1999/11/04 by Christopher Ronnewinkel, Ronnewinkel, Christopher, Claus O. Wilke +3
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Adaptation and Self-Organizing Systems (nlin.AO) #Biological Physics (physics.bio-ph) #Evolutionary Algorithms and Applications #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Physical sciences #Metaheuristic Optimization Algorithms Research #Neural and Evolutionary Computing (cs.NE) #Quantitative Biology (q-bio) #adap-org #cs.NE #nlin.AO #physics.bio-ph #q-bio
paper · pdf · doi:10.48550/arxiv.physics/9911006
24 pages, 14 figures, submitted to the 2nd EvoNet Summerschool
arxiv created 1999/11/04 · openalex publication_date 1999/11/04 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The influence of time-dependent fitnesses on the infinite population dynamics of simple genetic algorithms (without crossover) is analyzed. Based on general arguments, a schematic phase diagram is constructed that allows one to characterize the asymptotic states in dependence on the mutation rate and the time scale of changes. Furthermore, the notion of regular changes is raised for which the population can be shown to converge towards a generalized quasispecies. Based on this, error thresholds and an optimal mutation rate are approximately calculated for a generational genetic algorithm with a moving needle-in-the-haystack landscape. The so found phase diagram is fully consistent with our general considerations.