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An Integrated Loss-Based Optimization Model for Apple Supply Chain

In: Operations Research Proceedings 2017

Author

Listed:
  • P. Paam

    (The University of Newcastle)

  • R. Berretta

    (The University of Newcastle)

  • M. Heydar

    (The University of Newcastle)

Abstract

Food supply chain (FSC) refers to the processes from production to delivery of food products from farmers to customers and is different from other kinds of supply chains because of the perishable nature of food. Among the current FSCs, the agricultural fruit supply chain has been paid the least attention. The fact that the quality of fruits deteriorates along supply chain processes and the lack of planning in different stages of FSC results in food loss, which has an impact on food security, insufficiency, and profitability. Therefore, reducing food loss will bring substantial benefits not only to FSC companies but also to society regarding food provision. The purpose of this paper is to present a mixed-integer linear programming (MILP) model for apple supply chain to manage inventory flows in different types of storage rooms for apples from different harvesting periods, while satisfying the demand. The model also reports the optimal type of each storage room. Food loss decision variables are defined to quantify the amount of apple losses in each type of storage room based on the time gap between the harvest and delivery. The objective function of the model is total cost minimization, including penalty costs for apple losses. The model is applied in a real industrial case study in Australia to show its applicability and is solved by Gurobi optimization solver 7.0.

Suggested Citation

  • P. Paam & R. Berretta & M. Heydar, 2018. "An Integrated Loss-Based Optimization Model for Apple Supply Chain," Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 663-669, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-89920-6_88
    DOI: 10.1007/978-3-319-89920-6_88
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    Cited by:

    1. Fatemeh Keshavarz-Ghorbani & Seyed Hamid Reza Pasandideh, 2022. "Modeling and optimizing an agro-supply chain considering different quality grades and storage systems for fresh products: a Benders decomposition solution approach," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 21-50, August.
    2. Fatemeh Keshavarz-Ghorbani & Seyed Hamid Reza Pasandideh, 2022. "A Lagrangian relaxation algorithm for optimizing a bi-objective agro-supply chain model considering CO2 emissions," Annals of Operations Research, Springer, vol. 314(2), pages 497-527, July.

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