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Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 591))

Abstract

The purpose of this research is to propose an optimization method for the stochastic disassembly lot-sizing problem under uncertainty of lead time. One type of end-of-life (EoL) product is disassembled to satisfy a dynamic and known demand of items over a planning horizon. The tactical problem is considered as a random optimization problem in order to minimize the expected total cost. A sample average approximation (SAA) approach, is developed to model the studied random optimization problem and minimize the average total cost. The effectiveness of the solution approach has successfully tested and proved.

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References

  1. Barba-Gutiéerrez, Y., Adenso-Díaz, B.: Reverse MRP under uncertain and imprecise demand. Int. J. Adv. Manuf. Technol. 40(3–4), 413–424 (2009)

    Article  Google Scholar 

  2. Ilgin, M.A., Gupta, S.M.: Environmentally conscious manufacturing and product recovery (ECMPRO): a review of the state of the art. J. Environ. Manag. 91(3), 563–591 (2010)

    Article  Google Scholar 

  3. Inderfurth, K., Langella, I.M.: Heuristics for solving disassemble-to-order problems with stochastic yields. OR Spectr. 28(1), 73–99 (2006)

    Article  Google Scholar 

  4. Inderfurth, K., Vogelgesang, S., Langella, I.M.: How yield process misspecification affects the solution of disassemble-to-order problems. Int. J. Prod. Econ. 169, 56–67 (2015)

    Article  Google Scholar 

  5. Kim, H.J., Xirouchakis, P.: Capacitated disassembly scheduling with random demand. Int. J. Prod. Res. 48(23), 7177–7194 (2010)

    Article  Google Scholar 

  6. Lamiri, M., Xie, X., Dolgui, A., Grimaud, F.: A stochastic model for operating room planning with elective and emergency demand for surgery. Eur. J. Oper. Res. 185(3), 1026–1037 (2008)

    Article  MathSciNet  Google Scholar 

  7. Liu, K., Zhang, Z.H.: Capacitated disassembly scheduling under stochastic yield and demand. Eur. J. Oper. Res. 269(1), 244–257 (2018)

    Article  MathSciNet  Google Scholar 

  8. Ruszczynski, A., Shapiro, A.: Handbooks in operations research and management. Science 10, 1–64 (2003)

    Google Scholar 

  9. Slama, I., Ben-Ammar, O., Masmoudi, F., Dolgui, A.: Scenario-based stochastic linear programming model for multi-period disassembly lot-sizing problems under random lead time. IFAC-PapersOnLine 52(13), 595–600 (2019)

    Article  Google Scholar 

  10. Slama, I., Ben-Ammar, O., Dolgui, A., Masmoudi, F.: Newsboy problem with two- level disassembly system and stochastic lead time. In: ROADEF (2020)

    Google Scholar 

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Correspondence to Alexandre Dolgui .

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Slama, I., Ben-Ammar, O., Dolgui, A., Masmoudi, F. (2020). A Stochastic Model for a Two-Level Disassembly Lot-Sizing Problem Under Random Lead Time. In: Lalic, B., Majstorovic, V., Marjanovic, U., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. The Path to Digital Transformation and Innovation of Production Management Systems. APMS 2020. IFIP Advances in Information and Communication Technology, vol 591. Springer, Cham. https://doi.org/10.1007/978-3-030-57993-7_32

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  • DOI: https://doi.org/10.1007/978-3-030-57993-7_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57992-0

  • Online ISBN: 978-3-030-57993-7

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