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研究了制造车间中机床和被加工零件的分组问题，可减少零件加工过程中由于在制造单元组间的运输而增加成本函数．使用遗传算法，以染色体编码表示机床分组，以常用的交叉、变异算子对编码进行操作，以变更各单元内的机床组成．通过不同编码对一组零件加工时成本函数的比较，选择遗传后代，组成最佳的制造单元．以遗传算法对两个典型的机群分组算例进行了计算，并与已有结果进行了对照．
Studied the grouping of machine tools and parts to be machined in a manufacturing shop, and reduced the cost function due to transportation between manufacturing unit groups during parts machining. Genetic algorithms are used to represent the machine tool grouping by chromosome coding, and the codes are operated by the common crossover operator and mutation operator to change the machine components in each unit. Through different coding of a set of parts processing cost function comparison, select the genetic offspring, the best composition of the manufacturing unit. Two typical cluster grouping cases were calculated by genetic algorithm and compared with the existing results.