An Improved Ant Colony Algorithm for VRPTW

The vehicle routing problem with time windows (VRPTW) is a well-known and complex combinatorial problem. The primary objective of VRPTW is defined as the minimization of the number of routes or vehicles. Minimization of the total travel cost is secondary objective. This paper proposes an improved algorithm based on the ant colony system (ACS), which hybridized with randomized algorithm (RACS-VRPTW). In two objectives of VRPTW, only partial customers are randomly chosen to compute the transition probability. Experiments on various aspects of the algorithm and computational results for partial benchmark problems are reported. We compare our approach with some other meta-heuristics and show that our results are competitive.