基于多规则资源分配的柔性作业车间调度问题多目标集成优化方法

摘要/Abstract

摘要：

摘要：针对柔性作业车间调度问题中多种资源分配的复杂特性，建立了以最小完工时间、最优人工分配方案、设备最大负荷以及最小生产成本为目标的集成优化模型，并设计了一种具有多重资源约束的多目标集成优化方法；针对组合模型的爆炸性特征，为降低模型的复杂度，采用多规则资源分配的集成调度思想，通过调整规则概率使概率大的规则被优先选中，使用多规则导向机制“推动”搜索过程向指定目标方向移动, 并结合动态规划法求解最优人员分配方案；采用改进的非支配排序遗传算法——NSGAⅡ可以获得不同规则概率值的Pareto解集;最后，通过仿真对比与应用验证了所提方法的有效性.

关键词: , 柔性作业车间调度, 多目标集成优化, 多规则, 多重资源, 改进的非支配排序遗传算法

Abstract:

Abstract： In order to reduce the complexity of multi-objective optimization in flexible jobshop scheduling and improve optimization efficiency, a multiobjective integrated optimization method with multiple resource constraints was proposed in this paper. Firstly, an integrated optimization model was established according to the objectives of minimum completion time, optimal human resource allocation plan, maximum equipment load and lowest production costs. Besides, in view of the explosive characteristics of combination model, an integrated scheduling rule for multiple resources allocation was presented to reduce the model complexity. As for the selection strategies of the scheduling rules, the rules with a high probability were preferentially selected through adjusting the probability of rules. In addition, the multiplerule guiding mechanism was adopted to push the search process toward the target direction. Furthermore, the improved nondominated sorting genetic algorithm (NSGAⅡ) was adopted to obtain the Pareto solution sets of different probability values of the rules. Finally, the effectiveness of the proposed method was verified by simulation comparison.

Key words: , flexible job-shop scheduling； multi-objective integrated optimization； multirule； multiple resources； non-dominated sorting genetic algorithm

中图分类号:

TP 39

高丽1a,2,周炳海2,杨学良1b,王吉霞1a. 基于多规则资源分配的柔性作业车间调度问题多目标集成优化方法[J]. 上海交通大学学报（自然版）, 2015, 49(08): 1191-1198.

GAO Li1a,2,ZHOU Binghai2,YANG Xueliang1b,Wang Jixia1a. A MultiObjective Integrated Optimization Method for FJSP Based on Multi-Rule Resource Allocation[J]. Journal of Shanghai Jiaotong University, 2015, 49(08): 1191-1198.

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