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Hybrid genetic algorithm for permutation flowshop scheduling problems with total flowtime minimization

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  • Zhang, Yi
  • Li, Xiaoping
  • Wang, Qian

Abstract

In this paper, a HGA (hybrid genetic algorithm) is proposed for permutation flowshop scheduling problems (PFSP) with total flowtime minimization, which are known to be NP-hard. One of the chromosomes in the initial population is constructed by a suitable heuristic and the others are yielded randomly. An artificial chromosome is generated by a weighted simple mining gene structure, with which a new crossover operator is presented. Additionally, two effective heuristics are adopted as local search to improve all generated chromosomes in each generation. The HGA is compared with one of the most effective heuristics and a recent meta-heuristic on 120 benchmark instances. Experimental results show that the HGA outperforms the other two algorithms for all cases. Furthermore, HGA obtains 115 best solutions for the benchmark instances, 92 of which are newly discovered.

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  • Zhang, Yi & Li, Xiaoping & Wang, Qian, 2009. "Hybrid genetic algorithm for permutation flowshop scheduling problems with total flowtime minimization," European Journal of Operational Research, Elsevier, vol. 196(3), pages 869-876, August.
    • Handle: RePEc:eee:ejores:v:196:y:2009:i:3:p:869-876
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    1. Tan, Keah-Choon & Narasimhan, Ram & Rubin, Paul A. & Ragatz, Gary L., 2000. "A comparison of four methods for minimizing total tardiness on a single processor with sequence dependent setup times," Omega, Elsevier, vol. 28(3), pages 313-326, June.
    2. Chris N. Potts & Luk N. Van Wassenhove, 1985. "A Branch and Bound Algorithm for the Total Weighted Tardiness Problem," Operations Research, INFORMS, vol. 33(2), pages 363-377, April.
    3. Kim, Yeong-Dae, 1995. "Minimizing total tardiness in permutation flowshops," European Journal of Operational Research, Elsevier, vol. 85(3), pages 541-555, September.
    4. Allahverdi, Ali & Aldowaisan, Tariq, 2002. "New heuristics to minimize total completion time in m-machine flowshops," International Journal of Production Economics, Elsevier, vol. 77(1), pages 71-83, May.
    5. Rajendran, Chandrasekharan & Ziegler, Hans, 2004. "Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs," European Journal of Operational Research, Elsevier, vol. 155(2), pages 426-438, June.
    6. Osman, IH & Potts, CN, 1989. "Simulated annealing for permutation flow-shop scheduling," Omega, Elsevier, vol. 17(6), pages 551-557.
    7. Nearchou, A.C.Andreas C., 2004. "The effect of various operators on the genetic search for large scheduling problems," International Journal of Production Economics, Elsevier, vol. 88(2), pages 191-203, March.
    8. Tasgetiren, M. Fatih & Liang, Yun-Chia & Sevkli, Mehmet & Gencyilmaz, Gunes, 2007. "A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1930-1947, March.
    9. Framinan, J. M. & Leisten, R., 2003. "An efficient constructive heuristic for flowtime minimisation in permutation flow shops," Omega, Elsevier, vol. 31(4), pages 311-317, August.
    10. Ruiz, Rubén & Maroto, Concepciøn & Alcaraz, Javier, 2006. "Two new robust genetic algorithms for the flowshop scheduling problem," Omega, Elsevier, vol. 34(5), pages 461-476, October.
    11. Rajendran, Chandrasekharan & Ziegler, Hans, 1997. "An efficient heuristic for scheduling in a flowshop to minimize total weighted flowtime of jobs," European Journal of Operational Research, Elsevier, vol. 103(1), pages 129-138, November.
    12. Liu, Jiyin & Reeves, Colin R, 2001. "Constructive and composite heuristic solutions to the P//[summation operator]Ci scheduling problem," European Journal of Operational Research, Elsevier, vol. 132(2), pages 439-452, July.
    13. M. R. Garey & D. S. Johnson & Ravi Sethi, 1976. "The Complexity of Flowshop and Jobshop Scheduling," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 117-129, May.
    14. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
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    Cited by:

    1. Chang, Pei-Chann & Huang, Wei-Hsiu & Wu, Jheng-Long & Cheng, T.C.E., 2013. "A block mining and re-combination enhanced genetic algorithm for the permutation flowshop scheduling problem," International Journal of Production Economics, Elsevier, vol. 141(1), pages 45-55.
    2. Pessoa, Luciana S. & Andrade, Carlos E., 2018. "Heuristics for a flowshop scheduling problem with stepwise job objective function," European Journal of Operational Research, Elsevier, vol. 266(3), pages 950-962.
    3. Pan, Quan-Ke & Ruiz, Rubén, 2012. "Local search methods for the flowshop scheduling problem with flowtime minimization," European Journal of Operational Research, Elsevier, vol. 222(1), pages 31-43.
    4. Zhe Zhang & Xiaoling Song & Huijun Huang & Yong Yin & Benjamin Lev, 2022. "Scheduling problem in seru production system considering DeJong’s learning effect and job splitting," Annals of Operations Research, Springer, vol. 312(2), pages 1119-1141, May.
    5. Liu, Ming & Yang, Xuenan & Chu, Feng & Zhang, Jiantong & Chu, Chengbin, 2020. "Energy-oriented bi-objective optimization for the tempered glass scheduling," Omega, Elsevier, vol. 90(C).
    6. Wu, Xueqi & Che, Ada, 2020. "Energy-efficient no-wait permutation flow shop scheduling by adaptive multi-objective variable neighborhood search," Omega, Elsevier, vol. 94(C).
    7. Xiao, Yiyong & Yuan, Yingying & Zhang, Ren-Qian & Konak, Abdullah, 2015. "Non-permutation flow shop scheduling with order acceptance and weighted tardiness," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 312-333.

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