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Calculating safety stocks for assembly systems with random component procurement lead times: A branch and bound algorithm

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  • Louly, Mohamed-Aly Ould
  • Dolgui, Alexandre

Abstract

In this paper, a discrete single-level multi-component inventory control model for assembly systems with random component procurement lead times is considered. The economic order quantity (EOQ) policy is used for a type of finished product. The requirements of the components are constant and cyclic (periodic), and their values per period are deduced from the EOQ for the finished product. The paper focuses on the components safety stock calculation. The objective is to minimise the average holding cost of the components while keeping the desired service level for the finished product. For this, an upper bound, two lower bounds, two dominance properties and an efficient branch and bound algorithm are suggested. Several tests are executed and conclusions are drawn. The proposed model provides a substantial saving for assembly systems with a large number and unreliable delivery of components as in semi-conductor and automotive industries.

Suggested Citation

  • Louly, Mohamed-Aly Ould & Dolgui, Alexandre, 2009. "Calculating safety stocks for assembly systems with random component procurement lead times: A branch and bound algorithm," European Journal of Operational Research, Elsevier, vol. 199(3), pages 723-731, December.
    • Handle: RePEc:eee:ejores:v:199:y:2009:i:3:p:723-731
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Faicel Hnaien & Alexandre Dolgui & Desheng Dash Wu, 2016. "Single-period inventory model for one-level assembly system with stochastic lead times and demand," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 186-203, January.
    2. Borodin, Valeria & Dolgui, Alexandre & Hnaien, Faicel & Labadie, Nacima, 2016. "Component replenishment planning for a single-level assembly system under random lead times: A chance constrained programming approach," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 79-86.
    3. Wang, Hong, 2013. "Contingent payment auction mechanism in multidimensional procurement auctions," European Journal of Operational Research, Elsevier, vol. 224(2), pages 404-413.
    4. Barros, Júlio & Cortez, Paulo & Carvalho, M. Sameiro, 2021. "A systematic literature review about dimensioning safety stock under uncertainties and risks in the procurement process," Operations Research Perspectives, Elsevier, vol. 8(C).
    5. Yin, Zhe & Wang, Chen & Yin, Qian, 2018. "Coordinating overseas and local sourcing through a capacitated expediting transportation policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 258-271.
    6. Gonçalves, João N.C. & Sameiro Carvalho, M. & Cortez, Paulo, 2020. "Operations research models and methods for safety stock determination: A review," Operations Research Perspectives, Elsevier, vol. 7(C).
    7. Mitali Sarkar & Biswajit Sarkar, 2019. "Optimization of Safety Stock under Controllable Production Rate and Energy Consumption in an Automated Smart Production Management," Energies, MDPI, vol. 12(11), pages 1-16, May.
    8. 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.
    9. Osman, Hany & Demirli, Kudret, 2012. "Integrated safety stock optimization for multiple sourced stockpoints facing variable demand and lead time," International Journal of Production Economics, Elsevier, vol. 135(1), pages 299-307.
    10. Ben-Ammar, Oussama & Dolgui, Alexandre & Wu, Desheng Dash, 2018. "Planned lead times optimization for multi-level assembly systems under uncertainties," Omega, Elsevier, vol. 78(C), pages 39-56.

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