Scenario-based robust optimization of a water supply system under risk of facility failure. (May 2015)

• Record Type: Journal Article
• Authors: Lan, Fujun; Lin, Wei Hua; Lansey, Kevin
• Is Part Of: Environmental modelling & software. Volume 67(2015:May)
• Page Start: 160
• Page End: 172
• Publication Date: 2015-05
• Subjects: Water supply system design -- Robust optimization -- Benders decomposition; 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.2015.01.012
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: In this paper, we propose a scenario-based robust optimization model for the design of a water supply system considering the risk of facility failure, which is represented as an uncertainty set generated by a finite set of scenarios. New facilities are planned to be built to hedge against the possible failure of existing system facilities that would potentially damage the capacity of the system to meet given user demands. The goal is to build facilities that are both cost-effective and make the system robust. The system robustness is defined as the ability to satisfy user demands for every data realization in the uncertainty set. The proposed model is shown to be equivalent to a large-scale mixed-integer linear program that is solved by a Benders decomposition algorithm. Computational results demonstrate the efficiency of the proposed algorithm, and show that substantial improvement in system robustness can be achieved with minimal increase in system cost. Highlights: The risk of facility failure is modeled by a scenario-generated uncertainty set. A robust optimization model is formulated for water supply system planning. The Benders decomposition algorithm is proposed to solve the model. The proposed algorithm is demonstrated to outperform CPLEX. System robustness can be greatly improved with little increase in system cost.