4.3 Article

Toward Sustainable Urban Drainage Infrastructure Planning: A Combined Multiobjective Optimization and Multicriteria Decision-Making Platform

Journal

Publisher

ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)WR.1943-5452.0001389

Keywords

Urban drainage systems; Hybrid green-blue-gray infrastructures; (de)centralization (DC); Multicriteria decision making (MCDM); Multiobjective optimization (MOO); Stakeholder engagement

Funding

  1. BMBF-DAAD Sustainable Water Management: Study Scholarships and Research Grants 2015 [57156376]

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This study introduces a generic solution in a multicriteria decision making platform to optimize hybrid urban drainage infrastructures and investigate trade-offs between performance indicators and system configuration. Results confirm the framework's ability to handle complex optimization problems effectively.
This study aims to introduce a generic solution in the context of a multicriteria decision making (MCDM) platform to (1) facilitate the optimization of hybrid (de)centralized urban drainage infrastructures with many decisions and often conflicting objectives (reliability, resilience, sustainability, and construction costs); (2) investigate the trade-offs between performance indicators and system configuration; and (3) avoid conflicts between optimization analysts and decision makers by involving the latter in different stages of planning. For this purpose, first, all optimum design scenarios of hybrid urban drainage systems (UDSs) are generated through multiobjective optimization (MOO). Then a platform based on MCDM is presented to comprehensively analyze the solutions found by MOO and to rank the solutions. For the sake of demonstration, the proposed framework is applied to a real case study. The results confirm the ability of the proposed framework in handling many decisions, objectives, and indicators for solving a complex optimization problem in a reasonable time by delivering realistic solutions. In addition, the results demonstrate the important role of the degree of (de)centralization (DC) and the layout configuration in obtaining optimal solutions.

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