Two Novel Optimization Strategies Based on PSO and EDA for Water Distribution Network Design
Author(s)
Qi, Xuewei
Potter, Walter D.
Li, Ke
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Abstract
Geographically The optimal design of a water distribution network (WDN) is a highly non-linear, multimodel, and constrained NP-hard combinatorial problem. Particle Swarm Optimization (PSO) is a typical metaheuristic search algorithm inspired by the collective behavior of a migrating bird flock. It has been successfully introduced to solve the WDN optimization problem. However, the widely known premature convergence problem of PSO still needs to be addressed. This paper proposes two new PSO based hybrid models in which an Estimation Distribution Algorithm (EDA) is integrated into a standard PSO framework in order to prevent the optimization process from being trapped in local optima. Two famous benchmark networks from the literature are adopted to evaluate the performance of the proposed new algorithms. Thus far, the current extensive comparisons with previous work on the benchmark examples show that these new methods outperform many other previous models with regard to either the best result achieved or the efficiency of the algorithm.
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Sponsored by: Georgia Environmental Protection Division; U.S. Department of Agriculture, Natural Resources Conservation Service; Georgia Institute of Technology, Georgia Water Resources Institute; The University of Georgia, Water Resources Faculty.
Date
2013-04
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Proceedings