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The joint replenishment and delivery scheduling of the one-warehouse, n-retailer system

Author

Listed:
  • Cha, B.C.
  • Moon, I.K.
  • Park, J.H.

Abstract

We deal with the joint replenishment and delivery scheduling of the one-warehouse, n-retailer system in this paper. We suggest a more flexible policy for the joint replenishment and delivery scheduling of a warehouse compared with the existing researches. We introduce the mathematical model and two efficient algorithms for the joint replenishment and delivery scheduling of the warehouse. Subsequently, we develop the hybrid genetic algorithm (GA) and compare it with two efficient heuristic algorithms for extensive computational experiments. Further, we show the advantages of our GA in dealing easily with resource restrictions.

Suggested Citation

  • Cha, B.C. & Moon, I.K. & Park, J.H., 2008. "The joint replenishment and delivery scheduling of the one-warehouse, n-retailer system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 720-730, September.
    • Handle: RePEc:eee:transe:v:44:y:2008:i:5:p:720-730
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    Citations

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    Cited by:

    1. Moon, I.K. & Cha, B.C. & Lee, C.U., 2011. "The joint replenishment and freight consolidation of a warehouse in a supply chain," International Journal of Production Economics, Elsevier, vol. 133(1), pages 344-350, September.
    2. Zhang, Ying & Qi, Mingyao & Miao, Lixin & Liu, Erchao, 2014. "Hybrid metaheuristic solutions to inventory location routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 305-323.
    3. He-Yau Kang & Amy H.I. Lee & Chien-Wei Wu & Cheng-Han Lee, 2017. "An efficient method for dynamic-demand joint replenishment problem with multiple suppliers and multiple vehicles," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1065-1084, February.
    4. Amaya, Ciro Alberto & Carvajal, Jimmy & Castaño, Fabian, 2013. "A heuristic framework based on linear programming to solve the constrained joint replenishment problem (C-JRP)," International Journal of Production Economics, Elsevier, vol. 144(1), pages 243-247.
    5. Yao, Ming-Jong & Lin, Jen-Yen & Lin, Yu-Liang & Fang, Shu-Cherng, 2020. "An integrated algorithm for solving multi-customer joint replenishment problem with districting consideration," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    6. Nguyen, Christine & Dessouky, Maged & Toriello, Alejandro, 2014. "Consolidation strategies for the delivery of perishable products," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 108-121.
    7. Seyed Hamid Reza Pasandideh & Seyed Taghi Akhavan Niaki & Reza Abdollahi, 2020. "Modeling and solving a bi-objective joint replenishment-location problem under incremental discount: MOHSA and NSGA-II," Operational Research, Springer, vol. 20(4), pages 2365-2396, December.
    8. Qiu, Xuan & Lam, Jasmine Siu Lee & Huang, George Q., 2015. "A bilevel storage pricing model for outbound containers in a dry port system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 65-83.
    9. Cui, Ligang & Deng, Jie & Liu, Rui & Xu, Dongyang & Zhang, Yajun & Xu, Maozeng, 2020. "A stochastic multi-item replenishment and delivery problem with lead-time reduction initiatives and the solving methodologies," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    10. Carvajal, Jimmy & Castaño, Fabian & Sarache, William & Costa, Yasel, 2020. "Heuristic approaches for a two-echelon constrained joint replenishment and delivery problem," International Journal of Production Economics, Elsevier, vol. 220(C).

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