Background: The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Oth...
Yvan Saeys, Sven Degroeve, Dirk Aeyels, Pierre Rou...
Abstract: While code division multiple access (CDMA) is becoming a promising cellular communication system, the design for a CDMA cellular system configuration has posed a practica...
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...
In the sub-micron technology era, wire delays are becoming much more important than gate delays, making it particularly attractive to go for clustered designs. A common form of cl...
Estimation of Distribution Algorithms (EDAs) are new promising methods in the field of genetic and evolutionary algorithms. In the case of conventional Genetic and Evolutionary Al...
Genetic Programming (GP) provides evolutionary methods for problems with tree representations. A recent development in Genetic Algorithms (GAs) has led to principled algorithms cal...
Estimation of distribution algorithms (EDA) are similar to genetic algorithms except that they replace crossover and mutation with sampling from an estimated probability distributi...
Alden H. Wright, Riccardo Poli, Christopher R. Ste...
A new approach based on Estimation Distribution Algorithms for constrained multiobjective shape optimization is proposed in this article. Pareto dominance and feasibility rules ar...