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中文摘要：
针对多目标模糊柔性车间调度求解过程中普通遗传算法较难取得最优解的问题,以极大化客户满意度和最小化完工时间为目标,在考虑工件交货期服从模糊时间窗分布等约束条件的基础上,构建了多目标模糊柔性作业车间调度模型,并提出了纵横协同的多种群遗传算法。该算法首先基于工序和机器的两层编码方式产生多个初始种群,然后各种群之间通过相互竞争实现优秀个体的迁移共享,最后通过三个经典调度问题和实例仿真验证了该算法能有效克服停滞现象和增强全局搜索能力,并且与其他算法相比,该算法能够求得更好的最优解或近似最优解。
英文摘要：
It was difficult to obtain the optimal solution in multiobjective fuzzy flexible Job Shop scheduling by using common genetic algorithms.To solve this problem,based on the consideration of due date obeyed fuzzy time window distribution,a multiobjective fuzzy flexible Job Shop scheduling model was presented.It was aimed at maximize customer satisfaction and minimize completion time.Besides,crossbar collaborative multi-group genetic algorithm was proposed.In this algorithm,multiple initial populations were generated based on process and machine two layers coding mode.And then,migration and sharing of excellent individuals was achieved by competition among various groups.The simulation results of three classical Job Shop scheduling problems and instance demonstrated that the proposed algorithm could effectively overcome the stagnation and improve global search capability.Comparing to other algorithms,the optimal solution or near optimal solution obtained by the proposed algorithm was better.
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同项目期刊论文
Product collaborative design scheme evaluation based on gray statistical evaluation and analytic net
Research on an evaluation method of customer collaborative innovation design scheme based on R-A-WNN
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