A reactive tabu search metaheuristic for the vehicle routing problem with time windows

This article develops a reactive tabu search metaheuristic for the vehicle routing and scheduling problem with time window constraints. Reactive tabu search dynamically varies the size of the list of forbidden moves to avoid cycles as well as an overly constrained search path. Intensification and diversification strategies are examined as ways to achieve higher quality solutions. The λ-interchange mechanism of Osman is used as the neighborhood structure for the search process. Computational results on test problems from the literature as well as large-scale real-world problems are reported. The metaheuristic achieves solutions that compare favorably with previously reported results.