This paper aims at applying mathematical programming model to supply chain management in a fussy environment. It also critically examined the inventory, production and distribution activities in manufacturing organisation and the possibility of cost reduction in all segment of supply chain management. A linear programming model LINDO algorithm was used to determine the basic objective coefficient allowable decrease and optimum cost of inventory, production and transportation cost from plant to depots and from depots to various distributors of Five selected products of a multinational company. The finding revealed that for the company to optimally manage its resources, there is need for certain cost in Supply Chain to be reduced, the possible cost of reduction in each product was revealed, ranging from cost of inventory, production and transportation from plant to depots and transportation cost from depots to distributors. Also, quantity to transport from the plant to each depot and from depots to various distributors at a particular period of time under the study. The possibility of price increase in the future was also discovered and ranges in which the basis objective coefficient allowable decrease was critically analysed.
Mathematical Linear Programming Model, Supply Chain Management, Fuzzy Environment
