More than a decade after the first extensive overview on parameter control, we revisit the
field and present a survey of the state-of-the-art. We briefly summarize the development of …

The field of metaheuristics for the application to combinatorial optimization problems is a
rapidly growing field of research. This is due to the importance of combinatorial optimization …

Since cooling and heating loads are regarded as significant parameters to examine the
energy performance of buildings, the need to predict and analyze them for the residential …

Traditional books on machine learning can be divided into two groups-those aimed at
advanced undergraduates or early postgraduates with reasonable mathematical knowledge …

A unified view of metaheuristics This book provides a complete background on
metaheuristics and shows readers how to design and implement efficient algorithms to solve …

Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving
systems with sophisticated collective intelligence. Composed of simple interacting agents …

Swarm intelligence is a relatively new approach to problem solving that takes inspiration
from the social behaviors of insects and of other animals. In particular, ants have inspired a …

This paper introduces the ant colony system (ACS), a distributed algorithm that is applied to
the traveling salesman problem (TSP). In the ACS, a set of cooperating agents called ants …

This article presents an overview of recent work on ant algorithms, that is, algorithms for
discrete optimization that took inspiration from the observation of ant colonies' foraging …

Derived from the concept of self-adaptation in evolution strategies, the CMA (Covariance
Matrix Adaptation) adapts the covariance matrix of a multi-variate normal search distribution …