Process planning and workshop scheduling integrated optimization adopting new coding mode genetic algorithm

doi:10.16731/j.cnki.1671-3133.2024.09.004

Abstract

Abstract: In order to achieve integrated optimization of process planning and workshop scheduling with the goal of minimizing completion time, a novel coding Genetic Algorithm (GA) based integrated optimization method was proposed. The Integrated Process Planning and Scheduling optimization (IPPS) problem was described and an integrated optimization model with minimizing completion time was established; a chromosome encoding method with maximum flexibility space was designed to ensure the maximum flexibility of integrated optimization problems from an encoding perspective; crossover and mutation method based on specific constraints of IPPS problem was improved, ensuring feasible solutions before and after genetic operation and making algorithm iterations effective; furthermore, a novel encoding genetic algorithm based IPPS problem solving process was developed. According to the verification of Kim example, compared with the existing advanced algorithms such as Two-stage Hybrid Algorithm (THA), Enhanced Ant Colony Algorithm (EACA), Hybrid Genetic Algorithm (HGA), completion time optimized by the novel coding GA algorithm is the smallest (i.e. 343, 344, 372, 320, 427, 432 min respectively) in the case of small-scale and large-scale production. The experimental results verify that the novel coding GA algorithm in solving IPPS problems is feasibility and progressiveness.

Key words: integrated optimization, process planning, workshop scheduling, novel coding, maximum flexible space, genetic algorithm

CLC Number:

TH186
TP18

HUO Junjie, WANG Zhijian. Process planning and workshop scheduling integrated optimization adopting new coding mode genetic algorithm[J]. Modern Manufacturing Engineering, 2024, 528(9): 25-33.

References

[1] 吴迎晨,肖彪,赵正彩,等.柔性作业车间调度多策略果蝇优化算法研究[J].现代制造工程,2023(5):22-30,44.
[2] 刘琼,梅侦.面向低碳的工艺规划与车间调度集成优化[J].机械工程学报,2017,53(11):164-174.
[3] 文笑雨,罗国富,李浩,等.两阶段混合算法求解集成工艺规划与调度问题[J].中国机械工程,2018,29(22):2716-2724,2732.
[4] 吕海利,孙佳祺,吴姝.考虑机器能耗的绿色作业车间调度问题[J].运筹与管理,2021,30(12):220-225.
[5] 张红颖,申荣苗,罗谦.基于混合整数规划的停机位优化调度研究[J].计算机科学,2020,47(8):278-283.
[6] GAN P Y, LEE K S,ZHANG Y F. A branch and bound algorithm based process planning system for plastic injection mould bases[J]. International Journal of Advanced Manufacturing Technology, 2001,18(9):624-632.
[7] JIANG J,HSIAO W C. Mathematical programming for the scheduling problem with alternate process plans in FMS[J]. Computers & Industrial Engineering,1994,27(1/2/3/4):15-18.
[8] LI X,GAO L,PAN Q,et al. An effective hybrid genetic algorithm and variable neighborhood search for integrated process planning and scheduling in a packaging machine workshop[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems,2018,49(10):1933-1945.
[9] 马静,李言.模糊交货期条件下的IPPS问题研究[J].制造业自动化,2019,41(4):24-29.
[10] YUAN M,LI Y,ZHANG L,et al. Research on intelligent workshop resource scheduling method based on improved NSGA-II algorithm[J]. Robotics and Computer-Integrated Manufacturing, 2021,71:102141.
[11] JAIN A,JAIN P,SINGH I. An integrated scheme for process planning and scheduling in FMS[J]. International Journal of Advanced Manufacturing Technology,2006,30(11):1111-1118.
[12] LIU Q H,LI X Y,GAO L. A Novel MILD Model Based on the Topology of a Network Graph for Process Planning in an Intelligent Manufacturing System[J]. Engineering,2021,7(6):226-250.
[13] 慕飞飞,张惠珍.基于遗传算法的单点交叉口信号配时优化[J].上海理工大学学报,2015,37(6):600-604.
[14] KIM Y K,PARK K,KO J. A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling[J]. Computers & Operations Research,2003,30(8):1151-1171.
[15] 赵尔华,邢柏强,栾超,等.某航天型号部段装配工艺研究[J].现代制造技术与装备,2023,59(5):67-69.
[16] ZHANG S ,WONG T N . Integrated process planning and scheduling: an enhanced ant colony optimization heuristic with parameter tuning[J]. Journal of Intelligent Manufacturing,2018,29(3):585-601.