The Open Vehicle Routing Problem (OVRP) is one of the most intensively studied problems in operation research that nowadays, it has received much attention by researchers and scientists. In this Problem, the objective is to define minimized distance traveled of the several vehicles that start to move simultaneously from the depot and visit some customers. It is noted that against to the Vehicle Routing Problem (VRP), it is not necessary that vehicles return to the depot after servicing the customers. In this paper, a new linear programming model and an effective metaheuristic algorithm called EACO are proposed for solving OVRP in which the main idea is based on the ant colony optimization (ACO). Furthermore, the insert and swap local search algorithms are used for finding better solutions. Some numerical examples are presented to illustrate the effectiveness of the proposed algorithm and finally the efficiency of the proposed metaheuristic algorithm is compared to the other algorithms. The algorithm was tested in a set of instances including 15 benchmark problems with 50-480 customers and it was found capable of obtaining the best known results of %80 instances. In terms of quality of the solutions, the proposed algorithm has proven to be highly competitive and gives better results compared to the existing solution methods for OVRP in term of the solution quality
