A.R.M. Wolfert
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6 records found
1
Preference based decision support system for Waelpolder
An a priori design optimization approach (PDOA) as decision support system, applied to the urban development of Waelpolder
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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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.
Preference and Performance Based Design & Decision Systems in Offshore & Dredging Engineering
A multi-objective design/decision optimisation approach based on sound mathematical modelling of both preference and physical design performance functions
To solve the shortcomings given the current momentum within the ODE industry, a truly integrative Open Systems Design (Odesys) methodology is proposed in this thesis. For this purpose, a new multi-objective optimisation method IMAP is introduced which is operationalised in a Python-based software tool called Preferendus, including a new inter-generational Genetic Algorithm (GA) solver.
The application and added value of the Preferendus/IMAP are validated for two demonstrators within the maritime contractor Boskalis.
The first validation case concerns planning and design optimisation in the development of offshore floating wind farms, focusing on scheduling and mooring design. For this purpose, an integration was made with the wind turbine simulation tool OpenFAST. The new Preferendus/IMAP significantly improved the overall tender performance by: 1) providing initial design approaches within a few hours, where currently tender teams spend days working on design alternatives that, in hindsight, were suboptimal; 2) removing tender team bias from the design process and finding design solutions that were otherwise unfairly disregarded; 3) open glass-box modelling support for concurrent design between the asset owner and the contractor.
The second validation case is a decision support optimisation application of a dredging production in which multiple vessels jointly execute a dredging project. Due to different types of disturbances, these vessels often have to wait for each other, reducing the overall efficiency of the project. Current expert-based optimisation approaches are limited in their ability to adjust best-for-project. The new Preferendus/IMAP shows a clear improvement and finds solutions that significantly reduce waiting time while simultaneously achieving high production levels. Moreover, the Preferendus/IMAP outperforms single-sided optimisation on production alone by achieving similar high production levels while also improving other objectives such as CO2 emissions and vessel efficiency.
Steps for further development include: 1) improving OpenFAST integration and modelling; 2) addition of fatigue loading in the anchor design; 3) improving discrete event simulation scheduling modelling; 4) improving runtime by exploring other algorithms and/or programming improvements.
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To solve the shortcomings given the current momentum within the ODE industry, a truly integrative Open Systems Design (Odesys) methodology is proposed in this thesis. For this purpose, a new multi-objective optimisation method IMAP is introduced which is operationalised in a Python-based software tool called Preferendus, including a new inter-generational Genetic Algorithm (GA) solver.
The application and added value of the Preferendus/IMAP are validated for two demonstrators within the maritime contractor Boskalis.
The first validation case concerns planning and design optimisation in the development of offshore floating wind farms, focusing on scheduling and mooring design. For this purpose, an integration was made with the wind turbine simulation tool OpenFAST. The new Preferendus/IMAP significantly improved the overall tender performance by: 1) providing initial design approaches within a few hours, where currently tender teams spend days working on design alternatives that, in hindsight, were suboptimal; 2) removing tender team bias from the design process and finding design solutions that were otherwise unfairly disregarded; 3) open glass-box modelling support for concurrent design between the asset owner and the contractor.
The second validation case is a decision support optimisation application of a dredging production in which multiple vessels jointly execute a dredging project. Due to different types of disturbances, these vessels often have to wait for each other, reducing the overall efficiency of the project. Current expert-based optimisation approaches are limited in their ability to adjust best-for-project. The new Preferendus/IMAP shows a clear improvement and finds solutions that significantly reduce waiting time while simultaneously achieving high production levels. Moreover, the Preferendus/IMAP outperforms single-sided optimisation on production alone by achieving similar high production levels while also improving other objectives such as CO2 emissions and vessel efficiency.
Steps for further development include: 1) improving OpenFAST integration and modelling; 2) addition of fatigue loading in the anchor design; 3) improving discrete event simulation scheduling modelling; 4) improving runtime by exploring other algorithms and/or programming improvements.
Introducing a Load Trend to the Reliability Analysis of Hydraulic Structures
Application of Bayesian Network-supported Reliability Analysis to predict future failure of Pumping Station IJmuiden
Anticipating scope creep in the design phase of infrastructure projects
A case study on scope creep and its effects
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Flexibility and Uncertainty in Infrastructure Investment Valuation
A roadmap for valuing bridge life cycle investments taking flexibility and uncertainty along
If investments are subject to non-diversifiable uncertainties, investors should be compensated for associated risks by using time dependent risk adjusted discount rates for valuation practices. A discussion is taking place on difficulties that occur if this principle is applied to infrastructure investments. Conducted literature research shows that current techniques to correct for non-diversifiable cannot be applied directly to most engineering valuation problems.
A MCA on investment alternatives regarding to the replacement of a bridge in the municipality of Amsterdam demonstrates how expected investment values can be calculated taking along multiple uncertainties and flexibility. Although the value of flexibility is always equal or greater than zero, case study results show that incorporating uncertainty and flexibility in the analysis can also affect the NPV negatively. ...
If investments are subject to non-diversifiable uncertainties, investors should be compensated for associated risks by using time dependent risk adjusted discount rates for valuation practices. A discussion is taking place on difficulties that occur if this principle is applied to infrastructure investments. Conducted literature research shows that current techniques to correct for non-diversifiable cannot be applied directly to most engineering valuation problems.
A MCA on investment alternatives regarding to the replacement of a bridge in the municipality of Amsterdam demonstrates how expected investment values can be calculated taking along multiple uncertainties and flexibility. Although the value of flexibility is always equal or greater than zero, case study results show that incorporating uncertainty and flexibility in the analysis can also affect the NPV negatively.