An integrated approach for supply-production planning in a supply chain

Many firms try to optimize their supply and production levels separately, but this method could limit influence profitability, negatively. Thus, it is becoming more important to analyze these two levels, simultaneously. In this paper, an integrated supply-production planning is considered, simultaneously. We develop a mathematical model, which calculates the optimal inventory lot sizing for each supplier and minimizes the total cost associated with the process of procuring raw material, transferring and holding raw materials and manufacturing. The problem is formulated as a nonlinear programming and heuristic genetic algorithm (GA) method is developed to solve the resulted problem. We examine the performance of the proposed model for a case study conducted in Iran. Experimental results show that such a model can reduce the costs of the case study, substantially.