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‘Healing’ and ‘repairing’ techniques for faster optimization with genetic algorithm

机译:“修复”和“修复”技术可通过遗传算法更快地进行优化

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摘要

This paper presents two techniques, the ‘healing’ and ‘repairing’ that can reduce optimization time when using genetic algorithm for structural optimization. The techniques can be applied to: (a) quickly find feasible designs from completely infeasible set of alternatives, and (b) to make the best infeasible designs feasible. These procedures are implemented into a genetic algorithm ‘VOP’. The performance of the original and the modified version of the algorithm are compared with the widespread genetic algorithm ‘NSGA-II’ for the weight optimization of a 40 000 DWT chemical tanker midship section. The results show that these procedures can decrease the optimization time by approximately half.
机译:本文介绍了两种技术,即“修复”和“修复”,可以在使用遗传算法进行结构优化时减少优化时间。该技术可用于:(a)从完全不可行的替代方案中快速找到可行的设计,以及(b)使最佳的不可行设计可行。这些程序被实现为遗传算法“ VOP”。将算法的原始版本和修改版本的性能与广泛使用的遗传算法“ NSGA-II”进行了比较,以优化40 000 DWT化学品船中段的重量。结果表明,这些程序可以将优化时间减少大约一半。

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