基于郊狼优化算法的柔性作业车间调度问题  

Flexible job-shop scheduling problem based on coyote optimization algorithm

作　　者：张捷 李彬 姜杰 顾海 Zhang Jie;Li Bin;Jiang Jie;Gu Hai(School of Mechanical Engineering,Nantong Institute of Technology,Nantong 226002,Jiangsu,China;Jiangsu Provincial Key Laboratory of 3D Printing Equipment and Application Technology,Nantong 226002,Jiangsu,China)

机构地区：[1]南通理工学院机械工程学院,南通226002 [2]江苏省3D打印装备及应用技术重点建设实验室,南通226002

出　　处：《现代制造工程》2020年第10期39-44,共6页Modern Manufacturing Engineering

基　　金：南通理工学院中青年科研骨干培养工程项目(ZQNGG204);江苏省重点建设学科资助项目(苏教研〔2016〕9号);江苏省“青蓝工程”资助项目(苏教师〔2019〕3号);南通市港闸科技局项目(GZKJ2018ZLK013)。

摘　　要：针对传统元启发式算法求解柔性作业车间调度问题(Flexible Job-shop Scheduling Problem,FJSP)时,存在易陷入局部最优、寻优结果不稳定等缺点,首次将郊狼优化算法(Coyote Optimization Algorithm,COA)应用到柔性作业车间调度问题中,提出一种基于郊狼优化算法的柔性作业车间调度问题优化方法。首先,以最大完工时间最小为目标对FJSP进行描述和建模;然后,提出一种基于工序的实数单链编码方式,同时满足FJSP的表达和基于COA的求解,对COA算法流程进行设计,建立一种求解FJSP的COA流程;最后,根据标准算例进行仿真,证明了基于COA求解FJSP的可行性,通过与遗传算法和粒子群优化算法进行仿真对比,验证了COA求解FJSP的优越性。In order to solve the Flexible Job-shop Scheduling Problem(FJSP)with the traditional meta heuristic algorithm,which is easy to fall into local optimization and the result of optimization is not stable,the Coyote Optimization Algorithm(COA)is applied to the flexible job-shop scheduling problem for the first time,and a flexible job-shop scheduling problem based on coyote optimization algorithm is proposed.Firstly,describes and models the FJSP problem with the goal of the shortest completion time;then,it proposes a real single chain coding method based on the process,which satisfies the expression of FJSP and the solution of COA at the same time,designs each step of COA,and establishes a COA flow for solving FJSP;finally,according to the simulation of standard examples,it proves the feasibility of COA to solve FJSP problem,compared with genetic algorithm and particle swarm optimization algorithm,COA is superior in solving FJSP problem.

关 键 词：元启发式算法 柔性作业车间调度 郊狼优化算法 实数单链编码 

分 类 号：TP278[自动化与计算机技术—检测技术与自动化装置]