改进的混合蛙跳算法求解柔性作业车间调度
发布时间：2019-03-22 08:21
【摘要】：针对柔性作业车间调度问题,构建了以最大完工时间和总加工能耗最小为优化目标的多目标调度模型。发展了改进的混合蛙跳算法,通过设计基于MPX(Maximum Preserved Crossover)操作和单亲遗传算法基因移位操作的局部更新策略,避免了算法的非法解产生和修整,加快了算法寻优速率。并通过简化邻域寻优策略对组内最优解进行优化,防止算法陷入局部最优。通过求解某企业生产车间实例,得出了不同权重下的调度方案,并对比标准混合蛙跳算法下的最大完工时间和加工能耗,证明了算法的有效性。
[Abstract]:In order to solve the flexible job shop scheduling problem, a multi-objective scheduling model with the maximum completion time and minimum total machining energy consumption as the optimization objective is proposed. An improved hybrid frog jump algorithm is developed. By designing a local update strategy based on MPX (Maximum Preserved Crossover) operation and gene shift operation of partheno-genetic algorithm, the illegal solution generation and trimming of the algorithm are avoided, and the optimization rate of the algorithm is speeded up. By simplifying the neighborhood optimization strategy, the intra-group optimal solution is optimized to prevent the algorithm from falling into the local optimal solution. The scheduling scheme with different weights is obtained by solving an example of a production workshop in an enterprise. The maximum completion time and processing energy consumption under the standard hybrid frog jump algorithm are compared, and the effectiveness of the algorithm is proved.
【作者单位】： 江南大学物联网技术应用教育部工程研究中心;
【基金】：国家自然科学基金(61572238) 江苏省杰出青年基金(BK20160001) 江苏省产学研联合创新资金-前瞻性联合研究项目(BY2016022-24)
【分类号】：TB497;TP18
本文编号：2445430
[Abstract]:In order to solve the flexible job shop scheduling problem, a multi-objective scheduling model with the maximum completion time and minimum total machining energy consumption as the optimization objective is proposed. An improved hybrid frog jump algorithm is developed. By designing a local update strategy based on MPX (Maximum Preserved Crossover) operation and gene shift operation of partheno-genetic algorithm, the illegal solution generation and trimming of the algorithm are avoided, and the optimization rate of the algorithm is speeded up. By simplifying the neighborhood optimization strategy, the intra-group optimal solution is optimized to prevent the algorithm from falling into the local optimal solution. The scheduling scheme with different weights is obtained by solving an example of a production workshop in an enterprise. The maximum completion time and processing energy consumption under the standard hybrid frog jump algorithm are compared, and the effectiveness of the algorithm is proved.
【作者单位】： 江南大学物联网技术应用教育部工程研究中心;
【基金】：国家自然科学基金(61572238) 江苏省杰出青年基金(BK20160001) 江苏省产学研联合创新资金-前瞻性联合研究项目(BY2016022-24)
【分类号】：TB497;TP18
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