An iterative approach to multi-objective engineering design: Optimization of engineered injection and extraction for enhanced groundwater remediation. (July 2015)

• Record Type: Journal Article
• Authors: Piscopo, A.N.; Kasprzyk, J.R.; Neupauer, R.M.
• Is Part Of: Environmental modelling & software. Volume 69(2015:Jul.)
• Page Start: 253
• Page End: 261
• Publication Date: 2015-07
• Subjects: Multi-objective optimization -- Multi-objective evolutionary algorithms -- Groundwater remediation -- Problem formulation -- Visualization; 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.2014.08.030
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: This study contributes an iterative problem reformulation technique for multi-objective evolutionary algorithm (MOEA) decision support. Problem formulations consist of objectives, decision variables, and constraints, and directly influence the results generated by the MOEA. Typically, design problems are optimized based on a single problem formulation established a priori . In this paper, we demonstrate an approach to perform iterative optimization using problem formulations updated from analyses of results from prior rounds of optimization, which often reveal design components not initially considered. To demonstrate the approach, we consider a novel groundwater remediation technique, Engineered Injection and Extraction (EIE), which has never been optimized in the literature. Iterative problem reformulation enabled the MOEA to generate EIE solutions with better performance than the heuristically-developed solution used in prior work. Highlights: We optimize a groundwater remediation strategy using multi-objective optimization. We demonstrate an iterative approach to adapt the problem formulation. We couple visualizations of objective and decision space to analyze solutions.