This study is about a multi item inventory control model which is developed to optimize the total inventory cost and inventory layout management. Prioritizing environmental pollution as an integral part of inventory management, equivalent carbon emission cost is also considered in the proposed inventory control model. Assuming limited number of orders where no shortage is allowed, the raw material inventory control model is designed. The objective of this study is to minimize the inventory cost by determining economic order quantity (EOQ) and to minimize the use of storage space for the inventory. In order to solve the nonlinear programming model, a metaheuristic algorithm named multi-objective particle swarm optimization (MOPSO) algorithm is proposed.