Vehicle Routing Problem (VRP) plays a significant role in today’s demanding world, especially in Logistics, Disaster relief supplies or Emergency transportation, Courier services, ATM cash replenishment, School bus routing and so on and it acts as a central hub for distribution management. The objectives of the present research are to solve NP-Hard Multi-depot Vehicle Routing Problem (MDVRP) by using an enhanced firefly approach as well as to examine the efficiency of the proposed technique Cordeau benchmark dataset of MDVRP were used. The foremost principle of MDVRP is to optimize the cost of the solution, to minimize the overall vehicles, travelling distance and number of routes. MDVRP is constructed with two phase, assignment and routing. The firefly technique is enhanced by using inter depot, which is applied in assignment phase. In routing phase saving cost, intra and inter-route were used. The results were compared with Ant colony optimization (ACO), Genetic algorithm (GA), Intelligent water drops (IWD), Particle Swarm Optimization (PSO), Genetic cluster (GC), Genetic using Pareto Ranking (GAPR), Nomadic Genetic algorithm (NGA), and General Variable neighbourhood search (GVNS) algorithm. The solutions obtained in this research work found to be optimal for most of the benchmark instances
The Multiple Trip Vehicle Routing Problem with Backhauls: Formulation and a Two-Level Variable Neighbourhood Search