Simulation-Based Allocation and Routing Optimization: A Case Study of Single Versus Team Driving

Planning vehicle routes in supply chain management is a challenging problem since all demands need to be met at the minimum cost with various limitations on available resources. This study tries to find the optimal routes for multi-type vehicles based on information provided by a real-world supply chain dataset, which includes the delivery information of eleven vehicles with both single-type and team-type drivers. To achieve this, this paper also simulates routes and re-allocates delivery locations to different vehicles by the particle swarm optimization (PSO) algorithm and optimizes the routes within the newly allocated delivery locations. Experimental results show that this simulation-based approach improves the routes in terms of overall cost and distance for the deliveries in comparison with the original routes that have been operated. This study also evaluates the necessity of having additional drivers in a cost-effective manner. The optimal newly-assigned routes could help minimize the logistical costs of the company and efficiently manage its supply delivery network.