Intelligent Genetic Algorithms in Evolutionary Computation Part 1. Biological Foundation
Liwen He, Neil Mort · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 1998
In this paper, we review a large amount of historical biological literature [Darwin, 1862, 1871; Fisher, 1930 and others] and recent developments in biological [ Anderson, 1994] and biocomputational literature [Miller & Todd, 1992, 1994], try to integrate the dynamics of interplay between natural selection and sexual selection through mate choice in biology with evolutionary computation as a process of search, diversification and optimization and originate a new class of evolutionary algorithm which we term Intelligent Genetic Algorithms. These intelligent genetic algorithms demonstrate their effectiveness and efficiency in generating evolutionary innovations, maintaining genetic diversity, promoting mate choice and sexual recombination in species and guiding the movement of a population from local optima to global optima in parallel. Furthermore, we attempt to provide some common biological origins for these new Intelligent Genetic Algorithms.