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The development of gradual-priority weighting approach for the multi-objective flowshop scheduling problem

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  • Chang, Pei-Chann
  • Hsieh, Jih-Chang
  • Lin, Shui-Geng

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  • Chang, Pei-Chann & Hsieh, Jih-Chang & Lin, Shui-Geng, 2002. "The development of gradual-priority weighting approach for the multi-objective flowshop scheduling problem," International Journal of Production Economics, Elsevier, vol. 79(3), pages 171-183, October.
    • Handle: RePEc:eee:proeco:v:79:y:2002:i:3:p:171-183
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    References listed on IDEAS

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    1. Herbert G. Campbell & Richard A. Dudek & Milton L. Smith, 1970. "A Heuristic Algorithm for the n Job, m Machine Sequencing Problem," Management Science, INFORMS, vol. 16(10), pages 630-637, June.
    2. Ho, Johnny C. & Chang, Yih-Long, 1991. "A new heuristic for the n-job, M-machine flow-shop problem," European Journal of Operational Research, Elsevier, vol. 52(2), pages 194-202, May.
    3. Rajendran, Chandrasekharan, 1995. "Heuristics for scheduling in flowshop with multiple objectives," European Journal of Operational Research, Elsevier, vol. 82(3), pages 540-555, May.
    4. Neppalli, Venkata Ranga & Chen, Chuen-Lung & Gupta, Jatinder N. D., 1996. "Genetic algorithms for the two-stage bicriteria flowshop problem," European Journal of Operational Research, Elsevier, vol. 95(2), pages 356-373, December.
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    Cited by:

    1. Laslo, Zohar & Golenko-Ginzburg, Dimitri & Keren, Baruch, 2008. "Optimal booking of machines in a virtual job-shop with stochastic processing times to minimize total machine rental and job tardiness costs," International Journal of Production Economics, Elsevier, vol. 111(2), pages 812-821, February.
    2. Chang, Pei-Chann & Hsieh, Jih-Chang & Liu, Chen-Hao, 2006. "A case-injected genetic algorithm for single machine scheduling problems with release time," International Journal of Production Economics, Elsevier, vol. 103(2), pages 551-564, October.
    3. Maedeh Fasihi & Reza Tavakkoli-Moghaddam & Fariborz Jolai, 2023. "A bi-objective re-entrant permutation flow shop scheduling problem: minimizing the makespan and maximum tardiness," Operational Research, Springer, vol. 23(2), pages 1-41, June.
    4. Yenisey, Mehmet Mutlu & Yagmahan, Betul, 2014. "Multi-objective permutation flow shop scheduling problem: Literature review, classification and current trends," Omega, Elsevier, vol. 45(C), pages 119-135.
    5. Chiang, Tsung-Che & Lin, Hsiao-Jou, 2013. "A simple and effective evolutionary algorithm for multiobjective flexible job shop scheduling," International Journal of Production Economics, Elsevier, vol. 141(1), pages 87-98.
    6. Zheng, Huan-yu & Wang, Ling, 2015. "Reduction of carbon emissions and project makespan by a Pareto-based estimation of distribution algorithm," International Journal of Production Economics, Elsevier, vol. 164(C), pages 421-432.
    7. Vacharapoom Benjaoran & Nashwan Dawood & Brian Hobbs, 2005. "Flowshop scheduling model for bespoke precast concrete production planning," Construction Management and Economics, Taylor & Francis Journals, vol. 23(1), pages 93-105.
    8. Varadharajan, T.K. & Rajendran, Chandrasekharan, 2005. "A multi-objective simulated-annealing algorithm for scheduling in flowshops to minimize the makespan and total flowtime of jobs," European Journal of Operational Research, Elsevier, vol. 167(3), pages 772-795, December.
    9. Gerardo Minella & Rubén Ruiz & Michele Ciavotta, 2008. "A Review and Evaluation of Multiobjective Algorithms for the Flowshop Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 20(3), pages 451-471, August.
    10. Zhao, Siwei & Liu, Weidong & Zhu, Mengyuan & Ma, Yanfang & Li, Zongmin, 2021. "A priority-based multi-objective framework for water resources diversion and allocation in the middle route of the South-to-North Water Diversion Project," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    11. Gajpal, Yuvraj & Rajendran, Chandrasekharan, 2006. "An ant-colony optimization algorithm for minimizing the completion-time variance of jobs in flowshops," International Journal of Production Economics, Elsevier, vol. 101(2), pages 259-272, June.

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