Globalization of economy leads to create new markets for all industries and increases competitive pressures in this field. The main goal of any companies is trying to fulfill the needs of their customers without a lot of waiting time. In the recent decade, attention to customer service has increased. The assemble-to-order (ATO) strategy requires that the basic parts are produced in advance. Products are manufactured once the order has been received. Use common component in an ATO system will increase the variety of products and increase service levels. In this study, Economic Production Quantity with common component problem in ATO environment is investigated. This is a two-stage problem. On the first stage before realizing the amount of demand and by service level concept the ordering decision of each component are made. On the second stage due to the sharing of parts between products, in every period after realizing demands, should decide about how to allocate the common component to products when component shortages occur. In order to obtain an optimal policy for allocating components to finished products two cases for entering demand to system is investigated. In the first case the demands for all goods interred simultaneously into the system. The three policies: solving second stage linear programming, ascending order of demands and fair allocation policy for allocating component to product were compared by means of simulation and statistical analyzes. The best policy based on maximize the profit of the second stage problem is solving second stage linear programming. In the case it is assumed that the demands for final products is dynamic and enter during period. In this case, two policies first stage share and order entry demand for components allocation to final products were investigated. According to the results, has not significant different. Because the model have zero-one variables, the possibility of solving a large scale at the reasonable time is not possible. In order to obtain a near-optimal solution in a reasonable time, heuristic methods are used to solve the problem. All heuristic approaches response in a reasonable time with less than one percent away from the optimal solution.
