MILP Modeling and Optimization of Three-Stage Flexible Job Shop Scheduling Problem with Assembly and AGV Transportation

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Pubblicato in:Chinese Journal of Mechanical Engineering = Ji xie gong cheng xue bao vol. 38, no. 1 (Dec 2025), p. 115
Autore principale: Yang, Shiming
Altri autori: Meng, Leilei, Ullah, Saif, Zhang, Chaoyong, Sang, Hongyan, Zhang, Biao
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Springer Nature B.V.
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024 7 |a 10.1186/s10033-025-01281-z  |2 doi 
035 |a 3228587666 
045 2 |b d20251201  |b d20251231 
100 1 |a Yang, Shiming  |u Liaocheng University, School of Computer Science, Liaocheng, China (GRID:grid.411351.3) (ISNI:0000 0001 1119 5892) 
245 1 |a MILP Modeling and Optimization of Three-Stage Flexible Job Shop Scheduling Problem with Assembly and AGV Transportation 
260 |b Springer Nature B.V.  |c Dec 2025 
513 |a Journal Article 
520 3 |a The flexible job shop scheduling problem (FJSP) is commonly encountered in practical manufacturing environments. A product is typically built by assembling multiple jobs during actual manufacturing. AGVs are normally used to transport the jobs from the processing shop to the assembly shop, where they are assembled. Therefore, studying the integrated scheduling problem with its processing, transportation, and assembly stages is extremely beneficial and significant. This research studies the three-stage flexible job shop scheduling problem with assembly and AGV transportation (FJSP-T-A), which includes processing jobs, transporting them via AGVs, and assembling them. A mixed integer linear programming (MILP) model is established to obtain optimal solutions. As the MILP model is challenging for solving large-scale problems, a novel co-evolutionary algorithm (NCEA) with two different decoding methods is proposed. In NCEA, a restart operation is developed to improve the diversity of the population, and a multiple crossover strategy is designed to improve the quality of individuals. The validity of the MILP model is proven by analyzing its complexity. The effectiveness of the restart operator, multiple crossovers, and the proposed algorithm is demonstrated by calculating and analyzing the RPI values of each algorithm's results within the time limit and performing a paired t-test on the average values of each algorithm at the 95% confidence level. This paper studies FJSP-T-A by minimizing the makespan for the first time, and presents a MILP model and an NCEA with two different decoding methods. 
653 |a Scheduling 
653 |a Linear programming 
653 |a Collaboration 
653 |a Integer programming 
653 |a Decoding 
653 |a Confidence intervals 
653 |a Optimization techniques 
653 |a Genetic algorithms 
653 |a Optimization 
653 |a Assembling 
653 |a Job shops 
653 |a Methods 
653 |a Literature reviews 
653 |a Mixed integer 
653 |a Manufacturing 
653 |a Workloads 
653 |a Energy consumption 
653 |a Evolutionary algorithms 
653 |a Job shop scheduling 
700 1 |a Meng, Leilei  |u Liaocheng University, School of Computer Science, Liaocheng, China (GRID:grid.411351.3) (ISNI:0000 0001 1119 5892) 
700 1 |a Ullah, Saif  |u University of Engineering and Technology, Department of Industrial Engineering, Taxila, Pakistan (GRID:grid.411351.3) 
700 1 |a Zhang, Chaoyong  |u Huazhong University of Science and Technology, State Key Lab of Digital Manufacturing Equipment and Technology, Wuhan, China (GRID:grid.33199.31) (ISNI:0000 0004 0368 7223) 
700 1 |a Sang, Hongyan  |u Liaocheng University, School of Computer Science, Liaocheng, China (GRID:grid.411351.3) (ISNI:0000 0001 1119 5892) 
700 1 |a Zhang, Biao  |u Liaocheng University, School of Computer Science, Liaocheng, China (GRID:grid.411351.3) (ISNI:0000 0001 1119 5892) 
773 0 |t Chinese Journal of Mechanical Engineering = Ji xie gong cheng xue bao  |g vol. 38, no. 1 (Dec 2025), p. 115 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3228587666/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3228587666/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3228587666/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch