A Bi - Objective Model and Efficient Heuristic for Hazardous Material Inventory Routing Problem

Two types of decisions that directly affect the performance of a distribution system is the vehicle routing and inventory assignment. These problems have been studied separately for many years. The inventory routing problem (IRP) is integration of above mentioned distribution problems. In the other words, IRP assumes each customer maintains a local inventory of a product and consumes a certain amount of that product each day. Each day a fleet of vehicles is dispatched over a set of routes to resupply a subset of the customers. Specifically, IRP determines inventory allocation and vehicle routs by objective to minimize the distribution cost. Therefore, the determination of hazardous materials distribution routes can be defined as a bi-objective inventory routing problem (BiIRP) while risk minimization accompanies the cost minimization in the objective function. In this paper we introduce an efficient biobjective mixed integer linear programming model for IRP. For this purpose, we extend a well-known vehicle routing problem (VRP) formulation to consider the IRP assumptions. Also, we propose a binary chromosome representation to use in Multi-Objective GA algorithm. Finally, in order to evaluate the efficiency of proposed heuristic we design some novel experiments and solve them by both proposed algorithm and Cplex 12.2. Keywords— Genetic algorithm, hazardous material distribution, inventory routing problem, vehicle routing.