灰太狼优化算法
代码说明：
GWO算法模拟了灰狼在自然界中的领导层次和狩猎机制。四种类型的灰狼，如alpha，beta，delta和omega，用于模拟领导层次结构。此外，实施狩猎，搜寻猎物，环绕猎物和攻击猎物的三个主要步骤以执行优化。 压缩包包括：发表的论文、优化算法代码、优化工具箱。(The 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. Compression packages include: published papers, optimization algorithm code, optimization toolbox.)
文件列表：
灰太狼优化算法, 0 , 2019-03-27
灰太狼优化算法\Grey Wolf Optimizer Toolbox（灰太狼优化工具箱）.zip, 168773 , 2019-03-27
灰太狼优化算法\GWO（GWO算法）.zip, 1938668 , 2019-03-27
灰太狼优化算法\灰太狼优化器.pdf, 4464417 , 2019-03-27
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