Development of a Preference-based Goal Attainment Tool For a Balanced and Optimal Outcome

A Model-Based Decision-Making Approach

Master thesis (2023)

Authors

H. PATEL Civil Engineering & Geosciences

Contributors

H.M. Jonkers Materials and Environment - CEG (supervisor 2)
D. Zhilyaev Materials and Environment - CEG (supervisor 2)
P.H.A.J.M. van Gelder Safety and Security Science - TPM (supervisor 1)
Hans Ramler Integral Design & Management - CEG (supervisor 2)
Faculty
Civil Engineering & Geosciences
Copyright: © 2023 himanshu PATEL
Operations Research Multi-Objective Optimiation Model-based decision making Value-Creation Goal-Attainment Compromised Solution Better Construction
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Published Date

30-11-2023

Language

English

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Faculty

Civil Engineering & Geosciences

Abstract

Equalized involvement of stakeholders in decision-making processes (DMP) allows them to achieve a balanced outcome, when aiming to create value for each participant. However, as the number of stakeholders increases, traditional methods of interactive engagement become more complex, often leading to unbalanced solutions. Identifying such balanced outcomes also becomes more challenging and time-consuming, considering the wide range of potential outcomes. To address this complexity, this thesis introduces a new approach, Preference-based Goal Attainment (PBGA), and develops a tool for its application in DMPs. The PBGA tool facilitates transparent communication of stakeholders' needs, desires, and values within the DMP, helping to bridge satisfaction gaps among various stakeholders and yield an equitable and optimal outcome.

For the development of this tool, a multi-objective optimization framework is proposed. This framework allows stakeholders to integrate their needs, desires, and values as objective functions, with decision parameters represented as variables, in the tool. Crucially, it enables stakeholders to specify preferred states within their objectives, known as preferences. The framework also considers the varying influence of stakeholders by incorporating a weighted goal attainment method. This method focuses on improving the objective with the largest weighted preference deficit in each iteration of the genetic algorithms used in the optimization process.

For testing and validation, the approach is applied to a DMP in a selected case study. Data, including objectives, variables, and stakeholder preferences, are collected through semi-structured interviews, and transformed into a computational format for MATLAB® implementation. The outcomes are verified using the Kolmogorov-Smirnov and Chi-Square comparative methods. Additionally, the tool and its results are validated by stakeholders, ensuring the tool's practicality and acceptance of the new design.

With the PBGA tool, stakeholders can transparently communicate their needs and desires in the DMP and achieve an outcome that involves equal participation from each stakeholder. The thesis concludes with a comprehensive discussion on the practical applications, limitations, and assumptions of the tool, highlighting its potential to improve stakeholder collaboration and decision-making in project management.