A new model and heuristic for a multi-period inventory-routing problem

The need for integration in supply chain management leads us to consider the coordination of two logistic planning functions: transportation and inventory. The coordination of these activities can be an extremely important source of competitive advantage in supply chain management. The battle for cost reduction can involve finding the equilibrium between transportation and inventory management costs. The problem that considers Vehicle Routing (VR) and Inventory Management (IM) decisions together is known as the Inventory Routing Problem (IRP). The main objective in the IRP is to design the set of routes and decide the delivered quantities that minimize transportation cost while controlling the inventory costs. Considering these two problems in an integrated manner can reduce total costs. In this work, we study a specific case of an inventory-routing problem with weekly planning for different types of demand. We propose a Multi-Period IRP with customer that face two types of demand: stochastic and deterministic (MPIRP-SDD). The objective is to plan the deliveries for a week period and they routes that will make these deliveries. A heuristic methodology based on the Iterated Local Search is proposed to solve the Multi-Period Inventory Routing Problem with stochastic and deterministic demand. We also present some computational results and finally we draw some conclusions and further research.