مدیریت صنعتی (Feb 2022)

The Multi-Objective Locating Model for Cross-Docking Centers and Vehicle Routing Scheduling With Split Demands for Perishable Products

  • Mahboobeh Kazemi,
  • Darush Mohamadi Zanjirani,
  • Majid Esmaeilian

DOI
https://doi.org/10.22059/imj.2022.333499.1007883
Journal volume & issue
Vol. 13, no. 4
pp. 606 – 633

Abstract

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Objective: This paper sought to develop a food supply chain model that integrates the operational decisions (vehicle routing and scheduling) with strategic decisions (cross-docking centers locating) in a hub network, considering life - real constraints and the perishable nature. Methods: In this research, an integer Goal programming model for location, timing, and vehicle routing problems is proposed with the possibility of split demand for fresh items in which the impact of perishability is considered as the second objective besides the total cost. Accordingly, an augmented -constraint method was used to generate a Pareto optimal for these conflicting objectives. This model was implemented in CPLEX software, 20.1 version. Results: Previous studies neither considered the perishable nature of the items in cross-docking locations nor the split delivery vehicle routing scheduling models. The most important aspect of innovation in this research was that the characteristics of split demand in improving the timing of vehicles were used and in addition to improving the cost function, the value of the second objective function (network accountability) was also increased dramatically. The results of sensitivity analysis on some parameters such as shelf life of products (SL), quality reduction point (QRP), and capacity of vehicles (Q), showed the efficiency of the proposed model. Conclusion: Finally, the proposed model was utilized in random data and numerical results, and some managerial insights were provided. Comparing the results of the proposed model with the benchmark model in equal experimental conditions, the efficiency of the proposed model was confirmed. Cross-docking is nowadays used by many companies and industries and the provided model by this study can be applied especially for time-sensitive products.

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