Lot Streaming Flexible Job-shop Scheduling with Pre-maintenance

doi:10.3901/JME.260551

Abstract

Abstract: Considering the batch nature of production orders, the frequent need for mold changes during processing, the transportation requirements of workpieces, and the impact of cumulative processing hours on machine energy consumption, a green scheduling model for lot streaming flexible job-shop is developed. This model incorporates multiple temporal constraints and pre-maintenance mechanisms into batch scheduling with the dual objectives of minimizing makespan and energy consumption. By conducting necessary pre-maintenance on the continuous processing machines, the dynamic impact of cumulative working hours on the energy consumption of the machines can be effectively reduced. Based on the characteristics of batch scheduling and pre-maintenance, a Jaya algorithm based on sub-batch division is proposed, and multiple optimization mechanisms are designed. Firstly, various Jaya optimization guidance mechanisms based on sub-batch division are introduced to accelerate the convergence rate, increase population diversity, and enhance the global search capability of the algorithm. Secondly, a greedy search strategy based on sub-batch division is devised to improve the algorithm’s optimization ability and assist in escaping local optima. Finally, a tabu search strategy based on the number of sub-batches is proposed to improve the evolutionary efficiency of the algorithm, reduce redundant calculations, and enable multiple searches of complex individuals, thereby broadening the search space. The effectiveness of the proposed algorithm is confirmed through ablation experiments. Comparative studies with four other algorithms across 13 extended case examples demonstrate the superiority of the proposed approach.

Key words: flexible job-shop scheduling, multiple temporal constraints, batch scheduling, pre-maintenance, sub-batch partition

CLC Number:

TH165
TP18

WANG Yufang, HUA Xiaolin, ZHANG Dianqing, LIU Pingying. Lot Streaming Flexible Job-shop Scheduling with Pre-maintenance[J]. Journal of Mechanical Engineering, 2026, 62(15): 244-261.

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URL: http://www.cjmenet.com.cn/EN/10.3901/JME.260551

http://www.cjmenet.com.cn/EN/Y2026/V62/I15/244

References

[1] 梁志珍，王晓佳. 双资源约束的柔性作业车间鲁棒调度方法[J]. 机械工程学报，2024，60(6)：114-126. LIANG Zhizhen，WANG Xiaojia. Dual resource constraints flexible job shop robust scheduling method[J]. Journal of Mechanical Engineering，2024，60(6)：114-126.
[2] BRUCKER P, SCHLIE R. Job-shop scheduling with multi-purpose machines[J]. Computing，1990，45(4)：369-375.
[3] 闫富乾，陈浩杰，丁国富，等. 求解柔性分批调度问题的双层搜索框架入侵杂草算法[J]. 计算机集成制造系统，2023，29(2)：556-567. YAN Fuqing，CHEN Haojie，DING Guofu. Improved invasive weed algorithm based on double layer search framework for flexible batch scheduling problem[J]. Computer Integrated Manufacturing Systems，2023，29(2)：556-567.
[4] ABDOLLAHZADEH SANGROUDI H，RANJBAR- BOURANI M. Solving a flexible job shop lot sizing problem with shared operations using a self-adaptive COA[J]. International Journal of Production Research，2021，59(2)：483-515.
[5] JI B，ZHANG S J，YU S S，et al. Novel model and solution method for flexible job shop scheduling problem with batch processing machines[J]. Computers & Operations，2024，161：106442.
[6] YUNUSOGLU P，TOPALOGLUYILDIZ S. Solving the flexible job shop scheduling and lot streaming problem with setup and transport resource constraints[J]. International Journal of Systems Science，2023，54(11)： 2443.
[7] LI X，LU J，YANG C，et al. Research of flexible assembly job-shop batch-scheduling problem based on improved artificial bee colony[J]. Frontiers in Bioengineering and Biotechnology，2022，10：909548.
[8] XIE F，LI L，LI L，et al. A decomposition-based multi-objective Jaya algorithm for lot-streaming job shop scheduling with variable sublots and intermingling setting[J]. Expert Systems with Applications，2023，228： 120402.
[9] 王建华，潘宇杰，孙瑞. 考虑机床折旧的柔性作业车间绿色调度算法[J]. 计算机应用，2020，40(1)：43-49. WANG Jianhua，PAN Yujie，SUN Rui. Flexible job-shop green scheduling algorithm considering machine tool depreciation[J]. Journal of Computer Applications，2020，40(1)：43-49.
[10] YANG B，LIAW P K，MORRISON M，et al. Temperature evolution during fatigue damage[J]. Intermetallics，2005，13(3)：419-428.
[11] YAN J，HUA D. Energy consumption modeling for machine tools after preventive maintenance[C]. 2010 IEEE International Conference on Industrial Engineering and Engineering Management，Macao，China. 2010： 2201-2205.
[12] RAO R. Jaya：A simple and new optimization algorithm for solving constrained and unconstrained optimization problems[J]. Engineering Computations，2016，7(1)：19-34.
[13] PAN Y，GAO K，LI Z，et al. Solving biobjective distributed flow-shop scheduling problems with lot-streaming using an improved jaya algorithm[J]. IEEE Transactions on Cybernetics，2023，53(6)：3818-3828.
[14] CALDEIRA R H，GNANAVELBABU A. A Pareto based discrete Jaya algorithm for multi-objective flexible job shop scheduling problem[J]. Expert Systems with Applications，2021，170：114567.
[15] BEREN G Y，OMER F Y. Lot streaming in hybrid flowshop scheduling problem by considering equal and consistent sublots under machine capability and limited waiting time constraint[J]. Computers & Industrial Engineering，2022，173：108745.
[16] HUANG R H，YU T H. An effective ant colony optimization algorithm for multi-objective job-shop scheduling with equal-size lot-splitting[J]. Applied Soft Computing，2017，57：642-656.
[17] 王玉芳，华晓麟，章殿清，等. 基于混合Jaya算法的多时间约束柔性作业车间节能调度[J]. 控制工程，2025，32(6)：1074-1085. WANG Yufang，HUA Xiaolin，ZHANG Dianqing，et al. Energy-efficient scheduling of flexible job-shop with multiple temporal constraints based on hybrid jaya algorithm[J]. Control Engineering of China，2025，32(6)： 1074-1085.
[18] ZHANG H L，XU G J，PAN R L，et al. A novel heuristic method for the energy-efficient flexible job-shop scheduling problem with sequence-dependent set-up and transportation time[J]. Engineering Optimization，2021，54(10)：1646-1667.
[19] SUN J H，ZHANG G H，LU J，et al. A hybrid many -objective problem with transportation and setup times[J]. Computers & Operations Research，2021，132： 105263.
[20] TIAN Y，CHENG R，ZHANG X Y，et al. PlatEMO：a MATLAB platform for evolutionary multi-objective optimization[J]. IEEE Computational Intelligence Magazine，2017，12(4)：73-87.
[21] ANSARI T，CHANDRA G，GUPTA P K，et al. Synthesis of pine needle cyanoethyl cellulose using Taguchi L25 orthogonal array[J]. Industrial Crops & Products，2023，191：115973.
[22] 田志强，姜兴宇，杨国哲，等.一种面向航天复杂构件的柔性作业车间能耗优化调度问题研究[J]. 机械工程学报，2023，59(8)：273-287. TIAN Zhiqiang，JIANG Xingyu，YANG Guozhe，et al. Energy efficient scheduling of flexible job shop with aerospace complex components[J]. Journal of Mechanical Engineering，2023，59(8)：273-287.
[23] LI Y，YANG Z，WANG L，et al. A hybrid imperialist competitive algorithm for energy-efficient flexible job shop scheduling problem with variable-size sublots[J]. Computers & Industrial Engineering，2022，172： 108641.
[24] ZHENG X L，WANG L. A collaborative multiobjective fruit fly optimization algorithm for the resource constrained unrelated parallel machine green scheduling problem[J]. IEEE Transactions on Systems，Man，and Cybernetics：Systems，2016，48(5)：790-800.