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Comparative analysis of Simulated Annealing, Simulated Quenching and Genetic Algorithms for optimal reservoir operation

机译:模拟退火,模拟淬火和遗传算法优化油藏运行的对比分析

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The present study deals with the application of non-traditional optimization techniques, namely, Simulated Annealing (SA), Simulated Quenching (SQ) and Real-coded Genetic Algorithms (RGA) to a case study of Mahi Bajaj Sagar Project, India. The objective of the study is to maximize the annual net benefits subjected to various irrigation planning constraints for 75% dependable flow scenario. Extensive sensitivity analysis on various parameters used in above techniques indicated that they yielded same solution corresponding to a set of optimal combination of parameters. It is concluded that SA, SQ and RGA can be utilized for efficient planning of any irrigation system with suitable modifications.
机译:本研究涉及非传统优化技术的应用,即模拟退火(SA),模拟淬火(SQ)和实编码遗传算法(RGA)在印度Mahi Bajaj Sagar项目的案例研究中。该研究的目的是在75%可靠流量的情况下,在各种灌溉计划约束下最大化年度净收益。对以上技术中使用的各种参数的广泛敏感性分析表明,它们得出的结果与一组参数的最佳组合相对应。结论是,可以对SA,SQ和RGA进行有效的规划,并对其进行适当的修改,从而有效地规划任何灌溉系统。

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