The use of explicit building blocks in evolutionary computation

DOI10.1080/00207721.2014.901580zbMath1333.90155OpenAlexW2074959648MaRDI QIDQ2795172

Chalermsub Sangkavichitr, Prabhas Chongstitvatana

Publication date: 18 March 2016

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2014.901580

zbMATH Keywords

genetic algorithmestimation of distribution algorithmlinkagebuilding blockmulti-parent recombination

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59)

Cites Work

• Unnamed Item
• Unnamed Item
• Hierarchical Bayesian optimization algorithm. Toward a new generation of evolutionary algorithms. With a foreword by David E. Goldberg
• Parameter setting in evolutionary algorithms.
• Scalable optimization via probabilistic modeling. From algorithms to applications.
• Extending the scalability of linkage learning genetic algorithms. Theory \& practice.
• Foundations of global genetic optimization. With contribution by Henryk Telega.
• Linkage Learning in Estimation of Distribution Algorithms
• Application of genetic algorithms to robot kinematics calibration
• Introduction to Evolutionary Algorithms
• Introduction to Genetic Algorithms
• A survey of optimization by building and using probabilistic models

This page was built for publication: The use of explicit building blocks in evolutionary computation