Using an immune system model to explore mate selection in genetic algorithms.
- Chien-Feng
In the setting of multimodal function optimization, engineering and machine learning, identifying multiple peaks and maintaining subpopulations of the search space are two central themes when Genetic Algorithms (GAs) are employed. In this paper, an immune system model is adopted to develop a framework for exploring the role of mate selection in GAs with respect to these two issues. The experimental results reported in the paper will shed more light into how mate selection schemes compare to traditional selection schemes. In particular, we show that dissimilar mating is beneficial in identifying multiple peaks, yet harmful in maintaining subpopulations of the search space.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE
- OSTI ID:
- 976523
- Report Number(s):
- LA-UR-03-0534; TRN: US201017%%671
- Resource Relation:
- Journal Volume: 2723; Conference: Submitted to: Genetic and Evolutionary Computation Conference, (GECCO), Chicago, July 12-16, 2003
- Country of Publication:
- United States
- Language:
- English
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