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Issue title: FUZZYSS’2009
Article type: Research Article
Authors: Özdemir, R.G. | Çiçek, B. | Özenç, D.
Affiliations: Istanbul Kültür University, Faculty of Engineering and Architecture, Department of Industrial Engineering, Yanyol, Bakirkoy, Istanbul, Turkey
Note: [] Corresponding author. Dr. Rifat Gürcan Özdemir, Istanbul Kültür University, Faculty of Engineering and Architecture, Department of Industrial Engineering, Atakoy Campus, D-100 Yanyol, Bakirkoy, Istanbul, Turkey. Tel.: +90 212 4984238; E-mail: [email protected]
Abstract: This paper deals with the problem of multi objective new product development and its solution with an intelligent approach. The proposed approach uses fuzzy parameters for economic analysis and combines a multi-criteria decision making method to goal programming. In economic analysis, fuzzy life cycle costs and fuzzy life cycle pricing are considered with respect to demand changes during life cycle of new product alternatives. Fuzzy equivalent worth of each new product alternative is determined using fuzzy life cycle monetary input, and results are input to the multi-criteria analysis. The selected multi-criteria analysis tool is TOPSIS in the paper and some additional judgmental criteria are also considered to rank new product alternatives. The preference weights used to rank alternatives are then fed to a goal programming model which makes an ultimate selection of new product(s) to be produced in the manufacturing system under capacity, sales potential, and workforce balance constraints. The goal programming model has an objective of minimizing the weighted sum of positive deviation from target total cost and negative deviation from target total preference weights. The proposed approach is then implemented using real data of a continuous production system for the need of introducing new products into market.
Keywords: Fuzzy life-cycle-cost parameters, multi objective decision making, goal programming, new product development
DOI: 10.3233/IFS-2010-0463
Journal: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 5, pp. 303-316, 2010
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