The field of parallel metaheuristics is continuously evolving as a result of new technologies
and needs that researchers have been encountering. In the last decade, new models of …

This article presents a review and a comparative analysis between frameworks for solving
optimization problems using metaheuristics. The aim is to identify both the desirable …

In this paper we survey computational models for Grid scheduling problems and their
resolution using heuristic and meta-heuristic approaches. Scheduling problems are at the …

Structured parallel programs ought to be conceived as two separate and complementary
entities: computation, which expresses the calculations in a procedural manner, and …

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 …

In this paper we present Genetic Algorithms (GAs) based schedulers for efficiently allocating
jobs to resources in a Grid system. Scheduling is a key problem in emergent computational …

In recent years, a number of authors have successfully extended particle swarmoptimization
to problem domains with multiple objec\-tives. This paper addresses theissue of parallelizing …

In this chapter, we review a few important concepts from Grid computing related to
scheduling problems and their resolution using heuristic and meta-heuristic approaches …

The Quadratic Assignment Problem (QAP) is a difficult and important problem studied in the
domain of combinatorial optimisation. It is possible to solve QAP instances with 10--20 …

In this paper we discuss on the MALLBA framework, a software tool for the resolution of
combinatorial optimisation problems using generic algorithmic skeletons implemented in …