Artificial Intelligence, Evolutionary Computing and Metaheuristics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence, Evolutionary Computing and Metaheuristics write by Xin-She Yang. This book was released on 2012-07-27. Artificial Intelligence, Evolutionary Computing and Metaheuristics available in PDF, EPUB and Kindle. Alan Turing pioneered many research areas such as artificial intelligence, computability, heuristics and pattern formation. Nowadays at the information age, it is hard to imagine how the world would be without computers and the Internet. Without Turing's work, especially the core concept of Turing Machine at the heart of every computer, mobile phone and microchip today, so many things on which we are so dependent would be impossible. 2012 is the Alan Turing year -- a centenary celebration of the life and work of Alan Turing. To celebrate Turing's legacy and follow the footsteps of this brilliant mind, we take this golden opportunity to review the latest developments in areas of artificial intelligence, evolutionary computation and metaheuristics, and all these areas can be traced back to Turing's pioneer work. Topics include Turing test, Turing machine, artificial intelligence, cryptography, software testing, image processing, neural networks, nature-inspired algorithms such as bat algorithm and cuckoo search, and multiobjective optimization and many applications. These reviews and chapters not only provide a timely snapshot of the state-of-art developments, but also provide inspiration for young researchers to carry out potentially ground-breaking research in the active, diverse research areas in artificial intelligence, cryptography, machine learning, evolutionary computation, and nature-inspired metaheuristics. This edited book can serve as a timely reference for graduates, researchers and engineers in artificial intelligence, computer sciences, computational intelligence, soft computing, optimization, and applied sciences.
Handbook of AI-based Metaheuristics
Handbook of AI-based Metaheuristics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of AI-based Metaheuristics write by Anand J. Kulkarni. This book was released on 2021-09-01. Handbook of AI-based Metaheuristics available in PDF, EPUB and Kindle. At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms. This will be a valuable reference for researchers in industry and academia, as well as for all Master’s and PhD students working in the metaheuristics and applications domains.
Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends
Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends write by Yin, Peng-Yeng. This book was released on 2012-03-31. Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends available in PDF, EPUB and Kindle. "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.
Metaheuristic and Evolutionary Computation: Algorithms and Applications
Metaheuristic and Evolutionary Computation: Algorithms and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Metaheuristic and Evolutionary Computation: Algorithms and Applications write by Hasmat Malik. This book was released on 2020-10-08. Metaheuristic and Evolutionary Computation: Algorithms and Applications available in PDF, EPUB and Kindle. This book addresses the principles and applications of metaheuristic approaches in engineering and related fields. The first part covers metaheuristics tools and techniques such as ant colony optimization and Tabu search, and their applications to several classes of optimization problems. In turn, the book’s second part focuses on a wide variety of metaheuristics applications in engineering and/or the applied sciences, e.g. in smart grids and renewable energy. In addition, the simulation codes for the problems discussed are included in an appendix for ready reference. Intended for researchers aspiring to learn and apply metaheuristic techniques, and gathering contributions by prominent experts in the field, the book offers readers an essential introduction to metaheuristics, its theoretical aspects and applications.
Theory and Principled Methods for the Design of Metaheuristics
Theory and Principled Methods for the Design of Metaheuristics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Theory and Principled Methods for the Design of Metaheuristics write by Yossi Borenstein. This book was released on 2013-12-19. Theory and Principled Methods for the Design of Metaheuristics available in PDF, EPUB and Kindle. Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.
