Joint scheduling optimisation method for the machining and heat-treatment of hydraulic cylinders based on improved multi-objective migrating birds optimisation

被引:8
作者
Li, Xixing [1 ]
Zhao, Qingqing [1 ]
Tang, Hongtao [2 ]
Yang, Siqin [2 ]
Lei, Deming [3 ]
Wang, Xivincent [4 ]
机构
[1] Hubei Univ Technol, Sch Mech Engn, Hubei Key Lab Modern Mfg & Qual Engn, Wuhan, Peoples R China
[2] Wuhan Univ Technol, Sch Mech Engn, Wuhan, Peoples R China
[3] Wuhan Univ Technol, Sch Automat, Wuhan, Peoples R China
[4] KTH Royal Inst Technol, Dept Prod Engn, Stockholm, Sweden
基金
中国国家自然科学基金;
关键词
Hybrid flow shop; Flexible job shop; Co -evolution mechanism; Hydraulic cylinder; Improved migrating birds optimisation; MAINTENANCE; ALGORITHM;
D O I
10.1016/j.jmsy.2024.01.011
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
For the hydraulic cylinder parts manufacturing shop scheduling problem (HCPMS), which integrates a parallel batch processor hybrid flow shop scheduling problem with the flexible job shop scheduling problem, this paper establishes a multi -objective scheduling model with makespan, total energy consumption, and total machine workload as the optimisation objectives, and proposes an improved multi -objective migrating birds optimisation (IMOMBO) algorithm to solve the problem. First, considering the characteristics of the combination of singlepiece and batch processing in the workshop, a double -layer coding rule based on the operation and processing equipment is proposed, and the corresponding decoding rule is designed according to whether the workpiece requires quenching and tempering. Second, a multi -population co -evolution mechanism is developed to enhance the diversity of solutions by conducting different evolutionary strategies. Additionally, six neighborhood structures are introduced to perform local searches for the leader and follower birds, thereby improving the quality of the solutions. Finally, the effectiveness of the IMOMBO algorithm is demonstrated by comparing its results with those of four other algorithms through comparative experiments and a practical case.
引用
收藏
页码:170 / 191
页数:22
相关论文
共 59 条
[1]   Energy-efficient multi-objective flexible manufacturing scheduling [J].
Barak, Sasan ;
Moghdani, Reza ;
Maghsoudlou, Hamidreza .
JOURNAL OF CLEANER PRODUCTION, 2021, 283
[2]   Greedy randomized adaptive search procedure for simultaneous scheduling of production and preventive maintenance activities in dynamic flexible job shops [J].
Baykasoglu, Adil ;
Madenoglu, Fatma S. .
SOFT COMPUTING, 2021, 25 (23) :14893-14932
[3]   On the robustness of joint production and maintenance scheduling in presence of uncertainties [J].
Boudjelida, Abdelhamid .
JOURNAL OF INTELLIGENT MANUFACTURING, 2019, 30 (04) :1515-1530
[4]   Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints [J].
Chamnanlor, Chettha ;
Sethanan, Kanchana ;
Gen, Mitsuo ;
Chien, Chen-Fu .
JOURNAL OF INTELLIGENT MANUFACTURING, 2017, 28 (08) :1915-1931
[5]   A two-level method or production planning ana scheduling tor Bi-objective reentrant hybrid flow shops [J].
Cho, Hang-Min ;
Jeong, In-Jae .
COMPUTERS & INDUSTRIAL ENGINEERING, 2017, 106 :174-181
[6]   Modeling and solution methods for hybrid flow shop scheduling problem with job rejection [J].
Dabiri, Mohamadreza ;
Yazdani, Mehdi ;
Naderi, Bahman ;
Haleh, Hassan .
OPERATIONAL RESEARCH, 2022, 22 (03) :2721-2765
[7]   Multi-objective multitasking optimization based on positive knowledge transfer mechanism [J].
Dang, Qianlong ;
Gao, Weifeng ;
Gong, Maoguo ;
Yang, Shuai .
INFORMATION SCIENCES, 2022, 612 :322-343
[8]   Migrating Birds Optimization: A new metaheuristic approach and its performance on quadratic assignment problem [J].
Duman, Ekrem ;
Uysal, Mitat ;
Alkaya, Ali Fuat .
INFORMATION SCIENCES, 2012, 217 :65-77
[9]   A Hybrid Evolutionary Algorithm Using Two Solution Representations for Hybrid Flow-Shop Scheduling Problem [J].
Fan, Jiaxin ;
Li, Yingli ;
Xie, Jin ;
Zhang, Chunjiang ;
Shen, Weiming ;
Gao, Liang .
IEEE TRANSACTIONS ON CYBERNETICS, 2023, 53 (03) :1752-1764
[10]   Bi-Objective Modeling and Optimization for Stochastic Two-Stage Open Shop Scheduling Problems in the Sharing Economy [J].
Fu, Yaping ;
Li, Haobin ;
Huang, Min ;
Xiao, Hui .
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2023, 70 (10) :3395-3409