Metaheuristic Algorithms for the Many-to-one IRP with Dynamic Velocity

Abstract

Abstract Inventory Routing Problem (IRP) is a combination of inventory management and transportation optimization problems that involve route selection, number of product pickups, and customer demands. In the many-to-one IRP model, the vehicle is sent from the depot and goes to pick up products from several suppliers to the assembly plant. Vehicle loads on this model will increase every time a product is taken from the supplier. It can decrease vehicle speed in the next travel process (dynamic velocity). There are still a few papers that discuss many-toone IRP models with dynamic velocity. Therefore, this study aims to develop a new model called the many-to-one IRP model with dynamic velocity. A modified threshold accepting, variable neighborhood search, and record-to-record travel algorithm with the first improvement local search strategy is used to solve the IRP model. Small datasets many-to-one IRP from previous researches and experimental tests are used to test the algorithms. The results showed that the best-proposed algorithm is competitive when compared to the best-known solution in the previous studies (the average deviation is only 1.86%).