Ports are critical in global supply chains, and quay walls form one of their most expensive and durable assets. The design and renewal of these structures involve complex decisions in which technical, financial, and other considerations must be balanced against one another. In current practice, such decisions are commonly supported by a Multi-Criteria Decision Analysis (MCDA), yet the methodology is often applied in a qualitative and project-specific manner that leaves the derivation of weights and the treatment of soft criteria unstandardized. Moreover, the design process tends to evaluate a limited set of predefined alternatives and to minimize cost and material use, which does not guarantee that a design is either fit-for-purpose or economically optimal. This thesis therefore develops a two-part decision-support framework that is verified and validated through two case studies at the Port of Rotterdam (PoR).

Part I improves the evaluation process through the application of the Preference Function Modelling (PFM) methodology (Barzilai, 2010) within the Tetra software. Three weighting scenarios were constructed for case study I, in which equal weights, standardized survey weights, and project-specific weights were applied to nine decision criteria. The project-specific scenario reproduced the real-world decision, whereas the equal-weight and standardized survey scenarios did not. These results suggest that the standardized survey weights may serve as an organizational reference, but that they cannot replace project-specific input without critical evaluation.

Part II addresses the generative design stage through a single-objective model that maximizes value quantitatively by means of the Net Present Value (NPV). The model was implemented in Python, which combined a differential evolution algorithm with a Monte Carlo simulation of 500 iterations to account for demand uncertainty. Application to case study II yielded a near-optimal configuration of three berths of 360 m and a modal NPV of approximately EUR 303 M. The model identified the Very Large Bulk Carrier (VLBC) as the design vessel class, whereas the real-world quay wall accommodates the Valemax class. This divergence appears to be driven by the locational quay length constraint and by the dominance of cumulative seaport dues over the operational period.

These two parts together suggest that the framework can improve both the transparency and the economic justification of quay wall design decisions. The PFM-based tool provides a traceable and mathematically consistent evaluation process for quay wall projects, while the optimization model reframes the design problem in terms of value generation rather than cost minimization. Both tools were validated through semi-structured interviews with practitioners, who confirmed their added value as decision support instruments rather than as prescriptive design tools. One limitation is that the optimization adopts a single financial objective from the perspective of the PoR Authority, whereas the conventional process also involves other stakeholders. Future research could therefore extend the model towards a multi-objective optimization, for example through the Preferendus methodology by Wolfert (2023), which would broaden its applicability within the port industry. ... Read more

Real estate is considered one of the five core organisational resources and is expected to add value to organisational performance. Within Corporate Real Estate Management (CREM), a central challenge is the alignment between the demand side (corporate strategy) and the supply side (real estate portfolio). Decision-making in real estate portfolio management is considered complex.

Decision Support Systems (DSS) such as the Preference-Based Accommodation Strategy (PAS) have been developed to support this alignment process by translating stakeholder preferences into measurable and comparable performance indicators. Although PAS provides a structured and preference-based approach to strategic decision-making, earlier pilot studies have indicated that stakeholders experience difficulties in using the accompanying PAS dashboard. These stakeholders mentioned that they struggled to understand the dashboard back and calculations. This resulted in reduced trust in dashboard outcomes and decreased decision-making support. While extensive literature exists on dashboard design principles and effectiveness criteria, no prior research has applied these principles specifically to a DSS context in CREM, nor to the PAS dashboard.
This thesis aims to develop and evaluate a redesigned PAS dashboard based on established dashboard design principles. The central research question is: How can a PAS dashboard be redesigned based on identified design principles, and what lessons can be drawn for dashboard design in general?

A Research Through Design methodology was adopted. First, a structured literature study identified dashboard design principles and criteria for effectiveness. These principles were translated into a design framework and used to analyse the existing PAS dashboard. Subsequently, a redesigned dashboard was developed iteratively. The redesign was verified and evaluated in workshops with participants. User feedback was analysed in relation to the identified effectiveness criteria.
The results indicate that applying design principles, single screen view, simplicity, layering of information, visual clarity, cognitive fit, and tailoring capabilities, contributes to improved stakeholder understanding and perceived usability of the PAS dashboard. The redesigned dashboard better supports the interpretation of preference scores, comparison of alternatives, and identification of interventions. Participants indicated improved transparency of the model backend and a clearer connection between input (preferences) and output (overall performance).

This research contributes to both theory and practice. It provides a structured framework that connects dashboard design principles, effectiveness criteria, and concrete design features for DSS in CREM. Furthermore, it demonstrates how dashboard design can enhance stakeholder engagement and informed decision-making within PAS. The findings offer practical lessons for the further implementation of PAS and for the design of dashboards in comparable decision-support contexts.
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By 2040, the Port of Rotterdam Authority (PoR) intends to replace its fleet with vessels that do not emit greenhouse gases and are modernised. Replacing the entire fleet also presents an opportunity to review and improve the operational processes and the equipment used. This is a complex challenge due to the following three factors: (1) the high number of stakeholders complicating the decision-making process, (2) risk aversion in modifying current business operations due to a lack of clarity regarding the impact of decisions, and (3) the challenge of determining what is feasible while also meeting the expectations of all stakeholders.

The PoR expressed a need and interest in becoming familiar with more scientifically based decision-making methods to help them achieve their ambitious goal. The method should facilitate improved decision-making for complex choices and should consider how the impact of different choices will be made visible, allowing users to explore various fleet combinations regarding the system performance.

Therefore, this master's thesis aims to develop a decision-support tool based on the Preferendus Methodology (from \cite{zhilyaev_best_2022, van_heukelum_socio-technical_2024}), a state-of-the-art approach specifically designed to bridge the gap between what is 'desirable' and what is 'feasible'. By doing this they tool facilitates the finding of the best 'fit for purpose' renewed fleet composition.

This Master's thesis demonstrates the successful development of a 'Preference Based Idealized Design tool and methodology that integrates the Preferendus and Idealised Design methodologies. The tool and methodology are conceptually tested at the Port of Rotterdam for their Fleet Renewal Challenge. The tool facilitates the finding of a solution that is both ‘desirable’ and ‘capable’ by integrating multiple stakeholders' objectives and preferences into the modelled system. Additionally, by incorporating stakeholder preferences, the tool facilitates transparent collaborative decision-making and the integration of both technical and social aspects.

Furthermore, the tool is developed with object-oriented-programming principles that ensure the maintainability and scalability of the tool. This makes it suitable for extensions and applications at other projects.

Additional research can be conducted by applying the Preference-Based Idealised Design tool and methodology to other projects. Ideally, this would be done with a project team that has fully adopted the methodology. It is particularly interesting to apply this tool and methodology to a project involving organisational issues, as the Idealized Design approach is designed for organisational redesign. ... Read more

Delays and cost overruns are common problems in the construction industry. Despite extensive research on their causes and mitigations, these problems persist, suggesting that the challenge is not identifying possible mitigation measures, but rather selecting the optimal combination. Recently, a decision-support tool, Mit-C, was developed to help find the optimal strategy by combining a Monte Carlo simulation with mathematical optimization. However, the tool has a relevant limitation: it does not consider the resources required by the mitigation measures, potentially leading to unrealistic or infeasible solutions.
Consequently, this master thesis addresses this limitation by further developing the project management decision-support tool, Mit-C, through the inclusion of the resources availability and demand required by the mitigation measures. For this purpose, the addition of a significant number of variables and constraints into the original mathematical model was needed, increasing the computational time of the program but improving the realism of the results. The altered model was then validated using a case study: the construction of a warehouse. The tool was used with both simplified and detailed project data to test its performance.
The results demonstrated that including resource constraints has a significant effect on the optimal mitigation strategy and leads to a lower and more realistic probability of finishing the project on time. This difference is more noticeable when using detailed data. It is therefore concluded that while the resource-constrained model produces more pessimistic results, it offers a significantly more realistic, reliable and therefore valuable decision-making tool for project managers. ... Read more

Cities increasingly face challenges regarding climate change, urban densification, biodiversity loss and community needs. These challenges demand for adaptation strategies. Each neighborhood faces unique challenges, requiring locally adapted strategies. Public buildings, often owned by municipalities within a portfolio, can play a key role in these strategies to improve resilience and livability. Yet, due to the diversity and number of assets, deciding where and how to intervene is highly complex. Data and decision support tools such as Multi- Objective Optimization (MOO) and Multi-Criteria Decision Analysis (MCDA) can reduce this complexity, but traditional approaches often exclude stakeholders early, restrict evaluations to predefined solutions, commit aggregation errors, and typically end with Pareto fronts that lack a clear final design.
This thesis develops and tests a MOO decision support tool for the management of building portfolio assets. Based on the Preferendus framework, it integrates stakeholders a priori, avoids fixed solution spaces, applies mathematically sound preference modeling, and converges on a single optimal configuration. A demonstrator case with 25 buildings with data derived from The Hague was used to optimize rooftop interventions (sedum, biodiversity, solar, water retention, and social-commercial roofs), balancing conflicting objectives such as neighborhood needs, CO₂ impact, investment costs, and financial returns.
The tool was validated in a live workshop at Bress, where objectives, weights and preference curves were adjusted in real time to search for a final optimal design configuration. Results showed its ability to support portfolio owners in exploring trade-offs and aligning interventions with objectives. A review by Arcadis confirmed its potential, while also pointing to improvements for further development such as spatial impact modeling, data quality, a more user-friendly interface, and prioritization of assets over time.
In conclusion, this preference-based MOO tool demonstrates that rooftop allocation is an effective demonstrator case for sustainable portfolio asset management. Preferendus proves suitable for structuring complex decision-making and translating stakeholder preferences into optimized, data-driven design strategies, while overcoming key shortcomings in similar studies. ... Read more

Strategic behavior is inherent to multi-actor decision-making, allowing actors to see their goals reflected in the process and outcome, which is needed for achieving satisfaction. Traditional decision-making often favors those with the loudest voices, which can lead to decisions that reflect only the preferences of a few rather than a balanced consideration of all stakeholders' interests. While strategic behavior is necessary, its associated risks such as stagnation, perceived unfair distribution of benefits, and suboptimal solutions are well-documented. These can negatively impact the decision quality. These risks are tied to the strategic approach employed, whether competitive or collaborative, and are influenced by how the decision environment is structured. The literature indicates that a dominant reliance on competitive strategies within such environments often leads to the issues mentioned earlier.
While Decision Support System literature acknowledges the risks of strategic behavior, a lack of behavioral insight has been identified as a limitation. Understanding how decision support systems influence behaviors is crucial for improving their effectiveness. Emphasizing the importance of learning from real-life manifestations of decision-makers' behavior. It is assumed that the limited understanding how strategic behavior unfolds in practice within decision support system (DSS) supported decision-making environments, supports the understanding how these environments influence such behavior. This limited understanding hinders the development of effective decision support systems as well as current decision making practices. This research addressed this gap by employed a behavioral informed approach, used qualitative research methods such as interviewing and directly observing participants behavior with the use of a Decision Support Systems (DSS). Providing an understanding of how decision environments, shape strategic behaviors.
Through a qualitative analysis using the Preference-Based Accommodation Strategy (PAS) approach as a research instrument, this study explored how this design and decision support system facilitates a decision-making environment and influences the use of strategic behavior. Through analyzing the occurrence of these different approaches, collaborative or competitive, within specific decision environments, patterns were identified. These patterns revealed which environmental factors encourage or diminish certain strategies employed. For instance, collaborative patterns increase under conditions of transparency and inclusivity, while competitive patterns decrease as these address the underlying causes that facilitate such behaviors. These were found consistent in both literature, current decision making and the design and decision making process supported and facilitated by the PAS approach. This research provided insight into how the structure of a decision environment, such as the one created by the PAS approach, influences the nature and prevalence of strategic behaviors.
The PAS approach integrates features such as transparent information, transparent modeling and analysis, interdependency of goals, the overall preference score, and open dialogue. These elements create a transparent and inclusive environment where collaborative strategic behavior is naturally incentivized and is both effective and rewarding, reducing the reliance and effectiveness of competitive strategies. The research shows that PAS addresses limitations in current decision-making environments by fostering a transition from competitive to collaborative strategic behavior, through a transparent and inclusive environment.
By moving beyond assumptions, this research provides a clear understanding of how the PAS approach shapes and influences strategic behavior, offering insights into the design of decision support systems and current decision making practices that promote collaborative strategic behaviors over competitive strategic behavior, enhancing the potential to mitigate the risks mentioned earlier.
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In the field of urban development few challenges are as tough as the housing problem. The cause for this is the rapid expansion of urban populations combined with slow construction processes. The Open Design Systems (Odesys) methodology is a preference-based design methodology for creating and evaluating designs. For this it uses a-priori method of optimization, where the preferences of stakeholders for each project objective are determined in the beginning of the process. Designs are thereafter created based on these preferences. Central to the success of preference-based design is the attitude of stakeholders towards using the methodology, which in other words is acceptance for this methodology. How can acceptance be evaluated? To do this the Technology Acceptance Model (TAM) was used. The system design features in the TAM were categorized in the “Use”, “Functionality” and the “Presentation”. Modifications to the Odesys methodology were made in these categories to see the effect on the stakeholder acceptability using the TAM. This research attempted to raise the acceptability for the Odesys methodology with the use of 2 case studies. The conclusion was that for the “Use” category the acceptability was dependent on the project design phase and the involvement of stakeholders. For the “Functionality”, the result reliability and the running time were important factors. The “Presentation” category consisted of the interface and the distinction between group and individual sessions. Modifications to these were developed and tested. This resulted in an increased perceived usefulness and a perceived ease-of-use , which according to the TAM results in an increased acceptance. ... Read more

This thesis aims to design an interactive tool that facilitates collaboration between Microsoft’s teams in the datacenter development design process. Current datacenter development strategies of Microsoft do not sufficiently take into account socio-technical aspects which is causing project delays. Such socio-technical aspects are internally represented by different teams at Microsoft, such as the Community Affairs team and the Environmental team. Incorporating the preferences of all the relevant teams during the design, results in enhanced collaboration through increased mutual insights, which can be used to develop new design solutions. Such new design solutions inherently incorporate more socio-technical aspects... ... Read more

In response to the European Commission's initiative to shift freight transport from road to inland waterways, there is a need to expand the capacity of inland ports to accommodate larger cargo ships. This expansion requires lowering the water bottom, which will increase the forces exerted on the quay walls. The quay walls should therefore be reinforced by applying structural adjustments, for minimal costs and environmental impact. The goal of this thesis is therefore to develop a decision support tool, which is able to directly determine the preferred configuration of structural adjustments. To maximise the aggregated preference of all stakeholders involved while satisfying the systems constraints, the a-priori design optimisation method of the Preferendus is applied.

The tool, developed using computational science, uses Python because of its capability to automate repetitive calculations. It integrates with the program D-Sheet Piling that is used for specific sheet pile calculations. The tool is designed to be used during the preliminary design phase, enabling quick assessment of potential reinforcement adjustments and facilitating insight into the preferred solution. It evaluates three main strategies for quay wall reinforcement: lowering active soil stress, increasing passive soil stress, and enhancing pile stability. The tool uniquely focuses on maximising the aggregated preference of involved stakeholders and is capable of evaluating failure mechanisms of sheet piles.

It is tested on three case studies, all located in the industrial harbour Loven in Tilburg. The results show that the tool effectively proposes which structural adjustments are applicable to create a sheet pile design that satisfies. The thesis concludes by drawing specific conclusions for each structural adjustment considered in the project. Moreover, it concludes that the development of a decision support tool has been successful. In particular, the tool enhances efficiency in sheet pile calculations, offers detailed insights into the environmental and financial impact of adjustments and enables the direct determination of the preferred configuration of structural adjustments. This eliminates the need to choose the preferred configuration from a number of designed variants, which is the current approach.

Additionally, the thesis recommends to conduct a follow-up research on the applicability of underwater anchors, which have shown significant structural potential. Furthermore, it recommends to conduct laboratory tests to potentially improve the cohesion and angle of internal friction of soil layers. If those soil parameters can be improved, no structural adjustment may be necessary to reinforce quay walls at all. ... Read more

Negotiations in urban development projects can take a long time, going back and forward to the designer many times, even leading to stalemate situations. Requirements can be set intuitively, without knowing what the side effects of the constraints will be for the urban development. On top of that, approval of all stakeholders is needed to be able to implement the design. An integral process of decision-making, with cooperation, open communication and considering everyone’s opinion, seems to be challenging when it comes to urban development projects.

Current decision-making methods, such as Linear Programming, are lacking in terms of cooperation between parties, only finding a feasible design for a group of stakeholders and satisfying one party. Considering preferences helps overcome this problem. In this thesis, an a priori design optimization approach (PDOA) has been developed as decision support system, applied and tested on a real-life urban planning case, Waelpolder.

The PDOA returns a quantitative design (Program of Requirements) for the to be developed area which is considering preferences and wishes of stakeholders a priori, before a design is generated. By basing the design on preferences of stakeholders, intuitively determined requirements are avoided and designs will be more compliant to stakeholders’ needs. The PDOA generates a design by optimizing on overall preference. So, finding a feasible solution is guaranteed, on top of that the approach is able to find a most desired group solution.

The Preferendus (based on Tetra) method, where stakeholders do not make the same amount of compromises in a design, is preferred to use in the PDOA rather than the goal attainment method, where stakeholders do the same amount of compromises. This is mainly because the Preferendus returns more extreme designs and can better show the impact of adjustments in requirements in comparison to the more moderate designs generated with goal attainment. In addition, the stakeholders of Waelpolder indicate that it is realistic that one party should do more compromises than another party. Therefore, the Preferendus is better able to support decision-making and open up discussions.

The PDOA allows a new direction in decision-making, where negotiations become an open glass box rather than a black box. Openness & transparency, which is one of the fundamentals of the PDOA, takes away strategic play between stakeholders. Stakeholders are forced to express what they want upfront, before any design is created.

The approach supports negotiations in decision-making as it provides insights in a rapid and simple manner. The tool allows requirement modification, thereby showing the impact of certain requirements and presenting alternative possibilities. In addition, long negotiation processes where stakeholders need to get aligned are avoided because of the required openness and adaptability of the tool.One of the stakeholders within Waelpolder is willing to implement the PDOA within its organization as slip school model in urban development projects, to investigate the effects of adjusting requirements. Due to the iterative value of the approach, the stakeholders are positive about using the approach in other area developments, in an early stage.
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The purpose of this graduation thesis entitled "Probabilistic restructuring of complex construction project activity linking using GERT: an alternate network distribution in mitigation controller" is to analyse the effect of project network structures when the duration of the project activities is distributed stochastically and its following effect on the existing Mitigation Controller©. The researchers at TU Delft have developed a state-of-art tool called Mitigation Controller© (MitC) for automating the search for finding the most cost-effective set of mitigation measures to ensure the probability of the project's completion at a required level. However, there is a modelling error in the project network diagram of this tool. The risks and uncertainties are modelled using a Program Evaluation and Review Technique (PERT) distribution. The current Mitigation Controller has managed
to recreate the human-oriented selection of mitigation measures, but it has not considered all possible scenarios within a complex construction project.

PERT is the most straightforward distribution used for explanatory purposes. This does not reflect reallife conditions. There are instances where certain activities are repeated when the result does not meet the required quality. To overcome the limitations of PERT, it is suggested to implement the Graphical Evaluation and Review Technique (GERT) for scheduling construction projects. A new code
is integrated into the existing Mitigation Controller to generate new network paths based on the probabilistic nature of the project activity. The novel network structure is used to compute the optimal set of mitigation measures using Monte Carlo analysis and linear optimisation. It is also observed that the optimisation solver takes a substantial amount of time to compute depending on the number of activities on the project. An efficient Monte Carlo analysis is implemented to reduce optimisation time within the tool. ... Read more

Environmental sustainability has become an urgent matter on the Dutch political agenda, which will affect the built environment in the near future. Consequently, organizations have to adapt their real estate to new regulations for building performance and their own sustainability goals. The Preference-based Accommodation Strategy (PAS) is a decision-making strategy that aids organizations in finding a Corporate Real Estate Portfolio (CREP) that aligns with the organization’s values. This research aimed to stimulate organizations to improve the environmental sustainability of their CREP by changing the decision-making process. Therefore a sustainability reference model (SuRMo) was developed for PAS and tested on the CREP of Colliers, an international real estate consultancy firm with multiple offices in the Netherlands. In the pilot study, PAS and the SuRMo were used to evaluate three alternatives for a new office space in Utrecht. In an iterative process using the operation research methodology four tests were conducted which compared the outcome of the different decision-making processes. The four tests analysed 1) the current decision-making process, 2) the decision-making process and outcome using PAS, 3) the decision-making process and outcome using PAS with the SuRMo 2.0 and 4) the sustainability performance of Test 1-3 compared to Dutch sustainability goals for 2050. In the three tests the decision outcome resulted in the same office building that performed best in terms of environmental sustainability and matches the governmental goals for 2050. However, between Test 1 and Test 2 the total number of criteria increased from 7 to 37 and from two implicit environmental sustainability criteria to five explicit criteria. The outcome of this research shows that PAS increased the number of environmental sustainability criteria and changed the decision-making process of Colliers from implicit to explicit. The stakeholders expressed the need for the SuRMo because they lack knowledge about environmental sustainability in CREP but concluded that it requires further development for user-friendliness and suitability with PAS. The three actionable conclusions for practise are that PAS should be used in decision-making about CRE with a further developed SuRMo, Green Building Rating Systems should be used for sustainability in CRE decision-making instead of greenhouse gas emissions and project developers and investors can use the explicit outcome of PAS to adapt the supply to the demand on the real estate market. ... Read more

Marine contractors as Heerema Marine Contractors (HMC) have made decommissioning part of their core business. Being the owner of two of the largest semi-submersible crane vessels (SSCVs), the choice for single lift jacket removal is straightforward. However, jackets in the Northern North Sea have a weight and height exceeding the crane capacity of these vessels. Moreover, not all jackets have the structural integrity to be single lifted. Piece small jacket removal can be a solution but is often overlooked by the expectance of being labour-intensive and therefore too expensive. This thesis has the objective to develop a methodology for advising a jacket removal strategy based on a decision support model while comparing piece small versus single lift decommissioning. Comparing the two removal methods is done for a single case study of the Kinsale Bravo jacket, provided by HMC.

The budgets of both removal methods, resulting from the case study, are used as input for the decision support model (DSM). Based on the jacket characteristics, the model uses constrains, rules of thumb and calculations to determine several possible outcomes. These outcomes can then be further optimised based on costs, duration and Co2 emissions. Based on either one of these optimisations a removal scenario can be established by the model.
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With an increase of data documentation and standardization in the construction field in The Netherlands, by norms such as the NEN, there is a possibility to introduce data-driven approaches to certain areas within the construction industry. One of these is the area of budget estimation which is currently fully dependent on a cost estimating professional. Due to the need for estimations that are effective and time-efficient, especially in the primary phase of a project, the potential of introducing a data-driven approach is explored through this thesis. The main objective of this research is the development of a data-driven model, in the form of a Virtual Assistant (VA), to increase the objectivity of the estimation of maintenance budgets of civil engineering structures. From a literature study it is apparent that a fitting data-driven approach for the development of this model is the machine learning technique Decision Tree Classification (DTC). The VA model is developed using historical data, in the form of past input and past output, to train the model and therefore make predictions. Data that is used as past output for this model is a budget range which is documented as a budget class and data that is used as past input is data that is ensured to be objective and gives a description of each bridge. In this case the past input data are the characteristics of the bridge which refer mostly to the dimension of the bridge, the NEN2767, which captures the decomposition and condition of the bridge and to a lesser extent the duration of the maintenance. Through exploring past cases the machine learns rules and predicts the outcome for a new case and therefore predicts the budget range. This shows in which range the budget guess of the estimator should fall. Generally in order to develop a VA model and make it applicable for industry use it is important that an organization that uses such model aligns their data storage with the DTC methodology. This means the introduction of standardizing data in classes and the introduction of standard procedures to document the data. Only when these elements are present within the organization, the data that is used for past input and output can be regarded as objective and the VA can fulfill its function which is to verify the budget estimators guess in an objective manner. ... Read more

Projects in the Complex Engineer-to-order (ETO) sector are subjected to frequent schedule delays caused by engineering changes, supply chain delays and fabrication delays. Project organizations are faced with the challenge of realigning the project duration within the pre-determined time. Schedule delays often lead to 3-5% rise in project cost. This requires an efficient on-the-go reactive approach. At present, the development of strategy to realign the project is extensively manual in nature. This makes the exploration of alternative realigning strategies cumbersome. Lean Project Planning (LPP) and advances in Building Information Modelling (BIM) has enriched on-the-go planning. However, no existing tool equips the project organization to generate, visualize and evaluate possible set of alternative strategies in the event of a triggered change. No attention has been provided to integrate strategy generation algorithms like Evolutionary Algorithm with the LPP and BIM approaches. In this research, a tool was developed to enable the project organizations to generate and visualize strategies integrating Modified Evolutionary Algorithm (MEA) with LPP and BIM from a metaheuristic approach. Furthermore, by undertaking a case study on strategies adopted in real-life change events in a representative Complex ETO project, the reliability of the generated strategies was investigated. The application of the proposed tool in the real-life test case showed the advantages of having multiple alternative realignment strategies. ... Read more

In most of the current starting construction projects, most stakeholders use virgin materials for building elements. Considering climate change, building materials are getting scarce, it is necessary to reduce the number of virgin building materials and improve circularity in the construction industry. The problem is the absence of a middle man that could research the data of existing usable materials and connect this information to stakeholders of starting dwelling projects. This raises the research question: How can an operational model link the supply of existing building materials with the demand for new construction projects in order to reduce the use of virgin materials and thereby improve circularity in the construction industry? The goal of this research is to provide a useful tool for the construction industry to join the transition towards a circular economy. Based on three levels of scale, an operational model is developed that gives a comparison between the materials costs of existing building elements and virgin building elements for a starting dwelling project. This comparison results in insight and an overview for clients, such as municipalities or housing corporations into the costs of potential dwellings built with existing building materials. The operational tool also gives insight in whether or not reusable building materials provide a feasible business case, considering a framework based on the clients input. ... Read more

Deciding on where to locate the company’s assets is one of the main issues of the corporate real estate management field. It should support aligning the organization’s real estate strategy to its organizational objectives. Understanding which information is needed by the decision-makers is crucial to make a proper judgement. However, the awareness of criteria range and their relative importance is lacking in the majority of cases. Although literature recognises a number of structures based on which the criteria should be determined, this knowledge is disperse. It is not fully exploited to enrich the process, due to the scarcity of proper expert tools. As the high level of expertise and the vast amount of knowledge is required, the companies have to rely solely on available human resources.

This thesis provides the development of an expert tool, gathering state-of-art knowledge of location criteria. It strives to improve the (re)location decision making in large companies. It is done by using a hybrid research method, combining the operational research with an empirical one. The determinants for use of certain location criteria and the criteria itself are identified in the literature and linked to each other in a computer program. Through gathering the input from stakeholders, the tool suggests a prioritised list of criteria that should be used in the process.

The expert tool is tested in a pilot study at a company in order to evaluate the effectiveness and attractiveness of the model. It is done with a series of tests and interviews in connection with a pilot case. In addition, the acceptance and trust in the system are challenged.

Overall the tool is evaluated positively. It improves the location decision-making process by increasing the stakeholders understanding of the problem, transparency level, as well as empowering the decision-makers to express their needs that could have been omitted when using a traditional approach. This leads to better assessment of location alternatives. Although the tool itself requires a number of improvements before being able to be used in practice, the idea behind it was highly valued by the users.
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Infrastructure projects in the construction industry are complex. This complexity leads to unavoidable changes in scope. When scope changes are not formalized and managed correctly, it is a risk contributing to project failure. A scope change that is not formalized is scope creep. This research looks at the causes and effects of scope creep in both literature and practice. Furthermore, a case study is conducted to recommend a course of action to anticipate scope creep and its effects.
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Because of increased secularization and decreased parish revenues, obsolete churches are being sold. Adaptive re-use could preserve the cultural heritage these buildings represent, while having many further benefits. Decision modelling helps view these problems with every actor and their viewpoints in context and in relation with one another and the goal function. The case of the [church name] in [village name] was modelled in the original situation as well as an extended case, where more choice options were added and the new position of the Diocese was considered. Then more situations and aspects from various cases were modelled. In this way the fitness for use of a decision model for choices to be made in adaptive re-use of obsolete churches was proven. The use of decision modelling in adaptive re-use of obsolete churches might in the future lead to more successful outcomes. ... Read more

The Dutch construction industry is rising again. The economical crisis has had a major impact on the infrastructure sector, as the sector has experienced many cutbacks. Even though the economy is recovering, the consequences of these cutbacks are still present. According to the Economisch Instituut voor de Bouw (2016), the Dutch infrastructure task for the period of 2015- 2030 amounts to almost €245 billion. In response to the major infrastructure task, the Ministers of Economic Affairs, Housing & Public Services, and Infrastructure & Mobility initiated 'De Bouwagenda' late 2016. The aim of De Bouwagenda is to strengthen the construction sector and to offer solutions to the encountered challenges, as it is not feasible to realise the urgent task within the current system. One of the three concrete objectives that result from the initiative is a productivity increase of at least 10% in the construction industry by 2025. This exploratory research project focuses on improving the design productivity, which can be defined as "the efficiency of the production of a design solution, that is effective to the overall requirements and customer needs". The aim of this research is to discover which (combination of) design method(s) contributes to the enhancement of the design productivity of Dutch infrastructure projects, in order to contribute to the productivity objective of De Bouwagenda at a meta-level. In order to do so, this research identifies the factors that affect the current design process of infrastructure projects, also referred to as waste, and explores design methods that address these wastes... ... Read more