A hybrid intelligent algorithm for the vehicle scheduling problems with time windows

Abstract

Vehicle routing problems (VRP) emerge in large numbers within the real-world transportation and logistics applications. Vehicle routing problem with time windows (VRPTW) is an NP-hard problem. A mathematical model is built up with the objective of minimum route distances based on the analysis. A hybrid intelligent algorithm based on the max-min ant colony algorithm and a genetic algorithm is put forward to solve it. First, it gains the local optimization solution through ant colony algorithm. Then it makes use of the genetic algorithm to reserve some elitist genetic sense units for gaining a global optimization solution. The computational results show that the improved ant colony optimization method has high optimization efficiency than that of a single algorithm. It can solve the vehicle routing problem with time windows and fixed demand effectively.