Primal-dual genetic algorithms for royal road functions
Based on Holland's simple genetic algorithm (SGA) there have been many variations developed. Inspired by the phenomenon of diploid genotype and dominance mechanisms broadly existing in nature, we have proposed a primal-dual genetic algorithm (PDGA), see (Yang 2002). Our preliminary experiments based on the Royal Road functions have shown that PDGA outperforms SGA for different performance measures. In this paper we present some further experiment results, especially on the dynamic performance of PDGA over SGA, and give out our explanations and analyses about why PDGA outperforms SGA based on these results. Through the primal-dual mapping between a pair of chromosomes, PDGA's performance of exploration in the search space, especially during the early generations, is improved and thus its total searching efficiency is improved.
Citation : Yang, S. (2002) Primal-dual genetic algorithms for royal road functions. In: E. F. Camacho, L. Basanez, J. A. de la Puente (editors), Proceedings of the 15th IFAC World Congress, Vol. I: Fuzzy, Neural and Genetic Systems, pp. 373-378, Barcelona, Spain, 21-26 July 2002.
Research Group : Centre for Computational Intelligence
Research Institute : Institute of Artificial Intelligence (IAI)
Peer Reviewed : Yes