Benders decomposition for the mixed no-idle permutation flowshop scheduling problem

Abstract

[EN] The mixed no-idle flowshop scheduling problem arises in modern industries including integrated circuits, ceramic frit and steel production, among others, and where some machines are not allowed to remain idle between jobs. This paper describes an exact algorithm that uses Benders decomposition with a simple yet effective enhancement mechanism that entails the generation of additional cuts by using a referenced local search to help speed up convergence. Using only a single additional optimality cut at each iteration, and combined with combinatorial cuts, the algorithm can optimally solve instances with up to 500 jobs and 15 machines that are otherwise not within the reach of off-the-shelf optimization software, and can easily surpass ad-hoc existing metaheuristics. To the best of the authors' knowledge, the algorithm described here is the only exact method for solving the mixed no-idle permutation flowshop scheduling problem.This research project was partially supported by the Scientific and Technological Research Council of Turkey (TuBITAK) under Grant 1059B191600107. While writing this paper, Dr Hamzaday was a visiting researcher at the Southampton Business School at the University of Southampton. Ruben Ruiz is supported by the Spanish Ministry of Science, Innovation and Universities, under the Project 'OPTEP-Port Terminal Operations Optimization' (No. RTI2018-094940-B-I00) financed with FEDER funds. Thanks are due to two anonymous reviewers for their careful reading of the paper and helpful suggestions.Bektas, T.; Hamzadayi, A.; Ruiz García, R. (2020). Benders decomposition for the mixed no-idle permutation flowshop scheduling problem. Journal of Scheduling. 23(4):513-523. https://doi.org/10.1007/s10951-020-00637-8S513523234Adiri, I., & Pohoryles, D. (1982). Flowshop no-idle or no-wait scheduling to minimize the sum of completion times. Naval Research Logistics, 29(3), 495–504.Baker, K. R. (1974). Introduction to sequencing and scheduling. New York: Wiley.Baptiste, P., & Hguny, L. K. (1997). A branch and bound algorithm for the FF/no-idle/CmaxC_{max}. In Proceedings of the international conference on industrial engineering and production management, IEPM’97, Lyon, France (Vol. 1, pp. 429–438).Benders, J. F. (1962). Partitioning procedures for solving mixed-variables programming problems. Numerische Mathematik, 4(1), 238–252.Cordeau, J. F., Pasin, F., & Solomon, M. (2006). An integrated model for logistics network design. Annals of Operations Research, 144(1), 59–82.Costa, A. M., Cordeau, J. F., Gendron, B., & Laporte, G. (2012). Accelerating benders decomposition with heuristic master problem solutions. Pesquisa Operacional, 32(1), 3–20.Deng, G., & Gu, X. (2012). A hybrid discrete differential evolution algorithm for the no-idle permutation flow shop scheduling problem with makespan criterion. Computers & Operations Research, 39(9), 2152–2160.Goncharov, Y., & Sevastyanov, S. (2009). The flow shop problem with no-idle constraints: A review and approximation. European Journal of Operational Research, 196(2), 450–456.Kalczynski, P. J., & Kamburowski, J. (2005). A heuristic for minimizing the makespan in no-idle permutation flow shops. Computers & Industrial Engineering, 49(1), 146–154.Magnanti, T. L., & Wong, R. T. (1981). Accelerating benders decomposition: Algorithmic enhancement and model selection criteria. Operations Research, 29(3), 464–484.Pan, Q. K., & Ruiz, R. (2014). An effective iterated greedy algorithm for the mixed no-idle flowshop scheduling problem. Omega, 44(1), 41–50.Pan, Q. K., Tasgetiren, M. F., & Liang, Y. C. (2008). A discrete differential evolution algorithm for the permutation flowshop scheduling problem. Computers & Industrial Engineering, 55(4), 795–816.Pan, Q. K., & Wang, L. (2008a). No-idle permutation flow shop scheduling based on a hybrid discrete particle swarm optimization algorithm. International Journal of Advanced Manufacturing Technology, 39(7–8), 796–807.Pan, Q. K., & Wang, L. (2008b). A novel differential evolution algorithm for no-idle permutation flow-shop scheduling problems. European Journal of Industrial Engineering, 2(3), 279–297.Papadakos, N. (2008). Practical enhancements to the Magnanti–Wong method. Operations Research Letters, 36(4), 444–449.Röck, H. (1984). The three-machine no-wait flow shop is NP-complete. Journal of the Association for Computing Machinery, 31(2), 336–345.Ruiz, R., & Maroto, C. (2005). A comprehensive review and evaluation of permutation flowshop heuristics. European Journal of Operational Research, 165(2), 479–494.Ruiz, R., Vallada, E., & Fernández-Martínez, C. (2009). Scheduling in flowshops with no-idle machines. In U. Chakraborty (Ed.), Computational intelligence in flow shop and job shop scheduling, chap 2 (pp. 21–51). New York: Springer.Saadani, N. E. H., Guinet, A., & Moalla, M. (2003). Three stage no-idle flow-shops. Computers & Industrial Engineering, 44(3), 425–434.Saharidis, G., & Ierapetritou, M. (2013). Speed-up Benders decomposition using maximum density cut (MDC) generation. Annals of Operations Research, 210, 101–123.Shao, W., Pi, D., & Shao, Z. (2017). Memetic algorithm with node and edge histogram for no-idle flow shop scheduling problem to minimize the makespan criterion. Applied Soft Computing, 54, 164–182.Tasgetiren, M. F., Buyukdagli, O., Pan, Q. K., & Suganthan, P. N. (2013). A general variable neighborhood search algorithm for the no-idle permutation flowshop scheduling problem. In B. K. Panigrahi, P. N. Suganthan, S. Das, & S. S. Dash (Eds.), Swarm, evolutionary, and memetic computing (pp. 24–34). Cham: Springer.Vachajitpan, P. (1982). Job sequencing with continuous machine operation. Computers & Industrial Engineering, 6(3), 255–259

    Similar works