A Review on Estimation of Distribution Algorithms: 3
P Larranaga - Estimation of distribution algorithms: a new tool for …, 2002 - Springer
In this chapter, we review the Estimation of Distribution Algorithms proposed for the solution
of combinatorial optimization problems and optimization in continuous domains. Different …
of combinatorial optimization problems and optimization in continuous domains. Different …
A review of estimation of distribution algorithms in bioinformatics
Evolutionary search algorithms have become an essential asset in the algorithmic toolbox
for solving high-dimensional optimization problems in across a broad range of …
for solving high-dimensional optimization problems in across a broad range of …
[图书][B] Introduction to evolutionary computing
This is the second edition of our 2003 book. It is primarily a book for lecturers and graduate
and undergraduate students. To this group the book offers a thorough introduction to …
and undergraduate students. To this group the book offers a thorough introduction to …
An introduction and survey of estimation of distribution algorithms
M Hauschild, M Pelikan - Swarm and evolutionary computation, 2011 - Elsevier
Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that
explore the space of potential solutions by building and sampling explicit probabilistic …
explore the space of potential solutions by building and sampling explicit probabilistic …
Genetic algorithms
K Sastry, D Goldberg, G Kendall - Search methodologies: Introductory …, 2005 - Springer
Chapter 4 GENETIC ALGORITHMS Page 1 Chapter 4 GENETIC ALGORITHMS Kumara Sastry,
David Goldberg University of Illinois, USA Graham Kendall University of Nottingham, UK 4.1 …
David Goldberg University of Illinois, USA Graham Kendall University of Nottingham, UK 4.1 …
Bayesian networks for interpretable machine learning and optimization
As artificial intelligence is being increasingly used for high-stakes applications, it is
becoming more and more important that the models used be interpretable. Bayesian …
becoming more and more important that the models used be interpretable. Bayesian …
A survey of optimization by building and using probabilistic models
This paper summarizes the research on population-based probabilistic search algorithms
based on modeling promising solutions by estimating their probability distribution and using …
based on modeling promising solutions by estimating their probability distribution and using …
[图书][B] Hierarchical Bayesian optimization algorithm
M Pelikan, M Pelikan - 2005 - Springer
The previous chapter has discussed how hierarchy can be used to reduce problem
complexity in black-box optimization. Additionally, the chapter has identified the three …
complexity in black-box optimization. Additionally, the chapter has identified the three …
[图书][B] Bayesian optimization algorithm: From single level to hierarchy
M Pelikan - 2002 - search.proquest.com
There are four primary goals of this dissertation. First, design a competent optimization
algorithm capable of learning and exploiting appropriate problem decomposition by …
algorithm capable of learning and exploiting appropriate problem decomposition by …
Escaping hierarchical traps with competent genetic algorithms
M Pelikan, DE Goldberg - Proceedings of the 3rd Annual Conference on …, 2001 - dl.acm.org
To solve hierarchical problems, one must be able to learn the linkage, represent partial
solutions efficiently, and assure effective niching. We propose the hierarchical Bayesian …
solutions efficiently, and assure effective niching. We propose the hierarchical Bayesian …