Optimization of Supply Chain Management Based on Response Surface Methodology: A Case Study of Iran Khodro

This research aims at optimizing the production and transportation scheduling components at an automotive company. In particular, the transportation time, cost, as well as the capacity constraint constitute elements of vital significance in the decision making process. As found in a research conducted in Iran’s management and planning organization, an estimated 30% of all price increases was as a result of costs associated with transportation of products form from source to destination, depicting the component with the largest effect on price. Furthermore, despite the fact that the fundamental reason for planning is to ascertain the required production quantity needed in the future; there exist no more accurate model currently that has the required capability to predict production quantity of IKCO equipment. The objective of this study is to minimize the costs associated with delay of orders, the number vehicles used in the transportation, fuel as well as labor cost. Here, the employed analysis method is the multiple regression which uses response surface quadratic methodology analysis in order. These allow for the localization of the optimal region of response variables under study in this research; and also, to further generate the relationship between the four independent variables and the two response variables under test.