15th Triennial World Congress of the International Federation of Automatic Control
  Barcelona, 21–26 July 2002 
PRIMAL-DUAL GENETIC ALGORITHMS FOR ROYAL ROAD FUNCTIONS
Shengxiang Yang*
* Department of Mathematics and Computer Science
University of Leicester
University Road, Leicester, LE1 7RH, UK
s.yang@mcs.le.ac.uk http://www.mcs.le.ac.uk/~syang

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.
Keywords: Genetic algorithm, crossover, dominant, search, parallelism, optimization
Session slot T-Fr-M04: Genetic algorithms and Rule generation/Area code 3e : Fuzzy and Neural Systems