Modeling The Inventory Routing Problem (IRP) With Multiple Depots With Genetic Algorithms

• Published in: Revista IEEE América Latina Vol. 13; no. 12; pp. 3959 - 3965
• Main Authors: Arango Serna, Martin Dario, Zapata Cortes, Julian Andres, Gutierrez Sepulveda, Daniela
• Format: Journal Article
• Language: English
• Published: Los Alamitos IEEE 01.12.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Collaboration; Companies; Cooperation; Costs; Costs of inventory; Costs of transport; Customers; Distribution of Goods; Genetic algorithms; Inventories; Inventory; Inventory management; Inventory Routing Problem; Mathematical models; Routing; Stockpiling; Supply chains
• ISSN: 1548-0992; 1548-0992
• DOI: 10.1109/TLA.2015.7404933

This paper presents the application of Inventory Routing Problem (IRP) for the distribution of goods between multiple clients (n) and multiple suppliers (m), which is based on the concept of collaboration between companies through vendor managed inventory (VMI). A review of the processes of distribution and routing of goods including the variable inventory and the IRP model with multiple warehouses are presented and it is proposed a genetic algorithm for its solution. The distribution of goods is a key process in the supply chain, since it plays a decisive role in the business logistics costs and in service level provided to customers. The current competitive environment has led companies to work together through partnerships of cooperation and collaboration processes, leading to find new forms of distribution involving multiple suppliers and multiple customers. The main results of the model and the proposed genetic algorithm, reductions in inventory costs and transportation to the problem studied are obtained.