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A comparative analysis of multi-objective and multialgorithm approaches for the optimal design of distribution transformers

机译:配电变压器优化设计的多目标,多算法方法比较分析

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摘要

This paper presents the sizing of three phase transformer using four intelligentalgorithms namely geometric programming, genetic algorithm, simulated annealing,and particle swam optimization. Four independent objective functions and eightconstraints were used. The comparative analysis carried out on the results obtainedfrom these intelligent algorithms shows that all the outputs from the intelligentalgorithms are the same. The fastness of results shows that geometric programmingis the fastest, while genetic algorithm, simulated annealing, and particle swamoptimization followed in that order. The output results from the cost objective functionwere compared with the results obtained by Masood (2012) and it showed that moneywas saved in the following order, 6.4%, 16.32%, 10.63% and 16.79% respectively forgeometric programming, genetic algorithm, simulated annealing, and particle swamoptimization.
机译:本文利用几何编程,遗传算法,模拟退火和粒子群优化四个智能算法,给出了三相变压器的尺寸。使用了四个独立的目标函数和八个约束。对从这些智能算法获得的结果进行的比较分析表明,这些智能算法的所有输出都是相同的。结果的牢度表明,几何编程是最快的,而遗传算法,模拟退火和粒子游动优化依次进行。将成本目标函数的输出结果与Masood(2012)的结果进行了比较,结果表明,按几何顺序编程,遗传算法,模拟退火,分别以6.4%,16.32%,10.63%和16.79%的顺序节省了资金,和粒子游动优化。

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