Abstract: Coevolutionary algorithms prove to be powerful in solving combinatorial optimization problems.Different parts of population chromosomes，also called coevolution subsets，are used for the localized coevolution during the whole coevolution process.For flexible job shop scheduling problem（JSP），the solution quality of scheduling depends on the result of process planning.This means process planning and scheduling are tightly interwoven with each other.Symbiotic evolutionary algorithm，as one type of coevolutionary algorithm，has been proved to be a good alternative for dealing with complicated flexible JSP.How does the size of coevolution subset impact the symbiotic evolutionary algorithm is to be studied on the basis of a symbiotic evolutionary algorithm for a flexible JSP.Different coevolution subsets are tested with the same environment and compared upon solution quality.Average solution quality and capability for searching the best solution are the two most important aspects to be considered.The experimental results demonstrate that there does not exist a statistically significant difference among the alternatives，and besides，larger coevolution subset will consume more sorting time during evolution process.

Key words: coevolution subset, job shop scheduling problem, symbiotic evolutionary algorithm

摘要： 共生进化算法求解复杂组合问题时表现了良好的性能，其选择邻域实现局部进化。对于复杂的的柔性作业调度组合问题，作业调度结果的好坏首先依赖流程设计的质量。以共生进化算法求解复杂柔性作业调度为例，测试不同邻域规模对共生进化算法搜索性能的影响。仿真结果表明，局部进化邻域规模的大小对共生进化算法在平均求解质量及对最优解的逼近能力两个方面均没有显著影响，过大的局部进化邻域会增加算法中排序操作计算量。

关键词: 邻域, 作业调度, 共生进化算法