A Hybrid Particle Swarm Optimization – Travelling Salesman Problem for Efficient Multi Depot Vehicle Routing

The Fast-Moving Consumer Goods (FMCG) industry faces increasing demand to optimize distribution networks to reduce costs. The company seeks to establish a proper redistribution route network, optimize truck allocation, and minimize warehouse operations, administration, and transportation costs while adhering to capacity and volume constraints. To achieve this, the study formulates the problem as a Multi -Depot Vehicle Routing Problem (MDVRP) with 3 depots. The proposed model with the addition of a particle swarm algorithm yields a substantial cost reduction of 21.41% compared to the existing system, demonstrating the potential of hybrid metaheuristic algorithms for addressing complex logistics challenges in the FMCG industry. Keywords: Multi -depot vehicle routing problem; K-Means Clustering; Gravity model; Particle Swarm Optimization; Travelling Salesman Problem