Solving the flexible job shop scheduling and lot streaming problem with setup and transport resource constraints

References

• Abdollahzadeh Sangroudi, H., & Ranjbar-Bourani, M. (2021). Solving a flexible job shop lot sizing problem with shared operations using a self-adaptive COA. International Journal of Production Research, 59(2), 483–515. https://doi.org/10.1080/00207543.2019.1696492
   Web of Science ®Google Scholar
• Ahmadizar, F., & Shahmaleki, P. (2014). Group-shop scheduling with sequence-dependent set-up and transportation times. Applied Mathematical Modelling, 38(21–22), 5080–5091. https://doi.org/10.1016/j.apm.2014.03.035
   Web of Science ®Google Scholar
• Al Aqel, G., Li, X., & Gao, L. (2019). A modified iterated greedy algorithm for flexible job shop scheduling problem. Chinese Journal of Mechanical Engineering, 32(1), 1–11. https://doi.org/10.1186/s10033-019-0337-7
   Web of Science ®Google Scholar
• Åstrand, M., Johansson, M., & Zanarini, A. (2020). Underground mine scheduling of mobile machines using constraint programming and large neighborhood search. Computers & Operations Research, 123, 105036. https://doi.org/10.1016/j.cor.2020.105036
   Web of Science ®Google Scholar
• Birgin, E. G., Feofiloff, P., Fernandes, C. G., De Melo, E. L., Oshiro, M. T., & Ronconi, D. P. (2014). A MILP model for an extended version of the flexible job shop problem. Optimization Letters, 8(4), 1417–1431. https://doi.org/10.1007/s11590-013-0669-7
   Web of Science ®Google Scholar
• Blum, C., Puchinger, J., Raidl, G. R., & Roli, A. (2011). Hybrid metaheuristics in combinatorial optimization: A survey. Applied Soft Computing, 11(6), 4135–4151. https://doi.org/10.1016/j.asoc.2011.02.032
   Web of Science ®Google Scholar
• Bożek, A., & Werner, F. (2018). Flexible job shop scheduling with lot streaming and sublot size optimisation. International Journal of Production Research, 56(19), 6391–6411. https://doi.org/10.1080/00207543.2017.1346322
   Web of Science ®Google Scholar
• Bożek, A., & Wysocki, M. (2016). Off-line and dynamic production scheduling-A comparative case study. Management and Production Engineering Review, 7(1), 21–32. https://doi.org/10.1515/mper-2016-0003
   Web of Science ®Google Scholar
• Brandimarte, P. (1993). Routing and scheduling in a flexible job shop by tabu search. Annals of Operations Research, 41(3), 157–183. https://doi.org/10.1007/BF02023073
   Google Scholar
• Brucker, P., & Schlie, R. (1990). Job-shop scheduling with multi-purpose machines. Computing, 45(4), 369–375. https://doi.org/10.1007/BF02238804
   Web of Science ®Google Scholar
• Buscher, U., & Shen, L. (2009). An integrated tabu search algorithm for the lot streaming problem in job shops. European Journal of Operational Research, 199(2), 385–399. https://doi.org/10.1016/j.ejor.2008.11.046
   Web of Science ®Google Scholar
• Carchrae, T., & Beck, J. C. (2009). Principles for the design of large neighborhood search. Journal of Mathematical Modelling and Algorithms, 8(3), 245–270. https://doi.org/10.1007/s10852-008-9100-2
   Google Scholar
• Chan, F. T., Wong, T. C., & Chan, L. Y. (2009a). An evolutionary algorithm for assembly job shop with part sharing. Computers & Industrial Engineering, 57(3), 641–651. https://doi.org/10.1016/j.cie.2008.11.017
   Web of Science ®Google Scholar
• Chan, F. T., Wong, T. C., & Chan, L. Y. (2009b). The application of genetic algorithms to lot streaming in a job-shop scheduling problem. International Journal of Production Research, 47(12), 3387–3412. https://doi.org/10.1080/00207540701577369
   Web of Science ®Google Scholar
• Chan, F. T. S., Wong, T. C., & Chan, L. Y. (2008). Lot streaming for product assembly in job shop environment. Robotics and Computer-Integrated Manufacturing, 24(3), 321–331. https://doi.org/10.1016/j.rcim.2007.01.001
   Web of Science ®Google Scholar
• Chen, R., Yang, B., Li, S., & Wang, S. (2020). A self-learning genetic algorithm based on reinforcement learning for flexible job-shop scheduling problem. Computers & Industrial Engineering, 149, 106778. https://doi.org/10.1016/j.cie.2020.106778
   Web of Science ®Google Scholar
• Cheng, M., Mukherjee, N. J., & Sarin, S. C. (2013). A review of lot streaming. International Journal of Production Research, 51(23–24), 7023–7046. https://doi.org/10.1080/00207543.2013.774506
   Web of Science ®Google Scholar
• Cuiyu, W., Yang, L. I., & Xinyu, L. I. (2021). Solving flexible job shop scheduling problem by a multi-swarm collaborative genetic algorithm. Journal of Systems Engineering and Electronics, 32(2), 261–271. https://doi.org/10.23919/JSEE.2021.000023
   Web of Science ®Google Scholar
• Daneshamooz, F., Fattahi, P., & Hosseini, S. M. H. (2022). Scheduling in a flexible job shop followed by some parallel assembly stations considering lot streaming. Engineering Optimization, 54(4), 614–633. https://doi.org/10.1080/0305215X.2021.1887168
   Web of Science ®Google Scholar
• Dauzere-Peres, S., & Lasserre, J.-B. (1993). An iterative procedure for lot streaming in job-shop scheduling. Computers & Industrial Engineering, 25(1–4), 231–234. https://doi.org/10.1016/0360-8352(93)90263-W
   Web of Science ®Google Scholar
• Dauzere-Peres, S., & Lasserre, J.-B. (1997). Lot streaming in job-shop scheduling. Operations Research, 45(4), 584–595. https://doi.org/10.1287/opre.45.4.584
   Web of Science ®Google Scholar
• Defersha, F. M., & Chen, M. (2012). Jobshop lot streaming with routing flexibility, sequence-dependent setups, machine release dates and lag time. International Journal of Production Research, 50(8), 2331–2352. https://doi.org/10.1080/00207543.2011.574952
   Web of Science ®Google Scholar
• Defersha, F. M., & Movahed, S. B. (2018). Linear programming assisted (not embedded) genetic algorithm for flexible jobshop scheduling with lot streaming. Computers & Industrial Engineering, 117, 319–335. https://doi.org/10.1016/j.cie.2018.02.010
   Web of Science ®Google Scholar
• Demir, Y., & İşleyen, S. K. (2013). Evaluation of mathematical models for flexible job-shop scheduling problems. Applied Mathematical Modelling, 37(3), 977–988. https://doi.org/10.1016/j.apm.2012.03.020
   Web of Science ®Google Scholar
• Ding, H., & Gu, X. (2020). Improved particle swarm optimization algorithm based novel encoding and decoding schemes for flexible job shop scheduling problem. Computers & Operations Research, 121, 104951. https://doi.org/10.1016/j.cor.2020.104951
   Web of Science ®Google Scholar
• Fanjul-Peyro, L. (2020). Models and an exact method for the unrelated parallel machine scheduling problem with setups and resources. Expert Systems with Applications: X, 5, 100022. https://doi.org/10.1016/j.eswax.2020.100022
   Google Scholar
• Fattahi, P., Saidi Mehrabad, M., & Jolai, F. (2007). Mathematical modeling and heuristic approaches to flexible job shop scheduling problems. Journal of Intelligent Manufacturing, 18(3), 331–342. https://doi.org/10.1007/s10845-007-0026-8
   Web of Science ®Google Scholar
• Glass, C. A., Gupta, J. N. D., & Potts, C. N. (1994). Lot streaming in three-stage production processes. European Journal of Operational Research, 75(2), 378–394. https://doi.org/10.1016/0377-2217(94)90082-5
   Web of Science ®Google Scholar
• Güçdemir, H., & Selim, H. (2018). Integrating simulation modelling and multi criteria decision making for customer focused scheduling in job shops. Simulation Modelling Practice and Theory, 88, 17–31. https://doi.org/10.1016/j.simpat.2018.08.001
   Web of Science ®Google Scholar
• Ho, N. B., Tay, J. C., & Lai, E. M.-K. (2007). An effective architecture for learning and evolving flexible job-shop schedules. European Journal of Operational Research, 179(2), 316–333. https://doi.org/10.1016/j.ejor.2006.04.007
   Web of Science ®Google Scholar
• Hojabri, H., Gendreau, M., Potvin, J.-Y., & Rousseau, L.-M. (2018). Large neighborhood search with constraint programming for a vehicle routing problem with synchronization constraints. Computers & Operations Research, 92, 87–97. https://doi.org/10.1016/j.cor.2017.11.011
   Web of Science ®Google Scholar
• IBM. (2019). CP optimizer user’s manual. Retrieved April 30, 2021, from https://www.ibm.com/docs/en/icos/12.10.0?topic=optimizer-cp-users-manual.
   Google Scholar
• IBM. (2021a). IBM ILOG CPLEX optimization studio documentation: CumulFunction. Retrieved June 15, 2021, from https://www.ibm.com/docs/tr/icos/12.10.0?topic=keywords-cumulfunction.
   Google Scholar
• IBM. (2021b). IBM ILOG CPLEX Optimization studio documentation: CP.ImpactOfLastBranch Method. Retrieved June 15, 2021, from https://www.ibm.com/docs/en/icos/12.10.0?topic=cm-impactoflastbranch-method.
   Google Scholar
• Kacprzyk, J., & Pedrycz, W. (2015). Springer handbook of computational intelligence. Springer.
   Google Scholar
• Kesen, S. E., & Güngör, Z. (2012). Job scheduling in virtual manufacturing cells with lot-streaming strategy: A new mathematical model formulation and a genetic algorithm approach. Journal of the Operational Research Society, 63(5), 683–695. https://doi.org/10.1057/jors.2011.86
   Web of Science ®Google Scholar
• Kilby, P., & Urli, T. (2016). Fleet design optimisation from historical data using constraint programming and large neighbourhood search. Constraints, 21(1), 2–21. https://doi.org/10.1007/s10601-015-9203-0
   Web of Science ®Google Scholar
• Kreter, S., Schutt, A., Stuckey, P. J., & Zimmermann, J. (2018). Mixed-integer linear programming and constraint programming formulations for solving resource availability cost problems. European Journal of Operational Research, 266(2), 472–486. https://doi.org/10.1016/j.ejor.2017.10.014
   Web of Science ®Google Scholar
• Lei, D., & Guo, X. (2013). Scheduling job shop with lot streaming and transportation through a modified artificial bee colony. International Journal of Production Research, 51(16), 4930–4941. https://doi.org/10.1080/00207543.2013.784404
   Web of Science ®Google Scholar
• Li, L. (2022). Research on discrete intelligent workshop lot-streaming scheduling with variable sublots under engineer to order. Computers & Industrial Engineering, 165, 107928. https://doi.org/10.1016/j.cie.2021.107928
   Web of Science ®Google Scholar
• Liu, C.-H. (2009). Lot streaming for customer order scheduling problem in job shop environments. International Journal of Computer Integrated Manufacturing, 22(9), 890–907. https://doi.org/10.1080/09511920902866104
   Web of Science ®Google Scholar
• Liu, C.-H., Chen, L.-S., & Lin, P.-S. (2013). Lot streaming multiple jobs with values exponentially deteriorating over time in a job-shop environment. International Journal of Production Research, 51(1), 202–214. https://doi.org/10.1080/00207543.2012.657255
   Web of Science ®Google Scholar
• Meng, T., Pan, Q., & Chen, Q. (2018). An enhanced migrating birds optimization for the flexible job shop scheduling problem with Lot streaming. International Conference on Intelligent Computing, 769–779. https://doi.org/10.1007/978-3-319-95930-6_78
   Google Scholar
• Montgomery, D. C. (2003). Applied Statistics and Probability for Engineers.
   Google Scholar
• Nouri, H. E., Driss, O. B., & Ghédira, K. (2016). Simultaneous scheduling of machines and transport robots in flexible job shop environment using hybrid metaheuristics based on clustered holonic multiagent model. Computers & Industrial Engineering, 102, 488–501. https://doi.org/10.1016/j.cie.2016.02.024
   Web of Science ®Google Scholar
• Novas, J. M. (2019). Production scheduling and lot streaming at flexible job-shops environments using constraint programming. Computers & Industrial Engineering, 136, 252–264. https://doi.org/10.1016/j.cie.2019.07.011
   Web of Science ®Google Scholar
• Palpant, M., Artigues, C., & Michelon, P. (2004). LSSPER: Solving the resource-constrained project scheduling problem with large neighbourhood search. Annals of Operations Research, 131(1), 237–257. https://doi.org/10.1023/B:ANOR.0000039521.26237.62
   Web of Science ®Google Scholar
• Rossi, F., Van Beek, P., & Walsh, T. (2006). Handbook of constraint programming. Elsevier.
   Google Scholar
• Rou, L. Y., & Asmuni, H. (2010). A study of cooperative Co-evolutionary genetic algorithm for solving flexible Job shop scheduling problem. International Journal of Computer and Information Engineering, 4(12), 1849–1854. https://doi.org/10.5281/zenodo.1331427
   Google Scholar
• Ruiz, R., & Maroto, C. (2006). A genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility. European Journal of Operational Research, 169(3), 781–800. https://doi.org/10.1016/j.ejor.2004.06.038
   Web of Science ®Google Scholar
• Ruiz, R., & Stützle, T. (2008). An iterated greedy heuristic for the sequence dependent setup times flowshop problem with makespan and weighted tardiness objectives. European Journal of Operational Research, 187(3), 1143–1159. https://doi.org/10.1016/j.ejor.2006.07.029
   Web of Science ®Google Scholar
• Shi, X., Long, W., Li, Y., & Deng, D. (2020). Multi-population genetic algorithm with ER network for solving flexible job shop scheduling problems. PloS One, 15(5), e0233759. https://doi.org/10.1371/journal.pone.0233759
   PubMed Web of Science ®Google Scholar
• Taguchi, G. (1986). Introduction to quality engineering: Designing quality into products and processes (No. 658.562 T3).
   Google Scholar
• Topaloglu, S., & Ozkarahan, I. (2011). A constraint programming-based solution approach for medical resident scheduling problems. Computers & Operations Research, 38(1), 246–255. https://doi.org/10.1016/j.cor.2010.04.018
   Web of Science ®Google Scholar
• Vital-Soto, A., Azab, A., & Baki, M. F. (2020). Mathematical modeling and a hybridized bacterial foraging optimization algorithm for the flexible job-shop scheduling problem with sequencing flexibility. Journal of Manufacturing Systems, 54, 74–93. https://doi.org/10.1016/j.jmsy.2019.11.010
   Web of Science ®Google Scholar
• Wong, T. C., Chan, F. T., & Chan, L. Y. (2009). A resource-constrained assembly job shop scheduling problem with Lot Streaming technique. Computers & Industrial Engineering, 57(3), 983–995. https://doi.org/10.1016/j.cie.2009.04.002
   Web of Science ®Google Scholar
• Wong, T. C., & Ngan, S.-C. (2013). A comparison of hybrid genetic algorithm and hybrid particle swarm optimization to minimize makespan for assembly job shop. Applied Soft Computing, 13(3), 1391–1399. https://doi.org/10.1016/j.asoc.2012.04.007
   Web of Science ®Google Scholar
• Xing, L.-N., Chen, Y.-W., & Yang, K.-W. (2011). Multi-population interactive coevolutionary algorithm for flexible job shop scheduling problems. Computational Optimization and Applications, 48(1), 139–155. https://doi.org/10.1007/s10589-009-9244-7
   Web of Science ®Google Scholar
• Xiuli, W. U., Junjian, P., Zirun, X. I. E., Ning, Z., & Shaomin, W. U. (2021). An improved multi-objective optimization algorithm for solving flexible job shop scheduling problem with variable batches. Journal of Systems Engineering and Electronics, 32(2), 272–285. https://doi.org/10.23919/JSEE.2021.000024
   Web of Science ®Google Scholar
• Yepes-Borrero, J. C., Perea, F., Ruiz, R., & Villa, F. (2021). Bi-objective parallel machine scheduling with additional resources during setups. European Journal of Operational Research, 292(2), 443–455. https://doi.org/10.1016/j.ejor.2020.10.052
   Web of Science ®Google Scholar
• Yepes-Borrero, J. C., Villa, F., Perea, F., & Caballero-Villalobos, J. P. (2020). GRASP algorithm for the unrelated parallel machine scheduling problem with setup times and additional resources. Expert Systems with Applications, 141, 112959. https://doi.org/10.1016/j.eswa.2019.112959
   Web of Science ®Google Scholar
• Yuan, Y., Xu, H., & Yang, J. (2013). A hybrid harmony search algorithm for the flexible job shop scheduling problem. Applied Soft Computing, 13(7), 3259–3272. https://doi.org/10.1016/j.asoc.2013.02.013
   Web of Science ®Google Scholar
• Yunusoglu, P., & Topaloglu Yildiz, S. (2022). Constraint programming approach for multi-resource-constrained unrelated parallel machine scheduling problem with sequence-dependent setup times. International Journal of Production Research, 60(7), 2212–2229. https://doi.org/10.1080/00207543.2021.1885068
   Web of Science ®Google Scholar
• Zhang, C., Wang, K., Ma, Q., Li, X., & Gao, L. (2021). A Discrete Grey Wolf Optimizer for Solving Flexible Job Shop Scheduling Problem with Lot-streaming. 2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 969–974.
   Google Scholar
• Zhang, G., Zhang, L., Song, X., Wang, Y., & Zhou, C. (2019). A variable neighborhood search based genetic algorithm for flexible job shop scheduling problem. Cluster Computing, 22(5), 11561–11572. https://doi.org/10.1007/s10586-017-1420-4
   Google Scholar
• Zhang, Q., Manier, H., & Manier, M.-A. (2012). A genetic algorithm with tabu search procedure for flexible job shop scheduling with transportation constraints and bounded processing times. Computers & Operations Research, 39(7), 1713–1723. https://doi.org/10.1016/j.cor.2011.10.007
   Web of Science ®Google Scholar