  The vehicle routing problem has great importance and application in
transportation and supply chain management. In this case, there are several
supply requests in a transportation network. The main goal is to allocate
customers to available vehicles and find the sequence of customer visits on
each route. It is possible to attack the arcs of the network when two actors
compete against each other with conflicting goals. In this case, the attacker
may destroy the network arcs or prevent the supply of customers. The defender
also intends to fulfill customer demand with the least cost and the most
success rate. To this end, we define the robust vehicle routing problem in the
presence of a proactive attacker. In this research, we propose a mathematical
model with two objective functions to minimize total cost and maximize the
total success rate in fulfilling the demand. Also, an exact algorithm for
generating feasible routes has been used to solve small-scale problems. To
solve large-scale problems, a simulated annealing algorithm is used. We test
one numerical example problem and six medium and large size problems to
evaluate the proposed algorithms' efficiency. The results demonstrate that the
total success rate in supply is directly related to the amount of cost;
crossing shorter routes decrease the total of success rate.
