Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)
Author: Carlos Cruz
Publisher: Springer
Total Pages: 401
Release: 2010-04-16
Genre: Technology & Engineering
ISBN: 3642125387

Many aspects of Nature, Biology or even from Society have become part of the techniques and algorithms used in computer science or they have been used to enhance or hybridize several techniques through the inclusion of advanced evolution, cooperation or biologically based additions. The previous NICSO workshops were held in Granada, Spain, 2006, Acireale, Italy, 2007, and in Tenerife, Spain, 2008. As in the previous editions, NICSO 2010, held in Granada, Spain, was conceived as a forum for the latest ideas and the state of the art research related to nature inspired cooperative strategies. The contributions collected in this book cover topics including nature-inspired techniques like Genetic Algorithms, Evolutionary Algorithms, Ant and Bee Colonies, Swarm Intelligence approaches, Neural Networks, several Cooperation Models, Structures and Strategies, Agents Models, Social Interactions, as well as new algorithms based on the behaviour of fireflies or bats.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2011)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2011)
Author: David Alejandro Pelta
Publisher: Springer Science & Business Media
Total Pages: 359
Release: 2011-10-09
Genre: Computers
ISBN: 3642240933

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. The previous editions of NICSO were held in Granada, Spain (2006), Acireale, Italy (2007), Tenerife, Spain (2008), and again in Granada in 2010. NICSO evolved to be one of the most interesting and profiled workshops in nature inspired computing. NICSO 2011 has offered an inspiring environment for debating the state of the art ideas and techniques in nature inspired cooperative strategies and a comprehensive image on recent applications of these ideas and techniques. The topics covered by this volume include Swarm Intelligence (such as Ant and Bee Colony Optimization), Genetic Algorithms, Multiagent Systems, Coevolution and Cooperation strategies, Adversarial Models, Synergic Building Blocks, Complex Networks, Social Impact Models, Evolutionary Design, Self Organized Criticality, Evolving Systems, Cellular Automata, Hybrid Algorithms, and Membrane Computing (P-Systems).

Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)
Author: Carlos Cruz
Publisher: Springer Science & Business Media
Total Pages: 401
Release: 2010-04-07
Genre: Computers
ISBN: 3642125379

Many aspects of Nature, Biology or even from Society have become part of the techniques and algorithms used in computer science or they have been used to enhance or hybridize several techniques through the inclusion of advanced evolution, cooperation or biologically based additions. The previous NICSO workshops were held in Granada, Spain, 2006, Acireale, Italy, 2007, and in Tenerife, Spain, 2008. As in the previous editions, NICSO 2010, held in Granada, Spain, was conceived as a forum for the latest ideas and the state of the art research related to nature inspired cooperative strategies. The contributions collected in this book cover topics including nature-inspired techniques like Genetic Algorithms, Evolutionary Algorithms, Ant and Bee Colonies, Swarm Intelligence approaches, Neural Networks, several Cooperation Models, Structures and Strategies, Agents Models, Social Interactions, as well as new algorithms based on the behaviour of fireflies or bats.

Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization
Author: Javier Del Ser Lorente
Publisher: BoD – Books on Demand
Total Pages: 71
Release: 2018-07-18
Genre: Mathematics
ISBN: 1789233283

Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems.

Nature-Inspired Intelligent Computing Techniques in Bioinformatics

Nature-Inspired Intelligent Computing Techniques in Bioinformatics
Author: Khalid Raza
Publisher: Springer Nature
Total Pages: 340
Release: 2022-10-31
Genre: Technology & Engineering
ISBN: 9811963797

This book encapsulates and occupies recent advances and state-of-the-art applications of nature-inspired computing (NIC) techniques in the field of bioinformatics and computational biology, which would aid medical sciences in various clinical applications. This edited volume covers fundamental applications, scope, and future perspectives of NIC techniques in bioinformatics including genomic profiling, gene expression data classification, DNA computation, systems and network biology, solving personalized therapy complications, antimicrobial resistance in bacterial pathogens, and computer-aided drug design, discovery, and therapeutics. It also covers the role of NIC techniques in various diseases and disorders, including cancer detection and diagnosis, breast cancer, lung disorder detection, disease biomarkers, and potential therapeutics identifications.

Nature-Inspired Algorithms and Applied Optimization

Nature-Inspired Algorithms and Applied Optimization
Author: Xin-She Yang
Publisher: Springer
Total Pages: 332
Release: 2017-10-08
Genre: Technology & Engineering
ISBN: 3319676695

This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

Nature-Inspired Computing and Optimization

Nature-Inspired Computing and Optimization
Author: Srikanta Patnaik
Publisher: Springer
Total Pages: 506
Release: 2017-03-07
Genre: Technology & Engineering
ISBN: 3319509209

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.

Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications

Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications
Author: Serdar Carbas
Publisher: Springer Nature
Total Pages: 420
Release: 2021-03-31
Genre: Technology & Engineering
ISBN: 9813367733

This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in application contexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications.

Swarm Intelligence Optimization

Swarm Intelligence Optimization
Author: Abhishek Kumar
Publisher: John Wiley & Sons
Total Pages: 384
Release: 2021-01-07
Genre: Computers
ISBN: 1119778743

Resource optimization has always been a thrust area of research, and as the Internet of Things (IoT) is the most talked about topic of the current era of technology, it has become the need of the hour. Therefore, the idea behind this book was to simplify the journey of those who aspire to understand resource optimization in the IoT. To this end, included in this book are various real-time/offline applications and algorithms/case studies in the fields of engineering, computer science, information security, and cloud computing, along with the modern tools and various technologies used in systems, leaving the reader with a high level of understanding of various techniques and algorithms used in resource optimization.

Search Algorithm

Search Algorithm
Author: Dinesh G. Harkut
Publisher: BoD – Books on Demand
Total Pages: 140
Release: 2023-02-01
Genre: Computers
ISBN: 1839690860

Algorithms, particularly those embedded in search engines, social media platforms, recommendation systems, and information databases, play an increasingly important role in selecting what information is most relevant to us, which is a crucial feature of our participation in public life. These algorithms are not just helpful in our daily lives but are also one of the unavoidable necessities of modern living. This book discusses advances and applications of various types of search algorithms, such as quantum search, harmony search, cognitive search, genetic search, and many others. It is a valuable resource and provides a solid technical base for frontline investigations of search algorithms for scientists and students interested in search and optimization methods.