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首页> 外文会议>XIVth International Conference on Computational Methods in Water Resources (CMWR XIV), Jun 23-28, 2002, Delft, The Netherlands >Development of a multi-objective optimization algorithm for assessing tradeoffs between cost, reliability, and cleanup goals for subsurface remediation
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Development of a multi-objective optimization algorithm for assessing tradeoffs between cost, reliability, and cleanup goals for subsurface remediation

机译：开发用于评估地下修复成本，可靠性和清理目标之间权衡的多目标优化算法

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摘要

An algorithm is developed for finding optimal solutions for subsurface remediation design based on minimizing cost, maximizing cleanup performance and maximizing reliability. The multi-objective optimization algorithm is based on the niched Pareto genetic algorithm. Uncertainty in hydraulic conductivity is considered by finding optimal designs for a series of equally likely hydraulic conductivity values. Reliability is measured by determining the number of designs that meet a cleanup objective for a given cost. The simplified approach taken in this work is to demonstrate the concept of finding tradeoff surfaces based on three conflicting objective functions.
机译：在最小化成本，最大化清理性能和最大化可靠性的基础上，开发了一种用于寻找地下修复设计最佳解决方案的算法。多目标优化算法基于适当的帕累托遗传算法。通过为一系列同样可能的水力传导率值找到最佳设计，可以考虑水力传导率的不确定性。通过确定满足给定成本的清理目标的设计数量来衡量可靠性。在这项工作中采用的简化方法是演示基于三个相互冲突的目标函数查找折衷面的概念。

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