Suitability factor on the Capacitated Vehicle Routing Problem

Finding a good solution for logistics and transportation industries is a continuous effort to maximize the efficiencies especially on problem that relates to the industry such as Vehicle Routing Problem (VRP). One of the most popular solutions is using Ant Colony System (ACS) algorithm. Several versions of ACOs have been proposed which aim to achieve an optimum solution. A new variant of algorithm called Dynamic Ant Colony System with Three Level Updates (DACS3) has been developed which focuses on adding individual ant behavior. It has been applied in Capacitated Vehicle Routing Problem (CVRP). Therefore, this research aims to improve its solution by applying elitist ant concept, rearrange its selection of candidates and to include current status of vehicle capacity as part of its decision making. The result shows that DACS3 has achieve a better solution for most of the datasets. Applying elitist concept, rearrangement of candidate selection and vehicle capacity as part of its decision making can influence its achievement to reach an optimal distance.