关键词: 双资源约束, 分支种群, 遗传算法, 时窗比较, 压缩时窗

Abstract: To solve the multi-constraints of dual resource constrained job shop scheduling problem,a branch population genetic algorithm was proposed.According to analyzing deficiencies such as poor cost index and lot of time window gap,which caused by pre-scheduling strategy based on time window comparison,the strategy based on compressed time window was proposed and the scheduling prerequisites were demonstrated in accordance with double scheduling indexes to optimize the global performance index effectively through adjustment of jobs scheduling order.Through comparing the results of different scheduling strategies and scheduling algorithms,the superiority of proposed scheduling strategy was verified,which could effectively enhance the local search ability of scheduling algorithm and obtain scheduling results which were more approximate to Pareto front.

Key words: dual resource constrained, branch population, genetic algorithms, time window comparison, compressed time window