MODELLING & SOLVING THE VEHICLE ROUTING PROBLEM IN DISTRIBUTION OF A SUPPLY CHAIN CONSIDERING RESTRICTION ON THE MOVEMENT OF THE VEHICLES

Since precise assignment of vehicles to the routs in supply chain network has a great eect on the important results such as cost reduction, on time delivery of the products or services, and customer satisfaction indexes (CSI), the Vehicle Routing Problem (VRP) is one of the most important problems in the supply chain management. For the complexity of this problem in real world, researchers usually ignore some real conditions and restriction in modelling and solving this problem. In this paper, the Vehicle Routing Problem (VRP) considering real conditions, such as vehicle capacity and restriction for vehicles with their movement in some routes, is studied. At rst, the literature review and past studies are presented. Then, the considered problem will be illustrated completely and its parameters and variables will be dened. After that, the mathematical model of the problem is presented considering restriction for movement of the vehicles. This mathematical model will be codedinGAMSsoftware; becausethisproblemisknown as an NP-Hard problem, the mathematical model of the problem is solved just for the small-sized problems. A new model is also presented for the medium- and largesized problems based on ant colony (AC). The parameters of the ant colony are adjusted well in order to increase the eciency of the algorithm. Finally, some diversity test problems are designed considering the important and eective parameters. These test problems are solved in order to evaluate the eciency of the proposed algorithm, and the result shows that the proposed algorithm has a good performance in solving the test problems. Performanceoftheproposedalgorithmisalso compared with two power algorithms tabou search (TA) and genetic algorithm (GA) in solving the test problems. Results show that the proposed algorithm has better performance both in optimality and running time comparison of two other algorithms.