The increasing complexity of real-world optimization problems raises new challenges to
evolutionary computation. Responding to these challenges, distributed evolutionary …

This paper studies static and dynamic decentralized versions of the search model known as
cellular genetic algorithm (cGA), in which individuals are located in a specific topology and …

Research in exact algorithms, heuristics and metaheuristics for solving combinatorial
optimization problems is nowadays highly on the rise. The main advantage of using exact …

This book is the result of several years of research trying to better characterize parallel
genetic algorithms (pGAs) as a powerful tool for optimization, search, and learning. Readers …

The field of evolutionary computation (EC) can no longer be considered an esoteric one.
Today, after about thirty years of research, a rich corpus of theory exists and many …

This authoritative handbook reveals the connections between bioinspired techniques and
the development of solutions to problems that arise in diverse problem domains. It provides …

Evolutionary algorithms (EA s) have given rise to many parallel variants, fuelled by the
rapidly increasing number of CPU cores and the ready availability of computation power …

Summary form only given. This article gives a brief overview of theoretical advances,
computing trends, applications and future perspectives in parallel genetic algorithms. It …

Mobile Ad Hoc Networks (MANETs) are composed of a set of communicating devices which
are able to spontaneously interconnect without any pre-existing infrastructure. In such kind …

This paper proposes a novel distributed differential evolution algorithm, namely Distributed
Differential Evolution with Explorative–Exploitative Population Families (DDE-EEPF). In DDE …