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Multi-objective genetic algorithm for optimal scheduling of chlorine dosing in water distribution systems

机译:用于水分配系统中氯计量液的最佳调度的多目标遗传算法

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This paper presents two new multi-objective genetic algorithm models using a Pareto-based selection technique for determining the optimal schedule of chlorine dosing within a water distribution system with multiple, competing objectives: primarily disinfection control and aesthetic control. Formulating the optimal dosing problem using a Pareto-based multi-objective genetic algorithm offers water utilities an innovative solution technique, with each optimisation simulation returning a Pareto-optimal set of candidate solutions. An overview of the object-oriented application architecture, encapsulating each model, is also given, including the independent linked design with the water network simulation program. Both models were applied to a hypothetical distribution system, including comparison with existing non-Pareto techniques. Results are discussed, including the advantages of using the new Pareto-based multi-objective models.
机译:本文呈现了两种新的多目标遗传算法模型,采用了基于帕累托的选择技术,用于确定具有多种,竞争目标的水分配系统中氯带剂量的最佳时间表:主要是消毒控制和美学控制。使用基于帕累托的多目标遗传算法制定最佳计量问题,提供了一种创新的解决方案技术,每个优化仿真都返回帕累托最优的候选解决方案。还给出了面向对象应用架构的概述,封装每个型号,包括与水网络仿真程序的独立链接设计。这两种模型都应用于假设的分布系统,包括与现有的非帕累托技术进行比较。讨论了结果,包括使用新的基于帕累托的多目标模型的优点。

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