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A new model and hybrid approach for large scale inventory routing problems

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  • Yu, Yugang
  • Chen, Haoxun
  • Chu, Feng

Abstract

This paper studies an inventory routing problem (IRP) with split delivery and vehicle fleet size constraint. Due to the complexity of the IRP, it is very difficult to develop an exact algorithm that can solve large scale problems in a reasonable computation time. As an alternative, an approximate approach that can quickly and near-optimally solve the problem is developed based on an approximate model of the problem and Lagrangian relaxation. In the approach, the model is solved by using a Lagrangian relaxation method in which the relaxed problem is decomposed into an inventory problem and a routing problem that are solved by a linear programming algorithm and a minimum cost flow algorithm, respectively, and the dual problem is solved by using the surrogate subgradient method. The solution of the model obtained by the Lagrangian relaxation method is used to construct a near-optimal solution of the IRP by solving a series of assignment problems. Numerical experiments show that the proposed hybrid approach can find a high quality near-optimal solution for the IRP with up to 200 customers in a reasonable computation time.

Suggested Citation

  • Yu, Yugang & Chen, Haoxun & Chu, Feng, 2008. "A new model and hybrid approach for large scale inventory routing problems," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1022-1040, September.
  • Handle: RePEc:eee:ejores:v:189:y:2008:i:3:p:1022-1040
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    12. Jafarian, Ahmad & Asgari, Nasrin & Mohri, Seyed Sina & Fatemi-Sadr, Elham & Farahani, Reza Zanjirani, 2019. "The inventory-routing problem subject to vehicle failure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 254-294.
    13. Liu, Ming & Liu, Xin & Chu, Feng & Zheng, Feifeng & Chu, Chengbin, 2019. "Distributionally robust inventory routing problem to maximize the service level under limited budget," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 190-211.
    14. Gharehgozli, Amir & Zaerpour, Nima, 2018. "Stacking outbound barge containers in an automated deep-sea terminal," European Journal of Operational Research, Elsevier, vol. 267(3), pages 977-995.
    15. Bertazzi, Luca & Moezi, Sarem Deilami & Maggioni, Francesca, 2021. "The value of integration of full container load, less than container load and air freight shipments in vendor–managed inventory systems," International Journal of Production Economics, Elsevier, vol. 241(C).
    16. Oualid Guemri & Abdelghani Bekrar & Bouziane Beldjilali & Damien Trentesaux, 2016. "GRASP-based heuristic algorithm for the multi-product multi-vehicle inventory routing problem," 4OR, Springer, vol. 14(4), pages 377-404, December.
    17. Soysal, Mehmet & Bloemhof-Ruwaard, Jacqueline M. & Haijema, Rene & van der Vorst, Jack G.A.J., 2015. "Modeling an Inventory Routing Problem for perishable products with environmental considerations and demand uncertainty," International Journal of Production Economics, Elsevier, vol. 164(C), pages 118-133.
    18. Oğuz Solyalı & Jean-François Cordeau & Gilbert Laporte, 2012. "Robust Inventory Routing Under Demand Uncertainty," Transportation Science, INFORMS, vol. 46(3), pages 327-340, August.
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    22. Moin, N.H. & Salhi, S. & Aziz, N.A.B., 2011. "An efficient hybrid genetic algorithm for the multi-product multi-period inventory routing problem," International Journal of Production Economics, Elsevier, vol. 133(1), pages 334-343, September.

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