Developing an improved particle swarm optimization algorithm for solving the inventory routing problem with direct shipment

This paper considers a multi-period multi-product inventory routing problem whereas the objective is to minimize total system cost that includes production setup, inventory and distribution costs. The problem integrates decisions on the production planning, inventory management and distribution planning. Here, we assume that products are produced and delivered from one manufacturer to a set of retailers through a fleet of homogenous capacitated vehicles under direct shipping strategy. Since the problem is known as an NP-hard problem, this paper proposes an improved particle swarm optimization algorithm for solving the problem. The efficiency and the reliability of the proposed algorithm are evaluated by using various test problems with different sizes that is randomly generated. The performance of the developed algorithm is compared with two different algorithms: Particle Swarm Optimization, and Genetic Algorithm. The numerical results show that the developed algorithm outperforms benchmark algorithms, especially for the large-sized problems.