Mostly Inventory- rout planning is an important subject in distribution systems which considers the cost of routing and inventory in distribution networks and simultaneously evaluates inventory management and vehicle routing. In addition to consider the real world constrains, this issue helps the quality of answers enhanced and decision makers are provided with better results by modeling the problems in greater size. While traortation has a great roll in air pollution, governments are under pressure from environmental preservation organizations to reduce the portion of traortation in this issue. These challenges make governments impose a set of rules to reduce these adverse effects. These rules create some restrictions in traortation for small and big companies, causing a significant growth in traortation costs in case companies ignore these rules. One of the solution which presented to solved these constrains and reduce the costs of distribution is the use of the 2-echelon-inventory problem, Although the existence of two layers in this problem is very useful, this issue has been ignored in literature. This thesis is to propose a mathematical model to solve this problem. The objective of this research is to determine the customers that should be visited in each period, then find a set of routs in two layers in which all customers` demands and capacity restrictions are fulfilled, and finally minimize the total costs of distribution system. These decisions are made with considering customers’ demands, inventory costs for customers, the number of available vehicles and their related costs and capacities, the number of temporary inventory satellite, and the imposed restriction on vehicles` routs. Given that this problem is NP-hard, two metaheuristic algorithms, ALNS , VNS are used to solve this problem in large scale. To evaluate the performance of the algorithm, the results from the exact method in small scale are compared with the results from ALNS , VNS in large scale . The results show appropriated performance of proposed algorithm.
