Solving A Multi-Period Inventory Routing Problem With Multi-Vist: A Case Study Of Mesa Group

Abstract

Logistics has since played a key role in supply chain management. It is not denied that logistics has since played a key role in supply chain management for decades. This problem in general speaking or inventory coordination alone is enlarging as the global economic trade skyrocketing within the last ten years. Therefore, the high integration of these different functions that is fundamental between the inner inventory control and transportation management system to obtain a better coordination level. In the development of the distribution network, the product delivery has seemed as importantly necessary determinants based on making many decisions: (1) when to make and order from suppliers, (2) how to manage inventory level of distributors, (3) how much to deliver to supermarkets, (4) time schedule for store’s delivery. Among other proposed Inventory Routing Problem (IRP), the most common one to be discussed and currently applied to the real-life situation consists of a distribution of a commodity from a distributor to a set of retailers over a discrete planning horizon with a homogeneous fleet of capacitated vehicles. The problem simultaneously encounters various problems. To be more specific, vehicles pick up one or more products from origin distributor and then move it to multiple origins stores (pickup customers) and finally deliver it to multiple destinations (delivery customers) over a period of time. The most interesting ones are in rebalancing inventory problems in store chains, where some stores have an excess of inventory and others are running out of stock. So as to entangle the issues, an improved vehicle routing along with efficient inventory management needs to be proposed. In this paper, the focus is on the Inventory Routing Problem applied in MESA Group – the only distributor of P&G product in Vietnam. MESA is currently owning a private fleet ofiv vehicles, but as the demand constantly rising, the inventory routing problem (IRP) addressed in this study is a many-to-one distribution network consisting of an assembly plant and many distinct suppliers where each supplies a distinct product. We consider a finite horizon, multiperiods, multi-suppliers, and multi-products where a fleet of capacitated homogeneous vehicles, housed at a depot, transport products from the suppliers to meet the demand specified by the assembly plant in each period. The demand for each product is deterministic and time-varying. A mathematical formulation of the problem is given and CPLEX 9.1 is run for a finite amount of time to obtain lower and upper bounds. A hybrid genetic algorithm, which is based on the allocation first route second strategy and which considers both the inventory and the transportation costs, is proposed. In addition to a new set of crossover and mutation operators, we also introduce two new chromosome representations. Several medium and small-sized problems are also constructed and added to the existing data sets to show the effectiveness of the proposed approach.