Solving Dynamic Vehicle Routing Problem with Pickup and Delivery by CLARITY Method

Abstract

Dynamic Vehicle Routing Problem (DVRP), which is classified as a family of dynamic optimization problems, has come to light from the daily line of works. On the other hand, several applications of routing problems are subject to dynamic environments, such as cases that afresh orders gradually applied through the servicing of vehicles and would take into the available routing plan of vehicles. This common daily issue with many other similar cases are subject to DVRP, which is aims to planning the route of a number of vehicles for servicing demands like as Vehicle Routing Problem (VRP), but in a dynamic environment of customer queries. Even though, most of classical literatures on VRP, studied the static case that the entire data before implementing the routing algorithm have been known. In this study, the CLARITY (Clustering, eLbow-method, polAR-routing, InTeger-programing and evolutionarY) method for solving VRP, DVRP and one of the most widely used type of VRP as DVRP with Pickup and Delivery (DVRPD) has been suggested. The experiments on this main extension of VRP come to account for demonstrating high capability of our proposed method. The experimental efforts of CLARITY method have been compared with the results of standard benchmarks. In overall, computational results show that the CLARITY is competitive in comparison to state of the art methods.