An ant colony optimization model: The period vehicle routing problem with time windows

This paper proposes an improved ant colony optimization (IACO) to solve period vehicle routing problem with time windows (PVRPTW), in which the planning period is extended to several days and each customer must be served within a specified time window. Multi-dimension pheromone matrix is used to accumulate heuristic information on different days. Two-crossover operations are introduced to improve the performance of the algorithm. The effectiveness of IACO is evaluated using a set of well-known benchmarks. Some of the results are better than the best-known solutions. Results also show the IACO seems to be a powerful tool for PVRPTW.