Abstract
Flow shop scheduling problem is an important one in the real world production process. As tight constraint condition exits in just-in-time production systems, the no-wait flow shop scheduling problem (NWFSSP) is a typical research topic. In this paper, a hybrid discrete estimation of distribution algorithm (HDEDA) for NWFSSP is proposed to minimize the makespan. The proposed HDEDA utilizes the EDA and bat algorithm (BA). The probability matrix can be a view in the space distribution of the solution well by relying on the knowledge obtained from NWFSSP. The individual generated by sampling has the probability to spread throughout the entire solution space. Then, the designed step-based insertion in the BA stage attains the solution with the best makespan. All of the experiments are performed on the new hard benchmark for flow shop scheduling problems proposed by Ruiz in 2015. Through experimental comparisons, HDEDA shows better effectiveness than other algorithms.
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References
Vasile, M.A., Pop, F., Tutueanu, R.I., et al.: Resource-aware hybrid scheduling algorithm in heterogeneous distributed computing. Future Gener. Comput. Syst. 51, 61–71 (2015)
Yammani, C., Maheswarapu, S., Matam, S.K.: A multi-objective Shuffled Bat algorithm for optimal placement and sizing of multi distributed generations with different load models. Int. J. Electr. Power Energy Syst. 79(6), 120–131 (2016)
Dong, M.G., Li, S.Y., Zhang, H.Y.: Approaches to group decision making with incomplete information based on power geometric operators and triangular fuzzy AHP. Expert Syst. Appl. 42(21), 7846–7857 (2015)
Allahverdi, A.: The third comprehensive survey on scheduling problems with setup times/costs. Eur. J. Oper. Res. 246(2), 345–378 (2015)
Salman, A.A., Ahmad, I., Omran, M.G.H.: A metaheuristic algorithm to solve satellite broadcast scheduling problem. Inf. Sci. 322(20), 72–91 (2015)
Ruiz, R., Vázquez-RodrÃguez, J.: The hybrid flow shop scheduling problem. Eur. J. Oper. Res. 205(1), 1–18 (2010)
Eberle, L., Sugiyama, H., Papadokonstantakis, S., et al.: Data-driven tiered procedure for enhancing yield in drug product manufacturing. Comput. Chem. Eng. 87(6), 82–94 (2016)
Hall, N.G., Sriskandarajah, C.: A survey of machine scheduling problems with blocking and no-wait in process. Oper. Res. 44(3), 510–525 (1996)
Liu, B., Wang, L., Jin, Y.H.: An effective hybrid particle swarm optimization for no-wait flow shop scheduling. Int. J. Adv. Manuf. Technol. 31(9–10), 1001–1011 (2007)
Wang, C.Y., Li, X.P., Wang, Q.: Accelerated tabu search for no-wait flowshop scheduling problem with maximum lateness criterion. Eur. J. Oper. Res. 206(1), 64–72 (2010)
Jolai, F., Asefi, H., Rabiee, M., et al.: Bi-objective simulated annealing approaches for no-wait two-stage flexible flow shop scheduling problem. Scientia Iranica 20(3), 861–872 (2013)
Ding, J.Y., Song, S.J., Gupta, J.N.D., et al.: An improved iterated greedy algorithm with a Tabu-based reconstruction strategy for the no-wait flowshop scheduling problem. Appl. Soft Comput. 30(5), 604–613 (2015)
Pan, Q.K., Ruiz, R.: An estimation of distribution algorithm for lot-streaming flow shop problems with setup times. Omega 40(2), 166–180 (2012)
Zheng, H.Y., Wang, L.: Reduction of carbon emissions and project makespan by a Pareto-based estimation of distribution algorithm. Int. J. Prod. Econ. 164(6), 421–432 (2015)
Fister, I., Rauter, S., Yang, X.S., et al.: Planning the sports training sessions with the bat algorithm. Neurocomputing 149(Part B), 993–1002 (2015)
Adarsh, B.R., Raghunathan, T., Jayabarathi, T., Yang, X.S.: Economic dispatch using chaotic bat algorithm. Energy 96(2), 666–675 (2016)
Wang, K., Choi, S.H., Lu, H.: A hybrid estimation of distribution algorithm for simulation-based scheduling in a stochastic permutation flowshop. Comput. Ind. Eng. 90(12), 186–196 (2015)
Qian, B., Wang, L., Hu, R., Huang, D.X., Wang, X.: A DE-based approach to no-wait flow-shop scheduling. Comput. Ind. Eng. 57(3), 787–805 (2009)
Rahmani, M., Ghanbari, A., Ettefagh, M.M.: Robust adaptive control of a bio-inspired robot manipulator using bat algorithm. Expert Syst. Appl. 56(9), 164–176 (2016)
Pan, Q.K., Wang, L., Mao, K., et al.: An effective artificial bee colony algorithm for a real-world hybrid flowshop problem in steelmaking process. IEEE Trans. Autom. Sci. Eng. 10(2), 307–322 (2013)
Fernandez-Viagas, V., Framinan, J.M.: NEH-based heuristics for the permutation flowshop scheduling problem to minimise total tardiness. Comput. Oper. Res. 60(8), 27–36 (2015)
Vallada, E., Ruiz, R., Framinan, J.M.: New hard benchmark for flowshop scheduling problems minimising makespan. Eur. J. Oper. Res. 240(3), 666–677 (2015)
Acknowledgements
This work is supported by the National Natural Science Foundation of China (Grant Nos. 61174040, 61573144, 61673175) and the Fundamental Research Funds for the Central Universities.
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Sun, Z., Gu, X. (2017). Hybrid Discrete EDA for the No-Wait Flow Shop Scheduling Problem. In: Yue, D., Peng, C., Du, D., Zhang, T., Zheng, M., Han, Q. (eds) Intelligent Computing, Networked Control, and Their Engineering Applications. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 762. Springer, Singapore. https://doi.org/10.1007/978-981-10-6373-2_11
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DOI: https://doi.org/10.1007/978-981-10-6373-2_11
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