Description: A new multi-objective particle swarm optimization(MOPSO) is proposed. The proposed algorithms employs three techniques: adaptive
grid algorithms, which can obtain the valid density value of particles in Archive set Pareto optimal solution searching algorithm, which can equalize
the ability of global and local searching Archive pruning techniques, which can remove inferior particles in Archive set to fix the size of Archive set.
The algorithm is applied to solve multi-objective optimal regulation of Three Gorges. The simulation performance indicates the effectiveness of the
presented algorithm with regard to solving the large scale complex multi-objective optimization problem.
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matlab算法程序-多目标粒子群算法\fitness.m
...............................\GetFai.m
...............................\MaximumSpread.m
...............................\mycon.m
...............................\ParticleSwarmOpt.m
...............................\Script.m
...............................\ScriptScript.m
...............................\Spacing.m
...............................\Untitled.m
matlab算法程序-多目标粒子群算法
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