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A Knowledge-Based System for New Product Portfolio Selection

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New Frontiers in Information and Production Systems Modelling and Analysis

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 98))

Abstract

This chapter is concerned with designing and developing a knowledge-based system for evaluating concepts of new products and selecting product portfolio. The model of measuring the product success includes metrics identified by an expert, such as duration and cost of product development or net profit from a product. The model contains a set of decision variables, their domains, and the constraints that can be described in terms of a constraint satisfaction problem (CSP). Knowledge base is specified according to CSP framework and it reflects the company’s resources, performance metrics, and relationships identified. The presented knowledge discovery process consists of the stages such as data selection, data preprocessing, and data mining in the context of an enterprise system database. In order to identify the patterns, fuzzy neural networks have been used and compared with the results from artificial neural networks and linear regression. The illustrative example presents the use of fuzzy neural networks to the identification of patterns that are translated into rules understandable by users. The proposed knowledge-based system helps the managers in selecting the most promising product portfolio and reducing the risk of unsuccessful product development.

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Authors and Affiliations

  1. Faculty of Economics and Management, University of Zielona Gora, Zielona Gora, Poland

    Marcin Relich

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  1. Marcin Relich
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Correspondence to Marcin Relich .

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Editors and Affiliations

  1. Faculty of Computer Science and Information Systems, West Pomeranian University of Technology in Szczecin, Szczecin, Poland

    Przemysław Różewski

  2. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia

    Dmitry Novikov

  3. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia

    Natalia Bakhtadze

  4. Warsaw School of Computer Science, Warszawa, Poland

    Oleg Zaikin

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Relich, M. (2016). A Knowledge-Based System for New Product Portfolio Selection. In: Różewski, P., Novikov, D., Bakhtadze, N., Zaikin, O. (eds) New Frontiers in Information and Production Systems Modelling and Analysis. Intelligent Systems Reference Library, vol 98. Springer, Cham. https://doi.org/10.1007/978-3-319-23338-3_8

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  • DOI: https://doi.org/10.1007/978-3-319-23338-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23337-6

  • Online ISBN: 978-3-319-23338-3

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