In this context, the issue of unforeseen intervention delays is of particular relevance because its impact on cost and hindrance might be too costly for infrastructure operators. Building upon the 3C concept (Centralize, Cluster, and Calculate) for intervention scheduling and optimization, this paper investigates the effect of unforeseen intervention delays on the intervention costs and the corresponding closure cost of the affected interdependent systems. A stochastic approach has been proposed to deal with the uncertainty of such delays. Uncertain intervention times are combined by Monte Carlo simulations to obtain the probabilistic distribution of the total cost at the end of the timeline of an intervention program affecting multiple interdependent infrastructures. Also, the change in the statistical deviation over time of the total cost with respect to the planned (optimal) cost during the entire program is obtained. This analysis yields interesting conclusions, such as the need for specific mitigation plans conducted during the course of the program to reduce the cost generated by the cumulative delays, and the need for enhanced communication between infrastructure managers, which could bring significant (economic) benefits to all stakeholders by jointly planning their intervention activities.
The open design education approach
An integrative teaching and learning concept for management and engineering
Construction Management and Engineering students need to acquire managing skills for solving real-world problems that are complex, rarely straightforward and lack 'one right answer'. For this, they need to become 'open designers', capable to be reflective, integrative and creative in- and on action with dynamic and new situations. In this paper, the so-called Open Design Learning Circle (ODLC) will be proposed as an innovative educational concept in which engineering-, management- and pedagogic sciences are integrated. Within this concept the students 'dialogue' with: 1) an objective open glass box model covering engineering products and management processes (outer) and, 2) their subjective open human threefold, reflecting their personal learning (inner). The integration of both human and model dialogues is essential for the emergence of new knowledge and creative insights for open designs, which is essentially distinct from more traditional learning concepts. To enable this emergence, a self-chosen system of interest is the 'experiential vehicle' that forms the basis for a self-created textbook and model. Thereby, the ODLC forms the fundamental basis for creating 'open and persistent learners'. In this paper, it also will be shown how the ODLC can be operationalized into a learning cycle and how it has been implemented in an example course on systems engineering management within the MSc Construction Management Engineering curriculum at the TU Delft. Finally, some preliminary student findings and next steps for further research are discussed.
...
Construction Management and Engineering students need to acquire managing skills for solving real-world problems that are complex, rarely straightforward and lack 'one right answer'. For this, they need to become 'open designers', capable to be reflective, integrative and creative in- and on action with dynamic and new situations. In this paper, the so-called Open Design Learning Circle (ODLC) will be proposed as an innovative educational concept in which engineering-, management- and pedagogic sciences are integrated. Within this concept the students 'dialogue' with: 1) an objective open glass box model covering engineering products and management processes (outer) and, 2) their subjective open human threefold, reflecting their personal learning (inner). The integration of both human and model dialogues is essential for the emergence of new knowledge and creative insights for open designs, which is essentially distinct from more traditional learning concepts. To enable this emergence, a self-chosen system of interest is the 'experiential vehicle' that forms the basis for a self-created textbook and model. Thereby, the ODLC forms the fundamental basis for creating 'open and persistent learners'. In this paper, it also will be shown how the ODLC can be operationalized into a learning cycle and how it has been implemented in an example course on systems engineering management within the MSc Construction Management Engineering curriculum at the TU Delft. Finally, some preliminary student findings and next steps for further research are discussed.
With the rapid development of real estate markets under globalization and exponential competitive market conditions, risk evaluation has been one of the most important tasks in the process of real estate investment valuation. This paper describes the relationship between construction permit uncertainties and real estate development projects by using the Decision Tree Analysis (DTA) approach together with Monte Carlo simulations. Expected Value (EV) criterion for an office development project proposed and incorporated into conventional Discounted Cash Flow (DCF) analysis which is determined by stochastic DTA. This will help utility function to come closer to the real world, so that decision making and risk analysis can be done based on the real and possible data providing better conditions for investors. The results are consistent with the results calculated by conventional DCF analysis. However research demonstrates that is of application Monte Carlo Simulation (MCS) and DTA obviate the deficiencies of conventional DCF analysis under construction permit delays and scheduling uncertainties. Results also emphasize the importance of applying EV and DTA for the construction permit delays generate a significant change in NPV and also investment decisions of real estate development projects.
...
With the rapid development of real estate markets under globalization and exponential competitive market conditions, risk evaluation has been one of the most important tasks in the process of real estate investment valuation. This paper describes the relationship between construction permit uncertainties and real estate development projects by using the Decision Tree Analysis (DTA) approach together with Monte Carlo simulations. Expected Value (EV) criterion for an office development project proposed and incorporated into conventional Discounted Cash Flow (DCF) analysis which is determined by stochastic DTA. This will help utility function to come closer to the real world, so that decision making and risk analysis can be done based on the real and possible data providing better conditions for investors. The results are consistent with the results calculated by conventional DCF analysis. However research demonstrates that is of application Monte Carlo Simulation (MCS) and DTA obviate the deficiencies of conventional DCF analysis under construction permit delays and scheduling uncertainties. Results also emphasize the importance of applying EV and DTA for the construction permit delays generate a significant change in NPV and also investment decisions of real estate development projects.
Improving CRE decision making at Oracle
Implementing the PAS procedure with a brute force approach
Purpose –Alignment of corporate real estate to a corporation’s business strategy is a long-standing issue. In the past multiple models have been developed to support this process, but research shows that they fall short on certain parts of the CRE alignment activity, often lack transparency and fail to choose the real estate strategy that delivers most value to the organisation. The Preference-based Accommodation Strategy (PAS) procedure has been proposed as a solution to these issues and first results in two pilots are positive. However, to optimise the results, a brute force approach should be implemented in the procedure. This paper reports on a pilot study wherein this PAS procedure 3.0 was tested and evaluated.
Design/methodology/approach – A literature study is conducted to develop a theoretical basis for the implementation of a brute force approach in the PAS procedure. This procedure is implemented in a pilot study by building a mathematical model. During the pilot the users improved the reflection of their preferences in the model, in an iterative process of manually designing portfolio alternatives. A brute force approach is applied to the final model to yield the optimum portfolio alternative. The implementation of the brute force approach is evaluated and it is determined if the approach yields a higher preference rating than the stakeholders can achieve by manual design.
Findings – The pilot study shows that the brute force approach is able to improve the results over the manual design and yields a 7% increase in the real estate alignment compared to the current portfolio. The evaluation results reveal that the implementation process results in acceptance of- and trust in the model. Moreover, the users are very positive about the PAS and indicate that the model better reflects their preferences than their current process. They even indicate that they want to incorporate the tool in their daily decision-making process.
Research limitations/implications – This pilot study was less complex than previous pilots, therefore the PAS procedure 3.0 should be tested in more complex pilots to discover the boundaries of the brute force approach but to use it where possible. Also a search algorithm should be developed for pilots that are too complex for the brute force approach.
Practical implications – This pilot study has shown that the PAS procedure 3.0 is able to improve the corporate real estate (CRE) decision-making process and hereby improve the corporate real estate (CRE) alignment. This will result in more added value of real estate to the businesses in which the tool is used.
...
Purpose –Alignment of corporate real estate to a corporation’s business strategy is a long-standing issue. In the past multiple models have been developed to support this process, but research shows that they fall short on certain parts of the CRE alignment activity, often lack transparency and fail to choose the real estate strategy that delivers most value to the organisation. The Preference-based Accommodation Strategy (PAS) procedure has been proposed as a solution to these issues and first results in two pilots are positive. However, to optimise the results, a brute force approach should be implemented in the procedure. This paper reports on a pilot study wherein this PAS procedure 3.0 was tested and evaluated.
Design/methodology/approach – A literature study is conducted to develop a theoretical basis for the implementation of a brute force approach in the PAS procedure. This procedure is implemented in a pilot study by building a mathematical model. During the pilot the users improved the reflection of their preferences in the model, in an iterative process of manually designing portfolio alternatives. A brute force approach is applied to the final model to yield the optimum portfolio alternative. The implementation of the brute force approach is evaluated and it is determined if the approach yields a higher preference rating than the stakeholders can achieve by manual design.
Findings – The pilot study shows that the brute force approach is able to improve the results over the manual design and yields a 7% increase in the real estate alignment compared to the current portfolio. The evaluation results reveal that the implementation process results in acceptance of- and trust in the model. Moreover, the users are very positive about the PAS and indicate that the model better reflects their preferences than their current process. They even indicate that they want to incorporate the tool in their daily decision-making process.
Research limitations/implications – This pilot study was less complex than previous pilots, therefore the PAS procedure 3.0 should be tested in more complex pilots to discover the boundaries of the brute force approach but to use it where possible. Also a search algorithm should be developed for pilots that are too complex for the brute force approach.
Practical implications – This pilot study has shown that the PAS procedure 3.0 is able to improve the corporate real estate (CRE) decision-making process and hereby improve the corporate real estate (CRE) alignment. This will result in more added value of real estate to the businesses in which the tool is used.
Purpose: One of the long-standing issues in the field of corporate real estate management is the alignment of an organisation’s real estate to its corporate strategy. To date, 14 models for corporate real estate (CRE) alignment have been made, as well as four comparative studies about CRE alignment. Some of the CRE alignment models indicate that they strive for maximum or optimum added value. However, because most models take a so-called procedural rationality approach, where the focus is not on the content of the decision but on the way that the decision is made, “how a CRE manager can select an (optimum) alternative” stays a black box. The purpose of this paper is to open the black box and offer a Preference-based Accommodation Strategy (PAS) design procedure that enables CRE managers to design a real estate portfolio, makes use of scales for direct measurement of added value/preference, and allows the aggregation of individual ratings into an overall performance rating. This procedure can be used as add-on to existing alignment models. Design/methodology/approach: The objective of this paper is to test if participants are able to successfully perform the PAS procedure in practice. The PAS procedure is in essence a design methodology that aims to solve strategic portfolio design/decision-making problems. In accordance with problem-solving methodology, mathematical models are made for two pilot studies at the Delft University of Technology. This paper describes a second test of the proposed procedure for designing a real estate strategy. The application of real estate strategy design methods in practice is very context-dependent. Applying the PAS procedure to multiple context-dependent cases yields more valuable results than just applying it to one case. Findings: The PAS design procedure enables CRE managers to select the (optimal) solution and thereby enhances CRE decision-making. The pilot study results reveal that, by completing the steps in the PAS procedure, the participants are able to express their preferences accordingly. They designed an alternative portfolio with substantially more added value, i.e. a higher overall preference score, than their current real estate portfolio. In addition, they evaluated the design method positively. Research limitations/implications: The positive results suggest that designing a strategy by using the PAS design procedure is a suitable approach to alignment. Practical implications: The PAS design procedure enables CRE managers to determine the added value of a real estate strategy and quickly and iteratively design many alternatives. Moreover, the PAS design method is generic, it can be used for a wide range of real estate portfolio types. Originality/value: The PAS procedure is original because it considers CRE alignment as a combined design and decision problem. The use of operational design and problem-solving methodologies along with an iterative procedure, instead of empirical/statistical methods and procedures, is a novel approach to CRE alignment. The PAS procedure is tested in a second pilot study to provide an assessment of the methodology through the study by testing it under different conditions to the first study. The novelty of this pilot is also that it allowed testing the procedure in its purest form, as the problem structure did not require the additional use of linear programming.
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Purpose: One of the long-standing issues in the field of corporate real estate management is the alignment of an organisation’s real estate to its corporate strategy. To date, 14 models for corporate real estate (CRE) alignment have been made, as well as four comparative studies about CRE alignment. Some of the CRE alignment models indicate that they strive for maximum or optimum added value. However, because most models take a so-called procedural rationality approach, where the focus is not on the content of the decision but on the way that the decision is made, “how a CRE manager can select an (optimum) alternative” stays a black box. The purpose of this paper is to open the black box and offer a Preference-based Accommodation Strategy (PAS) design procedure that enables CRE managers to design a real estate portfolio, makes use of scales for direct measurement of added value/preference, and allows the aggregation of individual ratings into an overall performance rating. This procedure can be used as add-on to existing alignment models. Design/methodology/approach: The objective of this paper is to test if participants are able to successfully perform the PAS procedure in practice. The PAS procedure is in essence a design methodology that aims to solve strategic portfolio design/decision-making problems. In accordance with problem-solving methodology, mathematical models are made for two pilot studies at the Delft University of Technology. This paper describes a second test of the proposed procedure for designing a real estate strategy. The application of real estate strategy design methods in practice is very context-dependent. Applying the PAS procedure to multiple context-dependent cases yields more valuable results than just applying it to one case. Findings: The PAS design procedure enables CRE managers to select the (optimal) solution and thereby enhances CRE decision-making. The pilot study results reveal that, by completing the steps in the PAS procedure, the participants are able to express their preferences accordingly. They designed an alternative portfolio with substantially more added value, i.e. a higher overall preference score, than their current real estate portfolio. In addition, they evaluated the design method positively. Research limitations/implications: The positive results suggest that designing a strategy by using the PAS design procedure is a suitable approach to alignment. Practical implications: The PAS design procedure enables CRE managers to determine the added value of a real estate strategy and quickly and iteratively design many alternatives. Moreover, the PAS design method is generic, it can be used for a wide range of real estate portfolio types. Originality/value: The PAS procedure is original because it considers CRE alignment as a combined design and decision problem. The use of operational design and problem-solving methodologies along with an iterative procedure, instead of empirical/statistical methods and procedures, is a novel approach to CRE alignment. The PAS procedure is tested in a second pilot study to provide an assessment of the methodology through the study by testing it under different conditions to the first study. The novelty of this pilot is also that it allowed testing the procedure in its purest form, as the problem structure did not require the additional use of linear programming.
Conference paper
(2017)
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Angela Greco, Thaleia Konstantinou, Roel Schipper, Ruud Binnekamp, Esther Gerritsen, Andy van den Dobbelsteen
In Europe, the DIRECTIVE 2010/31/EU requires increasing the number of nearly zero energy buildings. The existing building stock needs to be included in order to achieve the 2020 EU environmental targets. The main barriers of energy neutral refurbishment of existing non-residential buildings appear to be financial rather than technical, next to a number of other extrinsic factors that do not stimulate such an investment. While a business case for new energy neutral buildings is believed to exist, controversial opinions can be found with respect to refurbishment of existing large buildings. Let properties, in particular, have a harder-to-justify business case because of contractual agreements between landlord and tenant: the former is usually accountable for renovation and the latter for energy bills. The present study aims at providing an overview of the barriers and benefits of energy neutral refurbishment according to relevant stakeholders. Through interviews with real estate investors, energy service companies and tenants, the main interests and risks encountered today to undertake deep energy retrofit as well as technical constraints were investigated. Subsequently, a roundtable discussion was organized with the interviewed real-estate investors. During the roundtable, the investment needed to refurbish an existing office building, meeting the zero energy target was presented and different strategies to improve the financial attractiveness of energy retrofitting were discussed. The study has shown that combining different benefits in the renovation is fundamental to convince investors. When the design provides additional benefits, such as increasing the rent, or allocating an energy budget to the tenant, the refurbishment can become feasible. Ultimately, a screening-checklist is proposed for a qualitative estimation of the potentials offered by a given building for a feasible energy neutral refurbishment.
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In Europe, the DIRECTIVE 2010/31/EU requires increasing the number of nearly zero energy buildings. The existing building stock needs to be included in order to achieve the 2020 EU environmental targets. The main barriers of energy neutral refurbishment of existing non-residential buildings appear to be financial rather than technical, next to a number of other extrinsic factors that do not stimulate such an investment. While a business case for new energy neutral buildings is believed to exist, controversial opinions can be found with respect to refurbishment of existing large buildings. Let properties, in particular, have a harder-to-justify business case because of contractual agreements between landlord and tenant: the former is usually accountable for renovation and the latter for energy bills. The present study aims at providing an overview of the barriers and benefits of energy neutral refurbishment according to relevant stakeholders. Through interviews with real estate investors, energy service companies and tenants, the main interests and risks encountered today to undertake deep energy retrofit as well as technical constraints were investigated. Subsequently, a roundtable discussion was organized with the interviewed real-estate investors. During the roundtable, the investment needed to refurbish an existing office building, meeting the zero energy target was presented and different strategies to improve the financial attractiveness of energy retrofitting were discussed. The study has shown that combining different benefits in the renovation is fundamental to convince investors. When the design provides additional benefits, such as increasing the rent, or allocating an energy budget to the tenant, the refurbishment can become feasible. Ultimately, a screening-checklist is proposed for a qualitative estimation of the potentials offered by a given building for a feasible energy neutral refurbishment.
Purpose–Alignment of corporate real estate to a corporation’s business strategy is a long-standing issue. In the past multiple models have been developed to support this process, but research shows that they fall short on certain parts of the CRE alignment activity, often lack transparency and fail to choose the real estate strategy that delivers most value to the organisation. The Preference-based Accommodation Strategy (PAS) procedure has been proposed as a solution to these issues and results in two pilots are positive. However, to optimise the results, a brute force approach should be implemented in the procedure. This paper reports on a pilot study wherein this PAS procedure 3.0 was tested and evaluated.
Approach–A literature study is conducted to develop a theoretical basis for the implementation of a brute force approach in the PAS procedure. This procedure is implemented in a pilot study by building a mathematical model. During the pilot the users improved the reflection of their preferences in the model, in an iterative process of manually designing portfolio alternatives. A brute force approach is applied to the final model to yield the optimum portfolio alternative. The implementation of the brute force approach is evaluated and it is determined if the approach yields a higher preference rating than the stakeholders can achieve by manual design.
Findings–The pilot study shows that the brute force approach is able to improve the results over the manual design and yields a 7% increase in the real estate alignment compared to the current portfolio. The evaluation results reveal that the implementation process results in acceptance of- and trust in the model. Moreover, the users are very positive about the PAS and indicate that the model better reflects their preferences than their current process. They even indicate that they want to incorporate the tool in their daily decision-making process.
Implications–This pilot study was less complex than previous pilots, therefore the PAS procedure 3.0 should be tested in more complex pilots to discover the boundaries of the brute force approach but to use it where possible. This pilot study has shown that the PAS procedure 3.0 is able to improve the corporate real estate (CRE) decision-making process and hereby improve the corporate real estate (CRE) alignment. This will result in more added value of real estate to the businesses in which the tool is used.
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Purpose–Alignment of corporate real estate to a corporation’s business strategy is a long-standing issue. In the past multiple models have been developed to support this process, but research shows that they fall short on certain parts of the CRE alignment activity, often lack transparency and fail to choose the real estate strategy that delivers most value to the organisation. The Preference-based Accommodation Strategy (PAS) procedure has been proposed as a solution to these issues and results in two pilots are positive. However, to optimise the results, a brute force approach should be implemented in the procedure. This paper reports on a pilot study wherein this PAS procedure 3.0 was tested and evaluated.
Approach–A literature study is conducted to develop a theoretical basis for the implementation of a brute force approach in the PAS procedure. This procedure is implemented in a pilot study by building a mathematical model. During the pilot the users improved the reflection of their preferences in the model, in an iterative process of manually designing portfolio alternatives. A brute force approach is applied to the final model to yield the optimum portfolio alternative. The implementation of the brute force approach is evaluated and it is determined if the approach yields a higher preference rating than the stakeholders can achieve by manual design.
Findings–The pilot study shows that the brute force approach is able to improve the results over the manual design and yields a 7% increase in the real estate alignment compared to the current portfolio. The evaluation results reveal that the implementation process results in acceptance of- and trust in the model. Moreover, the users are very positive about the PAS and indicate that the model better reflects their preferences than their current process. They even indicate that they want to incorporate the tool in their daily decision-making process.
Implications–This pilot study was less complex than previous pilots, therefore the PAS procedure 3.0 should be tested in more complex pilots to discover the boundaries of the brute force approach but to use it where possible. This pilot study has shown that the PAS procedure 3.0 is able to improve the corporate real estate (CRE) decision-making process and hereby improve the corporate real estate (CRE) alignment. This will result in more added value of real estate to the businesses in which the tool is used.
The department of MBE was originally called Real Estate & Project Management (BMVB: ‘Bouwmanagement & Vastgoedbeheer’) covering the domains of construction management and real estate management. The “raison d’être” for this new department was based on the recognition that a fair amount of architecture graduates were more interested in managing a building’s design and construction process than in its actual design. These students, however, were not taught management theories and skills at that time. As a result, they would end up in the construction industry poorly equipped for doing the
job they were required to do. This lack in education was addressed by our new department. Our graduates are multi-disciplinary schooled, not only in architectural design, computational design and management theories and skills, but very importantly also in building economics.
The research domain Building Economics comprises research on the market and the value of buildings, and the relationship between quality and revenues, and costs and fi nance (Soeter et al., 2009). In the real estate market, the space market is interlinked with the asset market and the construction market. The Building Economy research programme analyses the real estate portfolios of investors. In what type of properties do they invest and what are the returns, risk profi les and outcomes?
A crucial aspect in this is the expected rental income. To a large extent, the research focuses on the rent level and return on investment, in connection to location and building characteristics (quality) (see for instance Koppels et al.,
2009, 2011). A guideline for studies on costs and quality is the consideration
that organisations are interlinked with their location and buildings. An optimal solution for accommodation depends on the selected approach. For example, with a lowest cost approach, a minimum of investment costs, running costs and
life-cycle costs are sought after, usually resulting in low values as well. Research on the relationship between cost, quality, and willingness-to-pay is important to understand and steer on costs and quality.
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The department of MBE was originally called Real Estate & Project Management (BMVB: ‘Bouwmanagement & Vastgoedbeheer’) covering the domains of construction management and real estate management. The “raison d’être” for this new department was based on the recognition that a fair amount of architecture graduates were more interested in managing a building’s design and construction process than in its actual design. These students, however, were not taught management theories and skills at that time. As a result, they would end up in the construction industry poorly equipped for doing the
job they were required to do. This lack in education was addressed by our new department. Our graduates are multi-disciplinary schooled, not only in architectural design, computational design and management theories and skills, but very importantly also in building economics.
The research domain Building Economics comprises research on the market and the value of buildings, and the relationship between quality and revenues, and costs and fi nance (Soeter et al., 2009). In the real estate market, the space market is interlinked with the asset market and the construction market. The Building Economy research programme analyses the real estate portfolios of investors. In what type of properties do they invest and what are the returns, risk profi les and outcomes?
A crucial aspect in this is the expected rental income. To a large extent, the research focuses on the rent level and return on investment, in connection to location and building characteristics (quality) (see for instance Koppels et al.,
2009, 2011). A guideline for studies on costs and quality is the consideration
that organisations are interlinked with their location and buildings. An optimal solution for accommodation depends on the selected approach. For example, with a lowest cost approach, a minimum of investment costs, running costs and
life-cycle costs are sought after, usually resulting in low values as well. Research on the relationship between cost, quality, and willingness-to-pay is important to understand and steer on costs and quality.
Conference paper
(2016)
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A. Greco, T. Konstantinou, H.R. Schipper, R. Binnekamp, E. Gerritsen, R. de Graaf, A. van den Dobbelsteen
Net zero energy is already an ambitious target for several buildings, especially since the DIRECTIVE 2010/31/EU that requires increasing the number of nearly zero energy buildings. The existing commercial building stock needs to be included in order to achieve the 2020 EU environmental targets. The main barriers of zero energy refurbishment of existing nonresidential buildings appear to be financial rather than technical, next to a number of other extrinsic factors that do not stimulate such an investment. While a business case for new zero energy buildings is believed to exist, controversial opinions can be found with respect to refurbishment of large buildings. The present study aims to identify the factors that affect the feasibility of the zero energy refurbishment of existing commercial buildings, while suggesting ways to create the business case addressing the Dutch market. Through interviews with real estate investors, the study identified the financial and technical barriers encountered today to undertake deep energy retrofit. Subsequently, the design interventions needed to refurbish a Dutch office building and meeting the net zero energy target were evaluated using a software complying with the Dutch standards NEN 7120. A risk and sensitivity analysis with Monte Carlo simulations showed the influence that design aspects, energy price and landlord-tenant agreements have on the business case. The study has concluded that a business case considering the energy savings alone is not sufficient to convince investors. However, when the design provides additional benefits, such as increasing the property value, the refurbishment can become feasible. This is an important observation to promote the refurbishment towards a zero energy building stock.
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Net zero energy is already an ambitious target for several buildings, especially since the DIRECTIVE 2010/31/EU that requires increasing the number of nearly zero energy buildings. The existing commercial building stock needs to be included in order to achieve the 2020 EU environmental targets. The main barriers of zero energy refurbishment of existing nonresidential buildings appear to be financial rather than technical, next to a number of other extrinsic factors that do not stimulate such an investment. While a business case for new zero energy buildings is believed to exist, controversial opinions can be found with respect to refurbishment of large buildings. The present study aims to identify the factors that affect the feasibility of the zero energy refurbishment of existing commercial buildings, while suggesting ways to create the business case addressing the Dutch market. Through interviews with real estate investors, the study identified the financial and technical barriers encountered today to undertake deep energy retrofit. Subsequently, the design interventions needed to refurbish a Dutch office building and meeting the net zero energy target were evaluated using a software complying with the Dutch standards NEN 7120. A risk and sensitivity analysis with Monte Carlo simulations showed the influence that design aspects, energy price and landlord-tenant agreements have on the business case. The study has concluded that a business case considering the energy savings alone is not sufficient to convince investors. However, when the design provides additional benefits, such as increasing the property value, the refurbishment can become feasible. This is an important observation to promote the refurbishment towards a zero energy building stock.
One of the long-standing issues in the field of corporate real estate corporate strategy. Extensive research into existing approaches brought valuable insights into steps, components and variables that are needed in the alignment process. Despite that, it is not clear if existing approaches had much uptake in practice and they fall short in a number of aspects. In most models little to no attention is given to the design and selection of the alternative portfolio that adds most value to the organisation. Furthermore, university campus managers have indicated that they need better information and tools to support campus decision making.
The Preference-based Accommodation Strategy design (PAS) procedure is a tool to enhance CRE decision making and has been developed to remove these gaps. In the PAS design procedure decision makers define criteria and iteratively test and adjust these criteria by designing new real estate portfolios. The portfolio design that adds most value to the organisation, i.e. has the highest overall preference is suggested as the portfolio that optimally aligns real estate to corporate strategy. The PAS procedure is iteratively repeated with the participants in a series of interviews and workshops. Two pilot studies have been performed at the Delft University of Technology (DUT). The study into the portfolio of lecture halls showed that stakeholders were able to use the procedure successfully. This paper reports the pilot study for their portfolio of food facilities. The objective of this research is to test if participants are able to perform the PAS procedure. Therefore a mathematical model of the group decision making process is designed and tested.
This pilot study also reveals that the participants by completing the steps in the PAS procedure are able to express their preferences accordingly. They designed an alternative portfolio with a higher overall preference score than their current real estate portfolio. In addition, the design method is evaluated positively. The positive results suggest that designing a strategy by using the PAS procedure is a suitable approach to alignment. The PAS design procedure enables CRE managers to determine the added value of a real estate strategy. Because the PAS design method is generic in nature it can be used for a wide range of real estate portfolios.
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One of the long-standing issues in the field of corporate real estate corporate strategy. Extensive research into existing approaches brought valuable insights into steps, components and variables that are needed in the alignment process. Despite that, it is not clear if existing approaches had much uptake in practice and they fall short in a number of aspects. In most models little to no attention is given to the design and selection of the alternative portfolio that adds most value to the organisation. Furthermore, university campus managers have indicated that they need better information and tools to support campus decision making.
The Preference-based Accommodation Strategy design (PAS) procedure is a tool to enhance CRE decision making and has been developed to remove these gaps. In the PAS design procedure decision makers define criteria and iteratively test and adjust these criteria by designing new real estate portfolios. The portfolio design that adds most value to the organisation, i.e. has the highest overall preference is suggested as the portfolio that optimally aligns real estate to corporate strategy. The PAS procedure is iteratively repeated with the participants in a series of interviews and workshops. Two pilot studies have been performed at the Delft University of Technology (DUT). The study into the portfolio of lecture halls showed that stakeholders were able to use the procedure successfully. This paper reports the pilot study for their portfolio of food facilities. The objective of this research is to test if participants are able to perform the PAS procedure. Therefore a mathematical model of the group decision making process is designed and tested.
This pilot study also reveals that the participants by completing the steps in the PAS procedure are able to express their preferences accordingly. They designed an alternative portfolio with a higher overall preference score than their current real estate portfolio. In addition, the design method is evaluated positively. The positive results suggest that designing a strategy by using the PAS procedure is a suitable approach to alignment. The PAS design procedure enables CRE managers to determine the added value of a real estate strategy. Because the PAS design method is generic in nature it can be used for a wide range of real estate portfolios.