遗传算法在SPLP问题上的应用  

Application of Genetic Algorithm in Simple Plant Location Problems

作　　者：金煌[1] 陈铁英[1] 

机构地区：[1]华中科技大学系统工程研究所,湖北武汉430074

出　　处：《兵工自动化》2004年第4期16-18,共3页Ordnance Industry Automation

摘　　要：采用遗传算法求解SPLP优化问题,用染色体编码表示仓库的开关状态,随机生成初始群体。定义适应度函数估算适应度。选择优良个体随机配对,设定交叉点使配对个体彼此交换部分信息。随机改变个体基因链,经选择、交叉、变异运算得到下一代群体,再把优良个体复制到新的群体中。并用爬山算法优化新群体,使群体迅速逼近最优。The simple plant location problems are resolved with genetic algorithm, first the state of the warehouse was expressed by chromosome coding, early colony was generated randomly. Define the fitness function to estimate fitness. The choiceness unit was chose to make a pair randomly, fix the crossing. Through chosing, crossing and mutation calculation, the next generation was gained, then copy the choiceness unit to the new generation. The new generation was optimized with local search algorithm to make it avoid plunge in local optimize solution.

关 键 词：遗传算法 SPLP 适应度 爬山算法 优化 

分 类 号：O223[理学—运筹学与控制论]