Multi-objective Evolutionary Algorithms Assessment for Pump Scheduling Problems

2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) Pub Date : 2019-11-01 DOI:10.1109/CHILECON47746.2019.8987982

Jimmy H. Gutiérrez-Bahamondes, Yamisleydi Salgueiro, D. Mora-Meliá, M. Alsina, Sergio A. Silva-Rubio, P. Iglesias-Rey

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引用次数: 1

Abstract

The shortage of drinking water is one of the biggest problems facing humanity today. Solving this problem necessarily involves an optimal use of this resource, starting from the pumping. Determining the water pumping regime to meet the demands of a city is a multi-objective complex problem. One of the steps to solve this problem is assessing which multiobjective optimizer has better performance. In this work, we provide a methodology for the comparison of multi-objective evolutionary algorithms in the water pumping regime optimization problem through the combination of the EPANET and the jMetal framework. Both were validated in the comparison of NSGA-II, SPEA2, and SMPSO to optimize the pumping regime on the water distribution networks Van Zyl, Baghmalek, and Anytown. The quality indicators Spread, Epsilon, and Hypervolume, allow assessing the superiority/competitivity statistically of one method over others in terms of solutions’ convergence and distribution. The experimental results show that the combination of EPANET and jMetal provide the ideal environment to perform MOEAs comparisons effectively.

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泵调度问题的多目标进化算法评估

饮用水短缺是当今人类面临的最大问题之一。要解决这一问题，就必须从抽水开始，优化利用这一资源。确定满足城市用水需求的抽水制度是一个多目标的复杂问题。解决这个问题的步骤之一是评估哪个多目标优化器具有更好的性能。在这项工作中，我们通过EPANET和jMetal框架的结合，为水泵状态优化问题中的多目标进化算法的比较提供了一种方法。通过NSGA-II、SPEA2和SMPSO的比较，验证了两者的有效性，以优化Van Zyl、Baghmalek和Anytown配水网络的抽水制度。质量指标Spread、Epsilon和Hypervolume允许在统计上评估一种方法在解决方案的收敛性和分布方面优于其他方法的优势/竞争力。实验结果表明，EPANET和jMetal的结合为有效地进行moea比较提供了理想的环境。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

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