A New Capacitated Vehicle Routing Problem with Split Service for Minimizing Fleet Cost by Simulated Annealing

We address a capacitated vehicle routing problem (CVRP) in which the demand of a node can be split on several vehicles celled split services by assuming heterogeneous fixed fleet. The objective is to minimize the fleet cost and total distance traveled. The fleet cost is dependent on the number of vehicles used and the total unused capacity. In most practical cases, especially in urban transportation, several vehicles transiting on a demand point occurs. Thus, the split services can aid to minimize the number of used vehicles by maximizing the capacity utilization. This paper presents a mix-integer linear model of a CVRP with split services and heterogeneous fleet. This model is then solved by using a simulated annealing (SA) method. Our analysis suggests that the proposed model enables users to establish routes to serve all given customers using the minimum number of vehicles and maximum capacity. Our proposed method can also find very good solutions in a reasonable amount of time. To illustrate these solutions further, a number of test problems in small and large sizes are solved and computational results are reported in the paper.