Many-objective portfolio optimization approach for stormwater management project selection encouraging decision maker buy-in. (January 2019)

• Record Type: Journal Article
• Authors: Di Matteo, Michael; Maier, Holger R.; Dandy, Graeme C.
• Is Part Of: Environmental modelling & software. Volume 111(2019)
• Page Start: 340
• Page End: 355
• Publication Date: 2019-01
• Subjects: Stormwater management -- Water sensitive urban design -- Portfolio optimization -- Many-objective optimization -- Visual analytics -- Multi-criteria decision analysis; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.09.008
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Although formal simulation-optimization approaches have been shown to be able to identify near-optimal outcomes for a range of stormwater management problems, stakeholder acceptance of these solutions can be problematic, especially if there is a lack of familiarity with the optimization processes and simulation model used to arrive at these solutions. To address this problem, a portfolio optimization problem formulation is introduced that allows stormwater best management practices (BMPs) to be evaluated by stakeholders before the portfolio selection process. This enables the search space to be constrained before the BMP optimization process, ensuring that model results are transparent and only represent solutions that are trusted by experienced practitioners. This has the effect of reducing reliance on simulation-optimization involving complex stormwater simulation models, and increasing buy-in to the optimization results. The portfolio optimization formulation is applied to a catchment management problem in Australia, using a typical many-objective optimization approach including visualization techniques. Highlights: Many-objective optimization formulation for selecting catchment stormwater projects. Reduces optimization search space for many-objective analysis. Enhances multi-criteria decision analysis used in practice with optimization.