particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.

Packet : 67506265bipso.rar filelist
变异粒子群优化算法（VB版）\swarm.vbw
变异粒子群优化算法（VB版）\PSOUTFIL.TXT
变异粒子群优化算法（VB版）\MSSCCPRJ.SCC
变异粒子群优化算法（VB版）\frmSwarm.frx
变异粒子群优化算法（VB版）\Swarm.exe
变异粒子群优化算法（VB版）\说明.txt
变异粒子群优化算法（VB版）\Swarm1.exe
变异粒子群优化算法（VB版）\Swarm2.exe
变异粒子群优化算法（VB版）\Swarm3.exe
变异粒子群优化算法（VB版）\psoutfil(zhengchang).txt
变异粒子群优化算法（VB版）\Swarm3pm=w.exe
变异粒子群优化算法（VB版）\frmSwarm.frm
变异粒子群优化算法（VB版）\swarm.vbp
变异粒子群优化算法（VB版）

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