Natural selection drives evolving populations up the fitness landscape, the projection from
nucleotide sequence space to organismal reproductive success. While it has long been …

Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that
explore the space of potential solutions by building and sampling explicit probabilistic …

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 …

This paper reviews and summarizes existing linkage learning techniques for genetic and
evolutionary algorithms in the literature. It first introduces the definition of linkage in both …

The effect of a mutation on the organism often depends on what other mutations are already
present in its genome. Geneticists refer to such mutational interactions as epistasis. Pairwise …

We consider the problem of finding an unknown graph by using two types of queries with an
additive property. Given a graph, an additive query asks the number of edges in a set of …

In pseudo-Boolean optimization, a variable interaction graph represents variables as
vertices, and interactions between pairs of variables as edges. In black-box optimization, the …

Estimation of Distribution Algorithms (EDAs) belong to the class of population based
optimisation algorithms. They are motivated by the idea of discovering and exploiting the …

We present an optimisation problem which seeks to locate the Pareto-optimal front of
building window and shading designs minimising two objectives: projected energy use of …

Surrogate-assisted evolutionary algorithms have the potential to be of high value for real-
world optimization problems when fitness evaluations are expensive, limiting the number of …