Abstract
The no-wait lot-streaming flow shop scheduling has important applications in modern industry. This paper deals with the makespan for the problems with equal-size sublots. A fast calculation method is designed to reduce the time complexity. A discrete invasive weed optimization (DIWO) algorithm is proposed. In the proposed DIWO algorithm, job permutation representation is utilized, Nawaz–Enscore–Ham heuristic is used to generate initial solutions with high quality. A reference local search procedure is employed to perform local exploitation. Extensive computational simulations and comparisons are provided, which demonstrate the effectiveness of the proposed DIWO algorithm.
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Chang, J.H., Chiu, H.N.: A comprehensive review of lot streaming. Int. J. Prod. Res. 4(8), 1515–1536 (2005)
Yoon, S.H., Ventura, J.A.: Minimizing the mean weighted absolute deviation from due dates in lot-streaming flow shop scheduling. Comput. Oper. Res. 29, 1301–1315 (2002)
Yoon, S.H., Ventura, J.A.: An application of genetic algorithms to lot-streaming flow shop scheduling. IIE Trans. 34, 779–787 (2002)
Marimuthu, S., Ponnambalam, S.G., Jawahar, N.: Tabu search and simulated annealing algorithms for scheduling in flow shops with lot streaming. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 221, 317–331 (2007)
Marimulthu, S., Ponnambalam, S.G., Jawahar, N.: Evolutionary algorithms for scheduling m-machine flow shop with lot streaming. Robot. Comput.-Integr. Manuf. 24, 125–139 (2008)
Marimulthu, S., Ponnambalam, S.G., Jawaha, N.: Threshold accepting and ant-colony optimization algorithm for scheduling m-machine flow shop with lot streaming. J. Mater. Process. Technol. 209, 1026–1041 (2009)
Tseng, C.T., Liao, C.J.: A discrete particle swarm optimization for lot-streaming flow shop scheduling problem. Eur. J. Oper. Res. 191, 360–373 (2008)
Sriskandarajah, C., Wagneur, E.: Lot streaming and scheduling multiple products in two-machine no-wait flowshops. IIE Trans. 31(8), 695–707 (1999)
Kumar, S., Bagchi, T.P., Sriskandarajah, C.: Lot streaming and scheduling heuristics for m-machine no-wait flowshops. Comput. Ind. Eng. 38(1), 149–172 (2000)
Chen, J., Steiner, G.: On discrete lot streaming in no-wait flow shops. IIE Trans. 35(2), 91–101 (2003)
Hall, N.G., Laporte, G., Selvarajah, E.: Scheduling and lot streaming in flowshops with no-wait in process. J. Sched. 6(4), 339–354 (2003)
Kim, K., Jeong, I.J.: Flow shop scheduling with no-wait flexible lot streaming using an adaptive genetic algorithm. Int. J. Adv. Manuf. Technol. 44(11–12), 1181–1190 (2009)
Kim, K.W., Jeong, I.J.: Flow shop scheduling with no-wait flexible lot streaming using adaptive genetic algorithm. In: International Conference on Computational Science and its Applications, ICCSA 2007. IEEE, 474–479 (2007)
Zhang, P., Wang, L.: Grouped fruit-fly optimization algorithm for the no-wait lot streaming flow shop scheduling. In: Huang, D.-S., Jo, K.-H., Wang, L. (eds.) ICIC 2014. LNCS, vol. 8589, pp. 664–674. Springer, Heidelberg (2014)
Mehrabian, A.R., Lucas, C.: A novel numerical optimization algorithm inspired from weed colonization. Ecol. Inform. 1, 355–366 (2006)
Zhou, Y., Luo, Q., Chen, H.: A discrete invasive weed optimization algorithm for solving traveling salesman problem. Neurocomputing 151, 1227–1236 (2015)
Pouya, A.R., Solimanpur, M., Rezaee, M.J.: Solving multi-objective portfolio optimization problem using invasive weed optimization. Swarm Evol. Comput. 28, 42–57 (2016)
Hetmaniok, E., Slota, D., Zielonka, A.: Experimental verification of approximate solution of the inverse Stefan problem obtained by applying the invasive weed optimization algorithm. Therm. Sci. 19(Suppl. 1), 205–212 (2015)
Sang, H.Y., Pan, Q.K., Duan, P.Y.: An effective discrete invasive weed optimization algorithm for lot-streaming flowshop scheduling problems. J. Intell. Manuf. 1–13 (2015). doi:10.1007/s10845-015-1182-x
Zhou, Y., Chen, H., Zhou, G.: Invasive weed optimization algorithm for optimization no-idle flow shop scheduling problem. Neurocomputing 137(5), 285–292 (2014)
Mehrabian, A.R., Koma, A.Y.: A novel technique for optimal placement of piezoelectric actuators on smart structures. J. Franklin Inst. 348, 12–23 (2011)
Nawaz, M., Enscore, E.J.R., Ham, I.: A heuristic algorithm for the m machine, n job flowshop sequencing problem. Omega-Int. J. Manag. Sci. 11(1), 91–95 (1983)
Acknowledgements
This research is partially supported by National Foundation of China (515775212, 61503170, 61573178, and 61374187), Shandong Province Higher Educational Science and Technology Program (J14LN28).
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Sang, HY., Duan, PY., Li, JQ. (2016). A Discrete Invasive Weed Optimization Algorithm for the No-Wait Lot-Streaming Flow Shop Scheduling Problems. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9771. Springer, Cham. https://doi.org/10.1007/978-3-319-42291-6_52
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DOI: https://doi.org/10.1007/978-3-319-42291-6_52
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