Multiobjective evolutionary optimization of water distribution systems: Exploiting diversity with infeasible solutions

JOURNAL OF ENVIRONMENTAL MANAGEMENT

卷:183

Article

Tanyimboh, Tiku T.¹  Seyoum, Alemtsehay G.¹ 

[1] Univ Strathclyde, Dept Civil & Environm Engn, James Weir Bldg,75 Montrose St, Glasgow G1 1XJ, Lanark, Scotland

关键词: Water supply;    Dynamic simulation;    Constraint handling;    Minimum solution vector;    Maximum solution vector;    Infrastructure planning;   

DOI  :  10.1016/j.jenvman.2016.08.048

来源: Elsevier

【 摘 要 】

This article investigates the computational efficiency of constraint handling in multi-objective evolutionary optimization algorithms for water distribution systems. The methodology investigated here encourages the co-existence and simultaneous development including crossbreeding of subpopulations of cost-effective feasible and infeasible solutions based on Pareto dominance. This yields a boundary search approach that also promotes diversity in the gene pool throughout the progress of the optimization by exploiting the full spectrum of non-dominated infeasible solutions. The relative effectiveness of small and moderate population sizes with respect to the number of decision variables is investigated also. The results reveal the optimization algorithm to be efficient, stable and robust. It found optimal and near-optimal solutions reliably and efficiently. The real-world system based optimization problem involved multiple variable head supply nodes, 29 fire-fighting flows, extended period simulation and multiple demand categories including water loss. The least cost solutions found satisfied the flow and pressure requirernents consistently. The best solutions achieved indicative savings of 48.1% and 48.2% based on the cost of the pipes in the existing network, for populations of 200 and 1000, respectively. The population of 1000 achieved slightly better results overall. (C) 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license.

【 授权许可】

Free