New product supply chain configuration with fuzzy parameters

We address how to configure the supply chain for a new product for which the design has already been decided. The central question is to determine what suppliers, parts, processes, and transportation modes to select at each stage in the supply chain. There might be multiple options to supply a raw material, to manufacture or assemble the product, and to transport the product to the customer. Each of these options is differentiated by its lead time, direct cost added and reliability etc. These parameters are fuzzy in nature. Given these various choices along the supply chain, the configuration problem is to select the options that minimize the total supply chain cost. A defuzzification method is proposed. Genetic Algorithm is used to solve the problem. We illustrate the problem and its solution with an industrial example.