Metaheuristic Algorithms: New Methods, Evaluation, and Performance Analysis
Author: Erik Cuevas
Publisher: Springer Nature
Published:
Total Pages: 309
ISBN-13: 303163053X
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Metaheuristics
Author: El-Ghazali Talbi
Publisher: John Wiley & Sons
Published: 2009-05-27
Total Pages: 625
ISBN-13: 0470496908
DOWNLOAD EBOOKA unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.
Analysis and Comparison of Metaheuristics
Author: Erik Cuevas
Publisher: Springer Nature
Published: 2022-11-02
Total Pages: 230
ISBN-13: 3031201051
DOWNLOAD EBOOKThis book presents a comparative perspective of current metaheuristic developments, which have proved to be effective in their application to several complex problems. The study of biological and social entities such as animals, humans, or insects that manifest a cooperative behavior has produced several computational models in metaheuristic methods. Although these schemes emulate very different processes or systems, the rules used to model individual behavior are very similar. Under such conditions, it is not clear to identify which are the advantages or disadvantages of each metaheuristic technique. The book is compiled from a teaching perspective. For this reason, the book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. It is appropriate for courses such as Artificial Intelligence, Electrical Engineering, Evolutionary Computation. The book is also useful for researchers from the evolutionary and engineering communities. Likewise, engineer practitioners, who are not familiar with metaheuristic computation concepts, will appreciate that the techniques discussed are beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise in engineering areas.
Metaheuristics for Bi-level Optimization
Author: El-Ghazali Talbi
Publisher: Springer
Published: 2013-04-09
Total Pages: 298
ISBN-13: 3642378382
DOWNLOAD EBOOKThis book provides a complete background on metaheuristics to solve complex bi-level optimization problems (continuous/discrete, mono-objective/multi-objective) in a diverse range of application domains. Readers learn to solve large scale bi-level optimization problems by efficiently combining metaheuristics with complementary metaheuristics and mathematical programming approaches. Numerous real-world examples of problems demonstrate how metaheuristics are applied in such fields as networks, logistics and transportation, engineering design, finance and security.
Nature-Inspired Optimization Algorithms
Author: Xin-She Yang
Publisher: Elsevier
Published: 2014-02-17
Total Pages: 277
ISBN-13: 0124167454
DOWNLOAD EBOOKNature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. - Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature - Provides a theoretical understanding as well as practical implementation hints - Provides a step-by-step introduction to each algorithm
Harmony Search Algorithm
Author: Joong Hoon Kim
Publisher: Springer
Published: 2015-08-08
Total Pages: 456
ISBN-13: 3662479265
DOWNLOAD EBOOKThe Harmony Search Algorithm (HSA) is one of the most well-known techniques in the field of soft computing, an important paradigm in the science and engineering community. This volume, the proceedings of the 2nd International Conference on Harmony Search Algorithm 2015 (ICHSA 2015), brings together contributions describing the latest developments in the field of soft computing with a special focus on HSA techniques. It includes coverage of new methods that have potentially immense application in various fields. Contributed articles cover aspects of the following topics related to the Harmony Search Algorithm: analytical studies; improved, hybrid and multi-objective variants; parameter tuning; and large-scale applications. The book also contains papers discussing recent advances on the following topics: genetic algorithms; evolutionary strategies; the firefly algorithm and cuckoo search; particle swarm optimization and ant colony optimization; simulated annealing; and local search techniques. This book offers a valuable snapshot of the current status of the Harmony Search Algorithm and related techniques, and will be a useful reference for practising researchers and advanced students in computer science and engineering.
Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends
Author: Yin, Peng-Yeng
Publisher: IGI Global
Published: 2012-03-31
Total Pages: 446
ISBN-13: 1466602716
DOWNLOAD EBOOK"This book is a collection of the latest developments, models, and applications within the transdisciplinary fields related to metaheuristic computing, providing readers with insight into a wide range of topics such as genetic algorithms, differential evolution, and ant colony optimization"--Provided by publisher.
Parallel Metaheuristics
Author: Enrique Alba
Publisher: John Wiley & Sons
Published: 2005-10-03
Total Pages: 574
ISBN-13: 0471739375
DOWNLOAD EBOOKSolving complex optimization problems with parallel metaheuristics Parallel Metaheuristics brings together an international group of experts in parallelism and metaheuristics to provide a much-needed synthesis of these two fields. Readers discover how metaheuristic techniques can provide useful and practical solutions for a wide range of problems and application domains, with an emphasis on the fields of telecommunications and bioinformatics. This volume fills a long-existing gap, allowing researchers and practitioners to develop efficient metaheuristic algorithms to find solutions. The book is divided into three parts: * Part One: Introduction to Metaheuristics and Parallelism, including an Introduction to Metaheuristic Techniques, Measuring the Performance of Parallel Metaheuristics, New Technologies in Parallelism, and a head-to-head discussion on Metaheuristics and Parallelism * Part Two: Parallel Metaheuristic Models, including Parallel Genetic Algorithms, Parallel Genetic Programming, Parallel Evolution Strategies, Parallel Ant Colony Algorithms, Parallel Estimation of Distribution Algorithms, Parallel Scatter Search, Parallel Variable Neighborhood Search, Parallel Simulated Annealing, Parallel Tabu Search, Parallel GRASP, Parallel Hybrid Metaheuristics, Parallel Multi-Objective Optimization, and Parallel Heterogeneous Metaheuristics * Part Three: Theory and Applications, including Theory of Parallel Genetic Algorithms, Parallel Metaheuristics Applications, Parallel Metaheuristics in Telecommunications, and a final chapter on Bioinformatics and Parallel Metaheuristics Each self-contained chapter begins with clear overviews and introductions that bring the reader up to speed, describes basic techniques, and ends with a reference list for further study. Packed with numerous tables and figures to illustrate the complex theory and processes, this comprehensive volume also includes numerous practical real-world optimization problems and their solutions. This is essential reading for students and researchers in computer science, mathematics, and engineering who deal with parallelism, metaheuristics, and optimization in general.
Metaheuristics Algorithms for Medical Applications
Author: Mohamed Abdel-Basset
Publisher: Elsevier
Published: 2023-11-25
Total Pages: 249
ISBN-13: 0443133158
DOWNLOAD EBOOKMetaheuristics Algorithms for Medical Applications: Methods and Applications provides readers with the most complete reference for developing Metaheuristics techniques with Machine Learning for solving biomedical problems. The book is organized to present a stepwise progression beginning with the basics of Metaheuristics, leading into methods and practices, and concluding with advanced topics. The first section of the book presents the fundamental concepts of Metaheuristics and Machine Learning, and also provides a comprehensive taxonomic view of Metaheuristics methods according to a variety of criteria such as data type, scope, method, and so forth. The second section of the book explains how to apply Metaheuristics techniques for solving large-scale biomedical problems, including analysis and validation under different strategies. The final portion of the book focuses on advanced topics in Metaheuristics in four different applications. Readers will discover a variety of new methods, approaches, and techniques, as well as a wide range of applications demonstrating key concepts in Metaheuristics for biomedical science. The book provides a leading-edge resource for researchers in a variety of scientific fields who are interested in metaheuristics, including mathematics, biomedical engineering, computer science, biological sciences, and clinicians in medical practice. - Introduces a new set of Metaheuristics techniques for biomedical applications - Presents basic concepts of Metaheuristics, methods and practices, followed by advanced topics and applications - Provides researchers, practitioners, and project stakeholders with a complete guide for understanding and applying metaheuristics and machine learning techniques in their projects and solutions
New Metaheuristic Schemes: Mechanisms and Applications
Author: Erik Cuevas
Publisher: Springer Nature
Published: 2023-12-08
Total Pages: 280
ISBN-13: 3031455614
DOWNLOAD EBOOKRecently, novel metaheuristic techniques have emerged in response to the limitations of conventional approaches, leading to enhanced outcomes. These new methods introduce interesting mechanisms and innovative collaborative strategies that facilitate the efficient exploration and exploitation of extensive search spaces characterized by numerous dimensions. The objective of this book is to present advancements that discuss novel alternative metaheuristic developments that have demonstrated their effectiveness in tackling various complex problems. This book encompasses a variety of emerging metaheuristic methods and their practical applications. The content is presented from a teaching perspective, making it particularly suitable for undergraduate and postgraduate students in fields such as science, electrical engineering, and computational mathematics. The book aligns well with courses in artificial intelligence, electrical engineering, and evolutionary computation. Furthermore, the material offers valuable insights to researchers within the metaheuristic and engineering communities. Similarly, engineering practitioners unfamiliar with metaheuristic computation concepts will recognize the pragmatic value of the discussed techniques. These methods transcend mere theoretical tools that have been adapted to effectively address the significant real-world problems commonly encountered in engineering domains.
