An immune-genetic algorithm for introduction planning of new products

Authors:
Dingwei Wang;Richard Y. K. Fung;W. H. Ip
Affiliations:
Institute of Systems Engineering, Northeastern University, Shenyang 110004, China;Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong;Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong
Venue:
Computers and Industrial Engineering
Year:
2009

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Abstract

The introduction planning problem of new products can be described as a semi-infinite programming model with infinite constraints. To solve complex constrained optimization problems, a new immune-genetic algorithm is proposed in this paper. In this approach, first of all, some antigens are randomly generated for the production and training of antibodies. Then, an efficient immune system with the capability to recognize self- and non-self-antigens is supported by these trained antibodies. The resulting immune system is built into genetic algorithms, and they can be used to identify and repair the illegal and infeasible chromosomes during the genetic iterations. The recommended algorithm can improve the performance of genetic algorithms particularly in complex constrained optimization problems. It has been achieved satisfactory results from the new product introduction problems.