Application of Mixed Integer Linear Programming (MILP) Method in Capacity Vehicle Routing Problems in Heterogeneous Fleets (HFCVRP) at Bagol Hydroponics UMKM
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Due to variations in vehicle capacity, Bagol Hydroponics UMKM has trouble figuring out cost-effective and distance-efficient product distribution routes. For this reason, this study uses the Mixed Integer Linear Programming (MILP) approach to solve the Heterogeneous Fleet Capacitated Vehicle Routing Problem (HFCVRP). This study is a quantitative applied research project that uses distance data from the Google Maps API to create a mathematical model and the best distribution route using IBM ILOG CPLEX software. The MILP model is designed to decrease the overall distance driven by automobiles while taking sub-trip elimination and vehicle capacity limitations into account. The results demonstrate that the MILP model can provide optimal distribution routes with efficient calculation time and an average distance savings of 1.74% when compared to current routes. Therefore, it has been demonstrated that applying the MILP approach to the HFCVRP problem improves the distribution efficiency of Bagol Hidroponik UMKM products. This can serve as a guide for other UMKM in order to create the most efficient delivery routes.
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