Abstract

AbstractGroundwater is considered as an important source of freshwater for a variety of purposes including drinking, domestic, industrial, and irrigation uses. Because of increasing population and life standards, there is a growing need for the optimum utilization of groundwater resources. In this paper, a multiobjective particle swarm optimization model with a new evolutionary strategy based on the compromise solution of the Pareto-front optimal solutions is presented. The advantage of this proposed model stems from using a unique Pareto-compromise solution to drive the fitness calculations of the evolutionary process. The new evolutionary strategy is verified on a variety of multiobjective standard test problems with either connected or disconnected Pareto fronts. The proposed multiobjective evolutionary strategy is reminiscent of single-objective optimization, in that its fitness assignment and convergence criteria are both based on tracking a single evolving solution over the search history. Details o...

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