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Abstract
Configuring a supply chain for new products involves selecting how to source each stage in the supply chain given several alternatives that vary in cost, lead time, and other measures. One must also determine the best overall strategy for deploying safety stocks across the supply chain so as to buffer against demand uncertainty. Traditionally, this has been done based on costs (inventory cost, procurement cost, or a combination of both). This article introduces the use of a multi-objective optimisation model in configuring the supply chain during product development. In addition to using various production and inventory costs, the model makes use of subjective criteria such as alignment of business practices and financial objectives of member companies in configuring the supply chain. Fuzzy logic is used to analyse the subjective or qualitative variables, such as alignment of business cultures and practices. A genetic algorithm is used to solve the optimisation model. A bulldozer case study is then presented to benchmark and demonstrate the benefits of the proposed methodology.
