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Scheduling a hybrid assembly-differentiation flowshop to minimize total flow time

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  • Xiong, Fuli
  • Xing, Keyi
  • Wang, Feng

Abstract

This study considers a hybrid assembly-differentiation flowshop scheduling problem (HADFSP), in which there are three production stages, including components manufacturing, assembly, and differentiation. All the components of a job are processed on different machines at the first stage. Subsequently, they are assembled together on a common single machine at the second stage. At the third stage, each job of a particular type is processed on a dedicated machine. The objective is to find a job schedule to minimize total flow time (TFT). At first, a mixed integer programming (MIP) model is formulated and then some properties of the optimal solution are presented. Since the NP-hardness of the problem, two fast heuristics (SPT-based heuristic and NEH-based heuristic) and three hybrid meta-heuristics (HGA-VNS, HDDE-VNS and HEDA-VNS) are developed for solving medium- and large-size problems. In order to evaluate the performances of the proposed algorithms, a lower bound for the HADFSP with TFT criteria (HADFSP-TFT) is established. The MIP model and the proposed algorithms are compared on randomly generated problems. Computational results show the effectiveness of the MIP model and the proposed algorithms. The computational analysis indicates that, in average, the HDDE-VNS performs better and more robustly than the other two meta-heuristics, whereas the NEH heuristic consume little time and could reach reasonable solutions.

Suggested Citation

  • Xiong, Fuli & Xing, Keyi & Wang, Feng, 2015. "Scheduling a hybrid assembly-differentiation flowshop to minimize total flow time," European Journal of Operational Research, Elsevier, vol. 240(2), pages 338-354.
    • Handle: RePEc:eee:ejores:v:240:y:2015:i:2:p:338-354
    DOI: 10.1016/j.ejor.2014.07.004
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    1. Figielska, Ewa, 2014. "A heuristic for scheduling in a two-stage hybrid flowshop with renewable resources shared among the stages," European Journal of Operational Research, Elsevier, vol. 236(2), pages 433-444.
    2. Chen, Shih-Hsin & Chen, Min-Chih, 2013. "Addressing the advantages of using ensemble probabilistic models in Estimation of Distribution Algorithms for scheduling problems," International Journal of Production Economics, Elsevier, vol. 141(1), pages 24-33.
    3. Brah, Shaukat A. & Loo, Luan Luan, 1999. "Heuristics for scheduling in a flow shop with multiple processors," European Journal of Operational Research, Elsevier, vol. 113(1), pages 113-122, February.
    4. De Giovanni, L. & Pezzella, F., 2010. "An Improved Genetic Algorithm for the Distributed and Flexible Job-shop Scheduling problem," European Journal of Operational Research, Elsevier, vol. 200(2), pages 395-408, January.
    5. Tseng, Lin-Yu & Lin, Ya-Tai, 2009. "A hybrid genetic local search algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 198(1), pages 84-92, October.
    6. Lejeune, M.A., 2006. "A variable neighborhood decomposition search method for supply chain management planning problems," European Journal of Operational Research, Elsevier, vol. 175(2), pages 959-976, December.
    7. Framinan, Jose M. & Leisten, Rainer & Ruiz-Usano, Rafael, 2002. "Efficient heuristics for flowshop sequencing with the objectives of makespan and flowtime minimisation," European Journal of Operational Research, Elsevier, vol. 141(3), pages 559-569, September.
    8. 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.
    9. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    10. Naderi, Bahman & Ruiz, Rubén, 2014. "A scatter search algorithm for the distributed permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 323-334.
    11. Ruiz, Ruben & Stutzle, Thomas, 2007. "A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2033-2049, March.
    12. Chung-Yee Lee & T. C. E. Cheng & B. M. T. Lin, 1993. "Minimizing the Makespan in the 3-Machine Assembly-Type Flowshop Scheduling Problem," Management Science, INFORMS, vol. 39(5), pages 616-625, May.
    13. Ruiz, Ruben & Stutzle, Thomas, 2008. "An Iterated Greedy heuristic for the sequence dependent setup times flowshop problem with makespan and weighted tardiness objectives," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1143-1159, June.
    14. Eglese, R. W., 1990. "Simulated annealing: A tool for operational research," European Journal of Operational Research, Elsevier, vol. 46(3), pages 271-281, June.
    15. C. N. Potts & S. V. Sevast'janov & V. A. Strusevich & L. N. Van Wassenhove & C. M. Zwaneveld, 1995. "The Two-Stage Assembly Scheduling Problem: Complexity and Approximation," Operations Research, INFORMS, vol. 43(2), pages 346-355, April.
    16. Allahverdi, Ali & Aydilek, Harun, 2014. "Total completion time with makespan constraint in no-wait flowshops with setup times," European Journal of Operational Research, Elsevier, vol. 238(3), pages 724-734.
    17. Al-Anzi, Fawaz S. & Allahverdi, Ali, 2007. "A self-adaptive differential evolution heuristic for two-stage assembly scheduling problem to minimize maximum lateness with setup times," European Journal of Operational Research, Elsevier, vol. 182(1), pages 80-94, October.
    18. 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.
    19. Pan, Quan-Ke & Ruiz, Rubén, 2012. "An estimation of distribution algorithm for lot-streaming flow shop problems with setup times," Omega, Elsevier, vol. 40(2), pages 166-180, April.
    20. Wang, Sheng-yao & Wang, Ling & Liu, Min & Xu, Ye, 2013. "An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem," International Journal of Production Economics, Elsevier, vol. 145(1), pages 387-396.
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    2. 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).
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    4. Framinan, Jose M. & Perez-Gonzalez, Paz & Fernandez-Viagas, Victor, 2019. "Deterministic assembly scheduling problems: A review and classification of concurrent-type scheduling models and solution procedures," European Journal of Operational Research, Elsevier, vol. 273(2), pages 401-417.

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