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Sample average approximation for multi-vehicle collection–disassembly problem under uncertainty

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  • Muh. Khoirul Khakim Habibi
  • Olga Battaïa
  • Van-Dat Cung
  • Alexandre Dolgui
  • Manoj Kumar Tiwari

Abstract

The implementation of the circular economy is increasingly supported by many governments. It is performed by integrating the activities of reverse supply chain (RSC) into those of forward supply chain. However, many companies that traditionally focus on the activities of forward supply chain have decided to collaborate with third-party reverse logistics providers to manage the RSC. This collaboration motivates the work presented in this paper to propose better decisions for decision makers in the providers under the fact that integrating decisions of the collection of End-of-Life products and their disassembly process proposes a RSC with better performance. In this paper, an integrated problem concerning those decisions is presented and formalised. It also deals with the uncertainty of the quality and the quantity of products as well as the demands of the associated components. Two approximate methods are developed to provide the solutions.

Suggested Citation

  • Muh. Khoirul Khakim Habibi & Olga Battaïa & Van-Dat Cung & Alexandre Dolgui & Manoj Kumar Tiwari, 2019. "Sample average approximation for multi-vehicle collection–disassembly problem under uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 57(8), pages 2409-2428, April.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2409-2428
    DOI: 10.1080/00207543.2018.1519262
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    Cited by:

    1. Lei, Jieyu & Che, Ada & Van Woensel, Tom, 2024. "Collection-disassembly-delivery problem of disassembly centers in a reverse logistics network," European Journal of Operational Research, Elsevier, vol. 313(2), pages 478-493.
    2. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).
    3. Yicong Gao & Shanhe Lou & Hao Zheng & Jianrong Tan, 2023. "A data-driven method of selective disassembly planning at end-of-life under uncertainty," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 565-585, February.
    4. Ming Liu & Yueyu Ding & Lihua Sun & Runchun Zhang & Yue Dong & Zihan Zhao & Yiting Wang & Chaoran Liu, 2023. "Green Airline-Fleet Assignment with Uncertain Passenger Demand and Fuel Price," Sustainability, MDPI, vol. 15(2), pages 1-22, January.

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