Ant based solver for dynamic vehicle routing problem with time windows and multiple priorities

Abstract

In this paper, we propose an ant based solver to solve dynamic vehicle routing problem with time windows and multiple priorities (DVRPTWMP). In this problem, a fleet of vehicles will service a number of customers with time windows. But part of customers are unknown and revealed dynamically during the execution of the routes. More specifically, customers have different priority levels. Customers with higher priority should have a higher quality of service. The quality of service is measured by the sum of the expected delay time between the arrival time and the earliest available beginning service time of all customers. The goal is to minimize the traveling distance while minimizing the total delay time of customers. First, a new benchmark is generated for DVRPTWMP based on van Veen's benchmark which is a dynamical extension of Solomon's 100 customers benchmark. Then, the ant based solver is introduced and two strategies based on ant colony algorithm are proposed to deal with priorities of customers. One is servicing high priority level customers immediately using the nearest vehicle. The other is giving a penalty to the delay time, combining the penalty and traveling distance and minimizing them together. Finally, the results show that the second strategy performs better than the first one.