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A branch and bound algorithm for disassembly scheduling with assembly product structure

Author

Listed:
  • H-J Kim

    (Graduate School of Logistics, Inha University)

  • D-H Lee

    (Hanyang University)

  • P Xirouchakis

    (Swiss Federal Institute of Technology (EPFL))

  • O K Kwon

    (Graduate School of Logistics, Inha University)

Abstract

This paper considers a production planning problem in disassembly systems, which is the problem of determining the quantity and timing of disassembling end-of-use/life products in order to satisfy the demand of their parts or components over a planning horizon. The case of single product type without parts commonality is considered for the objective of minimizing the sum of setup and inventory holding costs. To show the complexity of the problem, we prove that the problem is NP-hard. Then, after deriving the properties of optimal solutions, a branch and bound algorithm is suggested that incorporates the Lagrangean relaxation-based upper and lower bounds. Computational experiments are performed on a number of randomly generated problems and the test results indicate that the branch and bound algorithm can give optimal solutions up to moderate-sized problems in a reasonable computation time. A Lagrangean heuristic for a viable alternative for large-sized problems is also suggested and compared with the existing heuristics to show its effectiveness.

Suggested Citation

  • H-J Kim & D-H Lee & P Xirouchakis & O K Kwon, 2009. "A branch and bound algorithm for disassembly scheduling with assembly product structure," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(3), pages 419-430, March.
    • Handle: RePEc:pal:jorsoc:v:60:y:2009:i:3:d:10.1057_palgrave.jors.2602568
    DOI: 10.1057/palgrave.jors.2602568
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    References listed on IDEAS

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    1. D-H Lee & P Xirouchakis, 2004. "A two-stage heuristic for disassembly scheduling with assembly product structure," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(3), pages 287-297, March.
    2. Marshall L. Fisher, 1981. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 27(1), pages 1-18, January.
    3. Wallace B. Crowston & Michael H. Wagner, 1973. "Dynamic Lot Size Models for Multi-Stage Assembly Systems," Management Science, INFORMS, vol. 20(1), pages 14-21, September.
    4. Kongar, Elif & Gupta, Surendra M., 2006. "Disassembly to order system under uncertainty," Omega, Elsevier, vol. 34(6), pages 550-561, December.
    5. H-J Kim & D-H Lee & P Xirouchakis, 2006. "A Lagrangean heuristic algorithm for disassembly scheduling with capacity constraints," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1231-1240, October.
    6. Albert Wagelmans & Stan van Hoesel & Antoon Kolen, 1992. "Economic Lot Sizing: An O(n log n) Algorithm That Runs in Linear Time in the Wagner-Whitin Case," Operations Research, INFORMS, vol. 40(1-supplem), pages 145-156, February.
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    Cited by:

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    2. Abdeljaouad, Mohamed Amine & Bahroun, Zied & Omrane, Anissa & Fondrevelle, Julien, 2015. "Job-shop production scheduling with reverse flows," European Journal of Operational Research, Elsevier, vol. 244(1), pages 117-128.
    3. Slama, Ilhem & Ben-Ammar, Oussama & Thevenin, Simon & Dolgui, Alexandre & Masmoudi, Faouzi, 2022. "Stochastic program for disassembly lot-sizing under uncertain component refurbishing lead times," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1183-1198.
    4. Godichaud, Matthieu & Amodeo, Lionel, 2018. "Economic order quantity for multistage disassembly systems," International Journal of Production Economics, Elsevier, vol. 199(C), pages 16-25.
    5. Liu, Kanglin & Zhang, Zhi-Hai, 2018. "Capacitated disassembly scheduling under stochastic yield and demand," European Journal of Operational Research, Elsevier, vol. 269(1), pages 244-257.
    6. Lu, Liang & Qi, Xiangtong & Liu, Zhixin, 2014. "On the cooperation of recycling operations," European Journal of Operational Research, Elsevier, vol. 233(2), pages 349-358.

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