Efficiency Enhancement of Genetic Algorithms via Building-Block-Wise Fitness Estimation
<|reference_start|>Efficiency Enhancement of Genetic Algorithms via Building-Block-Wise Fitness Estimation: This paper studies fitness inheritance as an efficiency enhancement technique for a class of competent genetic algorithms called estimation distribution algorithms. Probabilistic models of important sub-solutions are developed to estimate the fitness of a proportion of individuals in the population, thereby avoiding computationally expensive function evaluations. The effect of fitness inheritance on the convergence time and population sizing are modeled and the speed-up obtained through inheritance is predicted. The results show that a fitness-inheritance mechanism which utilizes information on building-block fitnesses provides significant efficiency enhancement. For additively separable problems, fitness inheritance reduces the number of function evaluations to about half and yields a speed-up of about 1.75--2.25.<|reference_end|>
@article{sastry2004efficiency,
    title={Efficiency Enhancement of Genetic Algorithms via Building-Block-Wise
  Fitness Estimation},
    author={Kumara Sastry, Martin Pelikan, David E. Goldberg},
    journal={arXiv preprint arXiv:cs/0405065},
    year={2004},
    doi={10.1109/CEC.2004.1330930},
    number={IlliGAL Report No. 2004010},
    archivePrefix={arXiv},
    eprint={cs/0405065},
    primaryClass={cs.NE}
}