A Benders’ decomposition algorithm for optimizing distribution of perishable products considering postharvest biological behavior in agri-food supply chain: a case study of tomato

V. R. Ghezavati (), S. Hooshyar and R. Tavakkoli-Moghaddam
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V. R. Ghezavati: Islamic Azad University
S. Hooshyar: Islamic Azad University
R. Tavakkoli-Moghaddam: University of Tehran

Central European Journal of Operations Research, 2017, vol. 25, issue 1, No 2, 29-54

Abstract: Abstract This paper presents a periodical planning mathematical model for distribution of fresh agri-food (a case study of tomato) after qualitative segregating. The main objective of the model is to maximize the profit of a distributor that has relative control on logistics decisions associated with distribution of fresh products in a agri-food supply chain. In a real world, there are some differences between suitable qualities of each customer and thus, fair pricing is determined by their level of satisfaction. Simultaneously, this model takes into account freshness and ripeness as for the food grade. For estimation of the ripeness, a formulation is used that is related to postharvest biological behavior of the fresh crops. In turn, quality loss functions for quantification of degrading are designed to accommodate fair pricing. In addition, potential warehouses are considered in this model to achieve suitable maturity and service level. This paper presents a mixed integer programming model according to the problem descriptions. Since the model is hard to be solved for large scale problems, a primal decomposition solution procedure is proposed based on Benders’ decomposition method. Meanwhile, performance of the proposed solution method will be evaluated through some test problems. Finally, the model is validated through decision making for a domestic distributor of fresh tomato in Iran.

Keywords: Agri-food supply chain; Fresh products; Fair pricing; Postharvest maturity behavior; Mixed integer programming; Benders’ decomposition (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s10100-015-0418-3

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