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A multi-objective simulation-based optimization approach for inventory replenishment problem with premium freights in convergent supply chains

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  • Avci, Mualla Gonca
  • Selim, Hasan

Abstract

In this study, a multi-objective simulation-based optimization approach is developed to solve inventory replenishment problem with premium freights in convergent supply chains. In this context, a decomposition-based multi-objective differential evolution algorithm (MODE/D) is used to determine demand forecast adjustment factor, safety stock and supplier flexibility parameters that minimize total holding cost, inbound and outbound premium freight ratios simultaneously. The proposed approach is applied a set of problem instances and the performance of the proposed approach is evaluated in comparison with the performance of non-dominated sorting genetic algorithm-II (NSGA-II). Furthermore, the proposed approach is applied to a multi-national automotive supply chain spread on Europe. The results reveal that the proposed approach is effective in solving inventory replenishment problem with premium freights in convergent supply chains.

Suggested Citation

  • Avci, Mualla Gonca & Selim, Hasan, 2018. "A multi-objective simulation-based optimization approach for inventory replenishment problem with premium freights in convergent supply chains," Omega, Elsevier, vol. 80(C), pages 153-165.
    • Handle: RePEc:eee:jomega:v:80:y:2018:i:c:p:153-165
    DOI: 10.1016/j.omega.2017.08.016
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    7. 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).
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    9. Dai, B. & Chen, H.X. & Li, Y.A. & Zhang, Y.D. & Wang, X.Q. & Deng, Y.M., 2021. "Inventory replenishment planning of a distribution system with storage capacity constraints and multi-channel order fulfilment," Omega, Elsevier, vol. 102(C).

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