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A Lagrangean heuristic algorithm for disassembly scheduling with capacity constraints

Author

Listed:
  • H-J Kim

    (Swiss Federal Institute of Technology (EPFL))

  • D-H Lee

    (Hanyang University)

  • P Xirouchakis

    (Swiss Federal Institute of Technology (EPFL))

Abstract

This paper considers the problem of determining the disassembly schedule (quantity and timing) of products in order to satisfy the demand of their parts or components over a finite planning horizon. The objective is to minimize the sum of set-up, disassembly operation, and inventory holding costs. As an extension of the uncapacitated versions of the problem, we consider the resource capacity restrictions over the planning horizon. An integer program is suggested to describe the problem mathematically, and to solve the problem, a heuristic is developed using a Lagrangean relaxation technique together with a method to find a good feasible solution while considering the trade-offs among different costs. The effectiveness of the algorithm is tested on a number of randomly generated problems and the test results show that the heuristic suggested in this paper can give near optimal solutions within a short amount of computation time.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:10:d:10.1057_palgrave.jors.2602094
    DOI: 10.1057/palgrave.jors.2602094
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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. 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:

    1. Yaping Ren & Xinyu Lu & Hongfei Guo & Zhaokang Xie & Haoyang Zhang & Chaoyong Zhang, 2023. "A Review of Combinatorial Optimization Problems in Reverse Logistics and Remanufacturing for End-of-Life Products," Mathematics, MDPI, vol. 11(2), pages 1-24, January.
    2. Suzanne, Elodie & Absi, Nabil & Borodin, Valeria, 2020. "Towards circular economy in production planning: Challenges and opportunities," European Journal of Operational Research, Elsevier, vol. 287(1), pages 168-190.
    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. Tian, Xiaoyu & Zhang, Zhi-Hai, 2019. "Capacitated disassembly scheduling and pricing of returned products with price-dependent yield," Omega, Elsevier, vol. 84(C), pages 160-174.
    7. 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.

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