This book is a PhD dissertation which focuses on the study, design, development and application of centralised cooperative strategies for optimisation problems. These models consist of a set of parallel cooperating agents, where each agent carries out a search in a solution space sharing information with the rest of the agents. Many studies have shown that this cooperation leads to more efficient and effective strategies. The authors start describing the most known trajectory and population-based metaheuristics and introduce the cooperative strategies. The core of this book is devoted to the following topics: analysis of the composition and the cooperation scheme, hybridization with Reactive Search ideas, application of centralised cooperative strategies to Dynamic Optimisation Problems and resolution of sets of instances by a cooperative method. The book is addressed to students or researchers in the fields of Intelligent Systems, Soft Computing, Optimisation Techniques and, especially, Hybrid Metaheuristics.

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Antonio D. Masegosa was born in Cúllar, Granada, Spain. He received his degree in Computer Engineering in 2005 and his PhD degree in Computer Sciences in 2010 from the School of Computer and Telecommunications Engineering, University of Granada, Spain. His research interest includes Intelligent Systems, Soft Computing and Cooperative Strategies.