激光杂志
激光雜誌
격광잡지
LASER JOURNAL
2015年
1期
122-127
,共6页
车间调度%混沌算子%种群多样性%多目标优化%粒子群算法
車間調度%混沌算子%種群多樣性%多目標優化%粒子群算法
차간조도%혼돈산자%충군다양성%다목표우화%입자군산법
scheduling%chaos operator%population diversity%multi-objective optimization%particle swarm algo-rithm
针对当前车间调度多目标优化研究存在收敛速度慢、精度低的问题，提出了混沌多目标粒子群优化算法。在算法中，设计了一种新的叠加Logistic扰动的Tent混沌映射算子，通过该算子周期性地更新种群以保证种群的多样性；对收缩粒子群算法进行了扩展使其能够快速收敛到Pareto前沿。通过标准测试问题与实际应用对所提方法进行了验证，实验结果显示混沌多目标粒子群优化算法无论在收敛速度还是在优化精度上都优于其它典型多目标进化算法。
針對噹前車間調度多目標優化研究存在收斂速度慢、精度低的問題，提齣瞭混沌多目標粒子群優化算法。在算法中，設計瞭一種新的疊加Logistic擾動的Tent混沌映射算子，通過該算子週期性地更新種群以保證種群的多樣性；對收縮粒子群算法進行瞭擴展使其能夠快速收斂到Pareto前沿。通過標準測試問題與實際應用對所提方法進行瞭驗證，實驗結果顯示混沌多目標粒子群優化算法無論在收斂速度還是在優化精度上都優于其它典型多目標進化算法。
침대당전차간조도다목표우화연구존재수렴속도만、정도저적문제，제출료혼돈다목표입자군우화산법。재산법중，설계료일충신적첩가Logistic우동적Tent혼돈영사산자，통과해산자주기성지경신충군이보증충군적다양성；대수축입자군산법진행료확전사기능구쾌속수렴도Pareto전연。통과표준측시문제여실제응용대소제방법진행료험증，실험결과현시혼돈다목표입자군우화산법무론재수렴속도환시재우화정도상도우우기타전형다목표진화산법。
Since the current job shop scheduling multi-objective optimization has the drawbacks of slow conver-gence speed and low accuracy, it proposes a chaotic multi-objective particle swarm optimization algorithm. In the algo-rithm, designed the Tent chaotic mapping a new stack Logistic disturbance, the operator periodically update population in order to ensure the diversity of population;on the contraction of particle swarm algorithm is extended so that it can rapidly converge to the Pareto front. The standard test problems and practical application to verify the proposed meth-od, experimental results show that the chaotic multi-objective particle swarm optimization algorithm both in conver-gence speed and optimization accuracy is better than other typical multi-objective evolutionary algorithm.
