A new model of Fleet Size and Mix Green Inventory Routing Problem, Solution: Multi-Objective Quantum Evolutionary Algorithm

Abstract

In Inventory Routing Problem (IRP), which is one of the most important logistics problems, decisions regarding the distribution and inventory management must be made by an integrated managerial approach. In this type of problems, decision maker usually has the option to use several types of vehicles to form a fleet with appropriate size and composition in order to minimize both inventory and transportation costs. Considering the amount of pollution produced, in this problem, may reduce pollution . This paper proposes a new model for green inventory routing problem with heterogeneous fleet. The objectives of the proposed model are to minimize the emissions, the fleet, routing and inventory costs. Due to the NP-hard nature of the assessed problem, a meta-heuristic algorithm based on Quantum Evolutionary Algorithm (QEA) is proposed. To evaluate the performance of the proposed algorithm, its results are compared with the results of exact method and basic Algorithm. The results of these comparisons indicate the good performance of the proposed algorithm.

Keywords

• comprehensive modal emission model (cmem)
• fuel consumption
• inventory routing problem with heterogeneous fleet
• quantum evolutionary algorithm