Solving generalized vehicle routing problem by parallel universes and Tabu search

Vehicle routing problem (VRP) is one of the most important transportation problems in such a way that most of the transportation problems are changeable to it. This problem can be considerably effective in transportation and the costs arising from it. The VRP with some constraints and limitations become closer to the actual world. The generalized problem of VRP is in a state that should select agents among the customers so that the problem to be solved in a more generalized form. In this paper, we have tried to improve the answers on generalized vehicle routing transportation problems (GVRP) and obtain a better result in implementation, using the combination of parallel universes´ algorithms in addition to the Tabu search. Our results indicate that our method has been productive successful and we have achieved better answers compared to the similar algorithms presented until now, in this context.