An Improved Ant Colony Algorithm for the Logistics Vehicle Scheduling Problem

The logistics vehicle scheduling problem is a widely existent problem in distribution. In fact, it is the vehicle routing problem with time window. In the vehicle routing problem with time windows (VRPTW), there are two main objectives. The primary objective is to reduce the number of vehicles, the secondary one is to minimize the total distance travelled by all vehicles. This is an NP-complete optimization problem. Ant colony system which is a novel simulated evolutionary algorithm, it can good for NP-hard problem. According to the features of the Vehicle routing problem with time windows and the ant colony algorithm, an improved ant colony system is proposed to solve this problem. It possesses a new state transition rule, a new pheromone updating rule and diverse local search approaches. Finally, Solomon´s benchmark instances (VRPTW 100-customer) are tested for the algorithm and shows that the improve ant colony is able to find solutions for VRPTW.