Dual problem of sorptive barrier design with a multiobjective approach

Abstract

Sorptive barrier technology is a recently developed tool to separate hazardous contaminants from friendly environment. The design of sorptive barrier refers to configuring different amendments with sorptive ability of organic pollutant, which is an integer programming problem and a relatively time consuming problem as well. In this paper, sorptive barrier design is newly modeled in a biobjective optimization approach, in which the dual problem of sorptive barrier design is deduced. The objectives are to minimize the financial cost and the amount of pollutant leaking through barriers. Then an opposition-based adaptive multiobjective differential evolution algorithm (MODEA-OA) is applied to handle the proposed model. The Pareto optimal front obtained by MODEA-OA spreads accurately and evenly in all three instances tested. To select extreme optimal solutions, the original and dual sorptive barrier design problems can be solved simultaneously. This study suggests that modeling barrier design as a multiobjective optimization problem is an effective approach.