王少航1,2, 蒋毅1,2*, 赵晓梦1,2.基于改进遗传算法的附加约束重调度策略[J].轻工机械,2023,41(3):100-104 |
基于改进遗传算法的附加约束重调度策略 |
基于改进遗传算法的附加约束重调度策略 |
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DOI:10.3969/j.issn.1005 2895.2023.03.015 |
中文关键词: 柔性生产线 遗传算法 附加约束 重调度 |
英文关键词:flexible production line genetic algorithm additional constraints rescheduling |
基金项目:国家自然科学基金资助项目(51675233)。 |
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中文摘要: |
针对某柔性生产线上遇到机器故障、加工延时、插单、撤单等不能提前预知的意外情况而对生产线的初始调度方案产生干扰的问题,课题组研究了该柔性生产线的重调度问题,设计了一种改进的遗传算法,提高了算法的收敛速度。课题组采用矩阵编码方式使算法便于添加约束条件;设计了一种附加约束重调度方案,采用统一的决策方式,有效应对处理多种意外干扰;最后在MATLAB软件中进行了仿真模拟运算。实验和仿真结果表明:改进遗传算法收敛时间相比经典遗传算法减少了38%,且避免了输出局部极值。课题组提出的重调度方案可有效处理生产线的各种意外情况。 |
英文摘要: |
Aiming at the problem that unexpected situations such as machine failures, processing delays, order insertion and cancellation that cannot be predicted in advance on a flexible production line may interfere with the initial scheduling plan of the production line, an improved genetic algorithm was designed to improve the convergence speed of the algorithm. The matrix coding method was used to make the algorithm easy to add constraints; An additional constraint rescheduling scheme was designed, which adopted a unified decision making mode to effectively deal with multiple unexpected disturbances; Finally, the simulation was carried out in MATLAB software. The experimental and simulation results show that the convergence time of the improved genetic algorithm is reduced by 38% compared with the classical genetic algorithm, and the output of local extremum is avoided; Rescheduling scheme can effectively deal with various unexpected situations of the production line. |
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