Abstract

This thesis presents the development of a multi-objective mixed linear programming model to design a material supply system for an ethanol manufacturing company. China has proposed a cassava development program to encourage cassava processing enterprises, mainly ethanol enterprises. These companies will build raw material production bases in mountain areas of Guang'xi province to help increase the revenues of local impoverished farmers. A cassava supply system responsible for raw material transportation from the farmers to the ethanol manufacturing plant is one of the essential strategies to ensure smooth operations of the company. The model is built to aid decision makers in selecting farmers for cassava supply and locating processing centers to serve farmers in order to construct the supply system. The locations of farmers and processing centers are determined to achieve the maximum poverty reduction and the minimum operation cost under the condition that cassava from all selected farmers meets the demand of the manufacturing plant. The maximum poverty reduction is accomplished by the largest poverty coverage and highest average income increase rate. The constraint method is applied to solve the model. The mathematical modeling formulation is coded in LINGO served by Excel data sheet. Trade-off solutions are presented to provide ample choices to decision makers on farmer selections and the processing center locations. The decision makers may choose to enlarge population coverage of the poor or increase their income increase rate, the cost will rise accordingly; or they may choose to reduce the cost with fewer covered poor farmers or with lower income increase rate.