Genetic algorithm (GA) is an artificial intelligence search method that uses the process of
evolution and natural selection theory and is under the umbrella of evolutionary computing …

“Exploration and exploitation are the two cornerstones of problem solving by search.” For
more than a decade, Eiben and Schippers' advocacy for balancing between these two …

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

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 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 …

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 …

Memetic computing is a subject in computer science which considers complex structures
such as the combination of simple agents and memes, whose evolutionary interactions lead …

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 …

Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for
attacking hard combinatorial optimization problems. Yet, its performance, when compared to …

Hybrid metaheuristics have received considerable interest these recent years in the field of
combinatorial optimization. A wide variety of hybrid approaches have been proposed in the …