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http://dx.doi.org/10.5762/KAIS.2011.12.7.2963

A Hybrid Artificial Neural Network and Genetic Algorithm based Cost Estimation Approach for Feature-based Plastic Injection Products  

Seo, Kwang-Kyu (Department of Management Engineering, Sangmyung University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.12, no.7, 2011 , pp. 2963-2968 More about this Journal
Abstract
Plastic injection products have been widely used in various electronic appliances and high-tech commodities. However, plastic injection product manufacturers have to spare no efforts to shorten new product development period to introduce new products into the market ahead of other competitors, gaining competitiveness and satisfying customers. The manufacturers cannot only get big target market share rapidly but also the advantage of leading the product price in order to survive in highly competitive market. This paper proposes the cost estimation approach of feature-based plastic injection products by using hybrid artificial neural network and genetic algorithm. The proposed method is to dramatically simplify and shorten the complex conventional cost estimation procedures and the requested computation parameters of plastic injection products. The case study demonstrates the efficiency and effectiveness of the proposed model in solving the cost estimation problem of plastic injection products at the development stage.
Keywords
Cost Estimation; Feature-based Model; Plastic Injection Product; Artificial Neural Network(ANN); Genetic Algorithm(GA); Hybrid Approach;
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