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Cost estimation is one of the influencial requirements for the current manufacturers when new products are introduced. This paper aims to propose a decision support system (DSS) that retrieves historical cases/products, which have the most similar cost estimates to the current case. This helps users to estimate the costs of new products at early stages of product development. The proposed DSS combines case-based reasoning (CBR), the analytic hierarchy process (AHP) and fuzzy set theory. Cases are represented using an object-oriented (OO) approach to characterize them in n-dimensional Euclidean vector space. A numerical example is illustrated to show the applicability of the proposed DSS.
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