本资源包含灰狼优化算法（GWO）代码以及粒子群算法（PSO），主函数为使用灰狼优化和粒子群优化对不同函数进行寻优并将两种算法的比较结果绘图显示
2019-12-21 21:46:11
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The Grey Wolf Optimizer(GWO) algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, three main steps of hunting, searching for prey, encircling prey, and attacking prey, are implemented to perform optimization.
2019-12-21 21:43:31
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比较新的优化算法，用差分进化(DE)改进原始的灰狼优化（GWO）得到的HGWO（DE-GWO）算法，以优化SVR参数为例，matlab源码有详细中文注释，便于使用，可以根据需要自己修改，是很好地学习材料。
2019-12-21 21:27:53
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该脚本实现了PSO和GWO优化算法的混合。不仅包含matlab源代码，还有PSO-GWO 和 GWO的matlab运行结果对比图。
2019-12-21 20:52:12
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用灰狼优化算法求解柔性作业车间问题，其中问题的规模为8*8，代码类型为Matlab，编码方式为三维实数编码。
2019-12-21 20:27:34
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最原始的灰狼优化算法，全面解释了灰狼优化算法的来源和基础应用，适合初学者。群智能优化算法，灰狼优化算法
2019-12-21 20:18:56
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In the Multi-Objective Grey Wolf Optimizer (MOGWO), a fixed-sized external archive is integrated to the GWO for saving and retrieving the Pareto optimal solutions. This archive has been employed to define the social hierarchy and simulate the hunting behavior of grey wolves in multi-objective search spaces.
2019-12-21 18:56:48
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