Abstract
Distributed Job shop Scheduling Problem is one of the well-known hardest combinatorial optimization problems. In the last two decades, the problem has captured the interest of a number of researchers and therefore various methods have been employed to study this problem. The scope of this paper is to give an overview of pioneer studies conducted on solving Distributed Job shop Scheduling Problem using different techniques and aiming to reach a specified objective function. Resolution approaches used to solve the problem are reviewed and a classification of the employed techniques is given.
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Naderi, B., Azab, A.: Modeling and heuristics for scheduling of distributed job shops. Expert Syst. Appl. 41(17), 7754–7763 (2014)
Jia, H.Z., Fuh, J.Y.H., Nee, A.Y.C., Zhang, Y.F.: Integration of genetic algorithm and gantt chart for job shop scheduling in distributed manufacturing systems. Comput. Ind. Eng. 53(2), 313–320 (2007)
Naderi, B., Ruiz, R.: The distributed permutation flowshop scheduling problem. Comput. Oper. Res. 37(4), 754–768 (2010)
Naderi, B., Ruiz, R.: A scatter search algorithm for the distributed permutation flowshop scheduling problem. Eur. J. Oper. Res. 239(2), 323–334 (2014)
Rifai, A.P., Nguyen, H.-T., Dawal, S.Z.M.: Multi-objective adaptive large neighborhood search for distributed reentrant permutation flow shop scheduling. Appl. Soft Comput. 40, 42–57 (2016)
Bargaoui, H., Driss, O.B., Ghédira, K.: Minimizing makespan in multi-factory flow shop problem using a chemical reaction metaheuristic. In: IEEE Congress on Evolutionary Computation, Vancouver, Canada, pp. 2919–2929 (2016)
Behnamian, J., Ghomi, S.M.T.F.: The heterogeneous multi-factory production network scheduling with adaptive communication policy and parallel machine. Inf. Sci. 219, 181–196 (2013)
Hatami, S., Ruiz, R., Andrés-Romano, C.: Heuristics and metaheuristics for the distributed assembly permutation flowshop scheduling problem with sequence dependent setup times. Int. J. Prod. Econ. 169, 76–88 (2015)
Adams, J., Balas, E., Zawack, D.: The shifting bottleneck procedure for job shop scheduling. Manage. Sci. 34(3), 391–401 (1988)
Fisher, H., Thompson, G.L.: Probabilistic learning combinations of local job-shop scheduling rules. Ind. Sched. 3, 225–251 (1963)
Storer, R.H., Wu, S.D., Park, I.: Genetic algorithms in problem space for sequencing problems. In: Fandel, G., Gulledge, T., Jones, A. (eds.) Operations Research in Production Planning and Control, pp. 584–597. Springer, Heidelberg (1993)
Taillard, E.: Benchmarks for basic scheduling problems. Eur. J. Oper. Res. 64(2), 278–285 (1993)
Lawrence, S.: Resource constrained project scheduling: an experimental investigation of heuristic scheduling techniques (supplement). Graduate School of Industrial Administration (1984)
Chung, S.H., Chan, F.T.S., Chan, H.K.: A modified genetic algorithm approach for scheduling of perfect maintenance in distributed production scheduling. Eng. Appl. Artif. Intell. 22(7), 1005–1014 (2009)
Garey, M.R., Johnson, D.S., Sethi, R.: The complexity of flowshop and jobshop scheduling. Math. Oper. Res. 1(2), 117–129 (1976)
Colorni, A., Dorigo, M., Maniezzo, V., Trubian, M.: Ant system for job-shop scheduling. Belg. J. Oper. Res. Stat. Comput. Sci. 34(1), 39–53 (1994)
Dell’Amico, M., Trubian, M.: Applying tabu search to the job-shop scheduling problem. Ann. Oper. Res. 41(3), 231–252 (1993)
Davis, L.: Job shop scheduling with genetic algorithms. In: Proceedings of an International Conference on Genetic Algorithms and their Applications, vol. 140. Carnegie-Mellon University, Pittsburgh, PA (1985)
Holland, J.H.: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. MIT Press, Cambridge (1992)
Jia, H.Z., Fuh, J.Y.H., Nee, A.Y.C., Zhang, Y.F.: Web-based multi-functional scheduling system for a distributed manufacturing environment. Concurrent Eng. 10(1), 27–39 (2002)
Jia, H.Z., Nee, A.Y.C., Fuh, J.Y.H., Zhang, Y.F.: A modified genetic algorithm for distributed scheduling problems. J. Intell. Manuf. 14(3–4), 351–362 (2003)
Muth, J.F., Thompson, G.L.: Industrial Scheduling. Prentice-Hall, Upper Saddle River (1963)
Naderi, B., Azab, A.: An improved model and novel simulated annealing for distributed job shop problems. Int. J. Adv. Manuf. Technol. 81, 693–703 (2015)
Allahverdi, A., Ng, C.T., Cheng, T.C.E., Kovalyov, M.Y.: A survey of scheduling problems with setup times or costs. Eur. J. Oper. Res. 187(3), 985–1032 (2008)
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Chaouch, I., Driss, O.B., Ghedira, K. (2017). A Survey of Optimization Techniques for Distributed Job Shop Scheduling Problems in Multi-factories. In: Silhavy, R., Senkerik, R., Kominkova Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Cybernetics and Mathematics Applications in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 574. Springer, Cham. https://doi.org/10.1007/978-3-319-57264-2_38
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DOI: https://doi.org/10.1007/978-3-319-57264-2_38
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