Genetic Algorithm based approach for the Multi Product Multi Period Inventory Routing Problem

摘要

The Inventory Routing Problems (IRP) is an important component of Supply Chain Management. The IRP refers to the coordination of the inventory management and transportation. The solution in IRP gives the optimum vehicle routing while at the same time minimizes the transportation and inventory costs. The problem addressed is of the many-to-one type with finite horizon, multi-periods, multi-suppliers, single assembly plant, where a fleet of capacitated identical vehicles, housed at a depot, transport parts from the suppliers to meet the demand specified by the assembly plant for each period. We propose a hybrid genetic algorithm based on allocation first, route second method to determine an optimal inventory and transportation policy that minimizes the total cost. We introduce two new representations and design corresponding crossover and mutation operators. It is found that a simple representation produces very encouraging results.