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Heuristic Genetic Algorithm for Product Portfolio Planning
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Author(s): Jianxin Jiao (Nanyang Technological University, Singapore), Yiyang Zhang (Nanyang Technological University, Singapore)and Yi Wang (Nanyang Technological University, Singapore)
Copyright: 2006
Pages: 16
Source title:
Business Applications and Computational Intelligence
Source Author(s)/Editor(s): Kevin Voges (University of Canterbury, New Zealand)and Nigel Pope (Griffith University, Australia)
DOI: 10.4018/978-1-59140-702-7.ch004
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Abstract
This chapter applies the Genetic Algorithm to help manufacturing companies plan their product portfolio. Product portfolio planning (PPP) is a critical decision faced by companies across industries and is very important in helping manufacturing companies keep their competitive advantage. PPP has been classified as a combinatorial optimization problem, in that each company strives for the optimality of its product offerings through various combinations of products and/or attribute levels. Towards this end, this chapter develops a heuristic genetic algorithm (HGA) for solving the PPP problem. The objective of this chapter is to develop a practical method that can find near optimal solutions and assist marketing managers in product portfolio decision-making.
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