文件名称:GS_CH_MOPSO_Grey
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- 上传时间：2013-09-20
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文件大小：19.5kb
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多目标非线性约束的粒子群算法，采用灰度理论，混沌理论，动态惩罚函数，可针对任何复杂函数进行优化，效果很好-Nonlinear constrained multi-objective particle swarm algorithm, using gray theory, chaos theory, dynamic penalty function can be optimized for any complex function, the effect is very good
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下载文件列表
GS_CH_MOPSO_Grey/AbsoluteGreyIncidence.m
GS_CH_MOPSO_Grey/BtypeGreyIncidence.m
GS_CH_MOPSO_Grey/CtypeGreyIncidence.m
GS_CH_MOPSO_Grey/DengTypeGreyIncidence.m
GS_CH_MOPSO_Grey/discrete.asv
GS_CH_MOPSO_Grey/discrete.m
GS_CH_MOPSO_Grey/emigrant_chao.asv
GS_CH_MOPSO_Grey/emigrant_chao.m
GS_CH_MOPSO_Grey/hs_err_pid5740.log
GS_CH_MOPSO_Grey/ImproveAbsoluteGreyIncidence.m
GS_CH_MOPSO_Grey/ImproveRelativeGreyIncidence.asv
GS_CH_MOPSO_Grey/ImproveRelativeGreyIncidence.m
GS_CH_MOPSO_Grey/Pso_Object.m
GS_CH_MOPSO_Grey/Pso_Opt.m
GS_CH_MOPSO_Grey/Pso_Opt_fun_1.m
GS_CH_MOPSO_Grey/Pso_Opt_fun_2.m
GS_CH_MOPSO_Grey/Pso_restrain.m
GS_CH_MOPSO_Grey/RelativeGreyIncidence.m
GS_CH_MOPSO_Grey
GS_CH_MOPSO_Grey/BtypeGreyIncidence.m
GS_CH_MOPSO_Grey/CtypeGreyIncidence.m
GS_CH_MOPSO_Grey/DengTypeGreyIncidence.m
GS_CH_MOPSO_Grey/discrete.asv
GS_CH_MOPSO_Grey/discrete.m
GS_CH_MOPSO_Grey/emigrant_chao.asv
GS_CH_MOPSO_Grey/emigrant_chao.m
GS_CH_MOPSO_Grey/hs_err_pid5740.log
GS_CH_MOPSO_Grey/ImproveAbsoluteGreyIncidence.m
GS_CH_MOPSO_Grey/ImproveRelativeGreyIncidence.asv
GS_CH_MOPSO_Grey/ImproveRelativeGreyIncidence.m
GS_CH_MOPSO_Grey/Pso_Object.m
GS_CH_MOPSO_Grey/Pso_Opt.m
GS_CH_MOPSO_Grey/Pso_Opt_fun_1.m
GS_CH_MOPSO_Grey/Pso_Opt_fun_2.m
GS_CH_MOPSO_Grey/Pso_restrain.m
GS_CH_MOPSO_Grey/RelativeGreyIncidence.m
GS_CH_MOPSO_Grey
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