Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm Intelligence, Hyper-heuristics, Evolutionary Algorithms, Cellular Automata, Artificial Bee Colony, Dynamic Optimization, Support Vector Machines, Multi-Agent Systems, Ant Clustering, Evolutionary Design Optimisation, Game Theory and other several Cooperation Models.

Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm Intelligence, Hyper-heuristics, Evolutionary Algorithms, Cellular Automata, Artificial Bee Colony, Dynamic Optimization, Support Vector Machines, Multi-Agent Systems, Ant Clustering, Evolutionary Design Optimisation, Game Theory and other several Cooperation Models.

The evolution of soft computing applications have offered a multitude of methodologies and techniques that are useful in facilitating new ways to address practical and real scenarios in a variety of fields. Exploring Innovative and Successful Applications of Soft Computing highlights the applications and conclusions associated with soft computing in different technological environments. Providing potential results based on new trends in the development of these services, this book aims to be a reference source for researchers, practitioners, and students interested in the most successful soft computing methods applied to recent problems.

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.