Mult-Depot Vehicle Routing Problem In Mango Distribution: A Case Study In Southern Of Vietnam

Abstract

The Mixed Integer Linear Programming by using Nearest Neighbor approach is used in this study to address a mango distribution problem in Southern Vietnam. We provide and formalize a model for a multi-product, multi-depot vehicle routing issue with a time window and different mango size constraints for each vehicle. The problem's purpose is to reduce the total cost. Customers' desires for various mango sizes are met by a variety of goods. A Mixed Integer Linear Programming (MILP) paradigm is presented in this study. The construct gap of MILP is measured when comparing the CPLEX to the Nearest Neighbor approach. The computational findings reveal that Nearest Neighbor approach performs better than CPLEX providing a 6.44% gap on average. Furthermore, our suggested method may be used for comparable agricultural logistics in Vietnam and throughout the world.