作者: Simon Fischer , Ingo Wegener
DOI: 10.1016/J.TCS.2005.04.002
关键词: Algorithm 、 Mathematics 、 Genetic algorithm 、 Local search (optimization) 、 Crossover 、 Statistical physics 、 Ising model 、 Periodic boundary conditions 、 Evolutionary algorithm 、 Mutation (genetic algorithm) 、 Boundary value problem
摘要: The investigation of genetic and evolutionary algorithms on Ising model problems gives much insight into how these work as adaptation schemes. one-dimensional with periodic boundary conditions has been considered a typical example clear building block structure suited well for two-point crossover. It claimed that GAs based recombination appropriate diversity-preserving methods by far outperform EAs mutation only. Here, rigorous analysis the expected optimization time proves mutation-based are surprisingly effective. (1 +λ) EA an λ-value is almost efficient GAs. Moreover, it proved specialized do even better this holds crossover one-point