multi-objectivewaste loadallocation in riversystembymopsoalgorithm

this paper explores the capabilities of multi-objective particle swarm optimization algorithmin a simulation-optimization model for solving waste load allocation problems. the main goals are totaltreatment costs, violation of the water quality standards and equity. in this research, the water qualitysimulation model is coupled with a multi-objective optimization model, mopso. in order to derive nondominatedsolutions, two different optimization models are used. the first is referred to as the cost versusquality model and the second one also consider minimizing cost and inequity. for the each case, the trade-offcurve (pareto front) is derived and the best non-dominated solution on the trade-off could be selected bystakeholders and decision makers. the proposed model has been developed for haraz river in the northernpart of iran which represented scenarios considering different interests and answered questions to modifyscenarios according to the decision makers’ideas. solutions were compared with nsga-ii, and the resultsdemonstrate a suitable convergence and diversity of proposed algorithm.