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多obhective GSA算法的matlab代码

于 2022-03-19 发布 文件大小:637.13 kB
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应用背景近年来,已经开发了各种启发式优化方法。许多这些方法的灵感来自于群体行为的性质。本文提出了一种新的优化方法介绍了基于重力和质量相互作用的算法。在建议的算法,搜索代理是一个集合的每个交互的群众基于牛顿引力定律和运动规律。所提出的方法有与一些著名的启发式搜索方法相比。所获得的结果证实所提出的方法在解决各种非线性函数的高性能。 2009 Elsevier公司保留所有权利。关键技术主。M:使用GSA算法主要功能。GSA。M:万有引力搜索算法。初始化。M:初始化代理在搜索空间中的位置,随机。gfield。M:计算每个代理的引力场中的加速度。移动:更新代理的速度和位置。masscalculation。M:计算每个剂质量。gconstant。M:计算引力常数。space_bound。M:检查代理的搜索空间的界限。evaluatef。M:评估代理。test_functions。M:计算目标函数值。test_functions_range。M:给出了边界和搜索空间的维数的测试功能。

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