改进蜉蝣算法求解工艺规划与调度集成问题

Improved Mayfly Algorithm for Integrated of Process Planning and Scheduling

针对工艺规划与调度集成问题(IPPS),基于AND/OR析取图和“组合”的概念以最小化最大完工时间为优化目标建立数学模型;设计一种整数编码方案,该方案无需预先为工件生成加工路径,可同时处理工艺规划与调度问题,由于初始解对算法的寻优能力的影响,在种群初始化时考虑机器的负荷以提高初始种群的质量;解码时采用插空的方法生成活跃调度,以缩短工件整体的加工时间;离散蜉蝣算法实现求解IPPS,采用Metropolis准则接收较差的解,引入自适应因子提高算法的收敛速度,设计局部搜索算法提高算法的精度。最后通过大规模基准算例进行实验并与其他算法对比分析,验证该算法有较好寻优性能。

Aiming at the integrated of process planning and scheduling(IPPS),a mathematical model is established based on AND/OR disjunction graph and the concept of“combination”to minimize the makespan optimization target.An integer coding scheme is designed,which does not need to generate a processing path for the workpiece in advance,can deal with process plan⁃ning and scheduling problems at the same time.Due to the effect of the initial solution on the algorithm’s ability to find the opti⁃mal,the load of the machine is considered to improve the quality of the initial population when the population is initialized.The plug-in method is used to generate active scheduling during decoding to shorten the overall processing time.The discrete mayfly algorithm is used to solve IPPS,and the Metropolis criterion is used to receive poor solutions,and the adaptive factors are intro⁃duced to improve the convergence speed of the algorithm,and a local search algorithm is designed to improve the accuracy of the algorithm.Finally,large-scale benchmark studies are carried out and compared with other algorithms to verify that the algorithm has good optimization performance.