GS_CH_MOPSO_Grey
代码说明：
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)
文件列表：
GS_CH_MOPSO_Grey
................\AbsoluteGreyIncidence.m,903,2013-06-05
................\BtypeGreyIncidence.m,919,2013-06-05
................\CtypeGreyIncidence.m,1214,2013-06-05
................\DengTypeGreyIncidence.m,1220,2013-06-05
................\discrete.asv,965,2013-06-05
................\discrete.m,895,2013-06-05
................\emigrant_chao.asv,1111,2013-06-05
................\emigrant_chao.m,1121,2013-06-05
................\hs_err_pid5740.log,16276,2013-06-08
................\ImproveAbsoluteGreyIncidence.m,1108,2013-06-05
................\ImproveRelativeGreyIncidence.asv,821,2013-06-05
................\ImproveRelativeGreyIncidence.m,1263,2013-06-05
................\Pso_Object.m,6937,2013-06-06
................\Pso_Opt.m,9600,2013-06-08
................\Pso_Opt_fun_1.m,905,2013-06-05
................\Pso_Opt_fun_2.m,1715,2013-06-05
................\Pso_restrain.m,4594,2013-06-06
................\RelativeGreyIncidence.m,1034,2013-06-05
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