Application of a fuzzy ant colony system to solve the dynamic vehicle routing problem with uncertain service time

Service management has been an important issue for many companies, especially for service-based companies. This paper studies a routing problem that is usually faced by on-site service companies. This type of company continuously receives orders during its working hours. In order to maximize the number of customers served and minimize the customer waiting time, the service team is responsible for determining which orders should be served during the ongoing working period and which orders should be served in the following working period. This paper represents this problem as a dynamic vehicle routing problem (DVRP). The proposed DVRP model also considers the uncertain service time using fuzzy theory. Furthermore, an algorithm using an improved fuzzy ant colony system (ACS) is proposed in order to solve the proposed model. The proposed algorithm embeds a cluster insertion algorithm into the ACS algorithm. The proposed algorithm is validated using some benchmark datasets. The results show that the proposed algorithm performs better than the previous fuzzy-ACS algorithm without cluster insertion algorithm. In addition, further sensitivity analysis is also presented to derive more information about the model and the proposed algorithm for application to real-world problems.