This research addresses the development of integrated inventory lot-sizing and supplier selection problem in supply chain management, in which a buyer firm that has limited budget and warehouse space wants to procure multiple products from a group of potential suppliers and sell to their customer. In particular, the suppliers may provide different quantity discount scheme, ordering cost, and transportation cost. The problem is modelled as mixed integer linear programming (MILP) by incorporating quantity discount. To overcome the large scale problem, Genetic Algorithm (GA) is developed in next phase. The comparison was conducted on both MILP and GA. The results showed that GA has better performance in term of solution feasibility and computational time.