A heuristic genetic algorithm for product portfolio planning

Author

Jiao, Jianxin ; Zhang, Yiyang

Author_Institution

Sch. of Mech. & Production Eng., Nanyang Technol. Univ., Singapore

Volume

1

fYear

2004

fDate

1-3 Dec. 2004

Firstpage

614

Abstract

For any manufacturing company, product portfolio planning constitutes one of the most important decisions regarding how to offer the "right" products to the target market. Essentially, such decisions exhibit a typical combinatorial optimization problem, which deems to be very complex and hard to solve using conventional optimization techniques. Enumeration is inhibitive if the problem size is extremely large. Genetic algorithms (GAs) have been proven to excel in solving combinatorial optimization problems. This paper develops a heuristic GA to tackle the product portfolio planning problem.

Keywords

decision making; genetic algorithms; heuristic programming; manufacturing industries; problem solving; product development; production planning; GA; combinatorial optimization problem; heuristic genetic algorithm; manufacturing company; product portfolio planning; Content addressable storage; Costs; Evolutionary computation; Genetic algorithms; Manufacturing; Optimized production technology; Portfolios; Production engineering; Production planning; Technology planning;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetics and Intelligent Systems, 2004 IEEE Conference on

Print_ISBN

0-7803-8643-4

Type

conf

DOI

10.1109/ICCIS.2004.1460486

Filename

1460486