Nature Inspired Optimization Algorithms Book

Nature Inspired Optimization Algorithms


  • Author : Xin-She Yang
  • Publisher : Elsevier
  • Release Date : 2014-02-17
  • Genre: Computers
  • Pages : 300
  • ISBN 10 : 9780124167452

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Nature Inspired Optimization Algorithms Excerpt :

Nature-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

Nature inspired Metaheuristic Algorithms Book

Nature inspired Metaheuristic Algorithms


  • Author : Xin-She Yang
  • Publisher : Luniver Press
  • Release Date : 2010
  • Genre: Computers
  • Pages : 148
  • ISBN 10 : 9781905986286

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Nature inspired Metaheuristic Algorithms Excerpt :

Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms. We also briefly introduce the photosynthetic algorithm, the enzyme algorithm, and Tabu search. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course. As some of the algorithms such as the harmony search and firefly algorithms are at the forefront of current research, this book can also serve as a reference book for researchers.

Introduction to Nature Inspired Optimization Book

Introduction to Nature Inspired Optimization


  • Author : George Lindfield
  • Publisher : Academic Press
  • Release Date : 2017-08-10
  • Genre: Mathematics
  • Pages : 256
  • ISBN 10 : 9780128036662

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Introduction to Nature Inspired Optimization Excerpt :

Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work. Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization. Applies concepts in nature and biology to develop new algorithms for nonlinear optimization Offers working MATLAB® programs for the major algorithms described, applying them to a range of problems Provides useful comparative studies of the algorithms, highlighting their strengths and weaknesses Discusses the current state-of-the-field and indicates possible areas of future development

Nature Inspired Optimization Algorithms with Java Book

Nature Inspired Optimization Algorithms with Java


  • Author : Shashank Jain
  • Publisher : Apress
  • Release Date : 2021-12-12
  • Genre: Computers
  • Pages : 175
  • ISBN 10 : 1484274008

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Nature Inspired Optimization Algorithms with Java Excerpt :

Gain insight into the world of nature-inspired optimization techniques and algorithms. This book will prepare you to apply different nature-inspired optimization techniques to solve problems using Java. You'll start with an introduction to the hidden algorithms that nature uses and find the approximate solutions to optimization problems. You'll then see how living creatures such as fish and birds are able to perform computation to solve specific optimization tasks. This book also covers various nature-inspired algorithms by reviewing code examples for each one followed by crisp and clear explanations of the algorithm using Java code. You'll examine the use of each algorithm in specific industry scenarios such as fleet scheduling in supply chain management, and shop floor management in industrial and manufacturing applications. Nature-Inspired Optimization Algorithms with Java is your pathway to understanding a variety of optimization problems that exist in various industries and domains and it will develop an ability to apply nature-inspired algorithms to find approximate solutions to them. What You'll Learn Study optimization and its problems Examine nature-inspired algorithms such as Particle Swarm, Gray wolf, etc. See how nature-inspired algorithms are being used to solve optimization problems Use Java for solving the different nature-inspired algorithms with real-world examples Who This Book Is For Software developers/architects who are looking to hone their skills in area of problem solving related to optimization with Java.

Nature Inspired Optimization Algorithms Book

Nature Inspired Optimization Algorithms


  • Author : Aditya Khamparia
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release Date : 2021-02-08
  • Genre: Computers
  • Pages : 168
  • ISBN 10 : 9783110676150

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Nature Inspired Optimization Algorithms Excerpt :

This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems. Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications. Tentative Table of Contents/Topic Coverage: - Neural Computation - Evolutionary Computing Methods - Neuroscience driven AI Inspired Algorithms - Biological System based algorithms - Hybrid and Intelligent Computing Algorithms - Application of Natural Computing - Review and State of art analysis of Optimization algorithms - Molecular and Quantum computing applications - Swarm Intelligence - Population based algorithm and other optimizations

Nature Inspired Optimization Algorithms Book

Nature Inspired Optimization Algorithms


  • Author : Vasuki A
  • Publisher : CRC Press
  • Release Date : 2020-05-31
  • Genre: Computers
  • Pages : 260
  • ISBN 10 : 9781000076608

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Nature Inspired Optimization Algorithms Excerpt :

Nature-Inspired Optimization Algorithms, a comprehensive work on the most popular optimization algorithms based on nature, starts with an overview of optimization going from the classical to the latest swarm intelligence algorithm. Nature has a rich abundance of flora and fauna that inspired the development of optimization techniques, providing us with simple solutions to complex problems in an effective and adaptive manner. The study of the intelligent survival strategies of animals, birds, and insects in a hostile and ever-changing environment has led to the development of techniques emulating their behavior. This book is a lucid description of fifteen important existing optimization algorithms based on swarm intelligence and superior in performance. It is a valuable resource for engineers, researchers, faculty, and students who are devising optimum solutions to any type of problem ranging from computer science to economics and covering diverse areas that require maximizing output and minimizing resources. This is the crux of all optimization algorithms. Features: Detailed description of the algorithms along with pseudocode and flowchart Easy translation to program code that is also readily available in Mathworks website for some of the algorithms Simple examples demonstrating the optimization strategies are provided to enhance understanding Standard applications and benchmark datasets for testing and validating the algorithms are included This book is a reference for undergraduate and post-graduate students. It will be useful to faculty members teaching optimization. It is also a comprehensive guide for researchers who are looking for optimizing resources in attaining the best solution to a problem. The nature-inspired optimization algorithms are unconventional, and this makes them more efficient than their traditional counterparts.

Nature Inspired Algorithms and Applied Optimization Book

Nature Inspired Algorithms and Applied Optimization


  • Author : Xin-She Yang
  • Publisher : Springer
  • Release Date : 2017-10-08
  • Genre: Technology & Engineering
  • Pages : 330
  • ISBN 10 : 9783319676692

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Nature Inspired Algorithms and Applied Optimization Excerpt :

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 Methods for Metaheuristics Optimization Book

Nature Inspired Methods for Metaheuristics Optimization


  • Author : Fouad Bennis
  • Publisher : Springer Nature
  • Release Date : 2020-01-17
  • Genre: Business & Economics
  • Pages : 502
  • ISBN 10 : 9783030264581

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Nature Inspired Methods for Metaheuristics Optimization Excerpt :

This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.

Advanced Optimization by Nature Inspired Algorithms Book

Advanced Optimization by Nature Inspired Algorithms


  • Author : Omid Bozorg-Haddad
  • Publisher : Springer
  • Release Date : 2017-06-30
  • Genre: Technology & Engineering
  • Pages : 159
  • ISBN 10 : 9789811052217

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Advanced Optimization by Nature Inspired Algorithms Excerpt :

This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.

Metaheuristic Optimization  Nature Inspired Algorithms Swarm and Computational Intelligence  Theory and Applications Book

Metaheuristic Optimization Nature Inspired Algorithms Swarm and Computational Intelligence Theory and Applications


  • Author : Modestus O. Okwu
  • Publisher : Springer Nature
  • Release Date : 2020-11-13
  • Genre: Technology & Engineering
  • Pages : 192
  • ISBN 10 : 9783030611118

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Metaheuristic Optimization Nature Inspired Algorithms Swarm and Computational Intelligence Theory and Applications Excerpt :

This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

Nature Inspired Computing and Optimization Book

Nature Inspired Computing and Optimization


  • Author : Srikanta Patnaik
  • Publisher : Springer
  • Release Date : 2017-03-07
  • Genre: Technology & Engineering
  • Pages : 494
  • ISBN 10 : 9783319509204

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Nature Inspired Computing and Optimization Excerpt :

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 Optimization Techniques for Image Processing Applications Book

Nature Inspired Optimization Techniques for Image Processing Applications


  • Author : Jude Hemanth
  • Publisher : Springer
  • Release Date : 2018-09-19
  • Genre: Technology & Engineering
  • Pages : 297
  • ISBN 10 : 9783319960029

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Nature Inspired Optimization Techniques for Image Processing Applications Excerpt :

This book provides a platform for exploring nature-inspired optimization techniques in the context of imaging applications. Optimization has become part and parcel of all computational vision applications, and since the amount of data used in these applications is vast, the need for optimization techniques has increased exponentially. These accuracy and complexity are a major area of concern when it comes to practical applications. However, these optimization techniques have not yet been fully explored in the context of imaging applications. By presenting interdisciplinary concepts, ranging from optimization to image processing, the book appeals to a broad readership, while also encouraging budding engineers to pursue and employ innovative nature-inspired techniques for image processing applications.

Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems Book

Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems


  • Author : Radu-Emil Precup
  • Publisher : Butterworth-Heinemann
  • Release Date : 2019-05-15
  • Genre: Technology & Engineering
  • Pages : 148
  • ISBN 10 : 9780128163580

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Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems Excerpt :

Nature-inspired Optimization Algorithms for Fuzzy Controlled Servo Systems suits the general need of a book that explains the major issues to fuzzy control in servo systems without any solid mathematical prerequisite. In addition, pertinent information on nature-inspired optimization algorithms is offered. The book is intended to rapidly make intelligible notions of fuzzy set theory and fuzzy control to readers with limited experience. The attractive analysis and design methodologies dedicated to fuzzy controllers are accompanied by applications to servo systems and case studies in fuzzy controlled servo systems are organized in a special chapter of this book, and allow simple implementations of low-cost automation solutions. The theoretical approaches presented throughout the book are validated by the illustration of digital simulation results and real-time experimental results as well. This book aims at a large category of audience including graduate students, engineers (designers, practitioners and researchers), and everyone who faces challenging control problems. Gives a merge between classical and modern approaches to fuzzy control Presents in a unified structure from the point of view of a control engineer the essential aspects regarding fuzzy control in servo systems Makes intelligible notions of fuzzy set theory and fuzzy control to readers with limited experience

Mathematical Foundations of Nature Inspired Algorithms Book

Mathematical Foundations of Nature Inspired Algorithms


  • Author : Xin-She Yang
  • Publisher : Springer
  • Release Date : 2019-05-08
  • Genre: Mathematics
  • Pages : 107
  • ISBN 10 : 9783030169367

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Mathematical Foundations of Nature Inspired Algorithms Excerpt :

This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms.

Nature Inspired Algorithms and Applications Book

Nature Inspired Algorithms and Applications


  • Author : S. Balamurugan
  • Publisher : John Wiley & Sons
  • Release Date : 2021-12-14
  • Genre: Computers
  • Pages : 388
  • ISBN 10 : 9781119681748

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Nature Inspired Algorithms and Applications Excerpt :

NATURE-INSPIRED ALGORITHMS AND APPLICATIONS The book’s unified approach of balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Inspired by the world around them, researchers are gathering information that can be developed for use in areas where certain practical applications of nature-inspired computation and machine learning can be applied. This book is designed to enhance the reader’s understanding of this process by portraying certain practical applications of nature-inspired algorithms (NIAs) specifically designed to solve complex real-world problems in data analytics and pattern recognition by means of domain-specific solutions. Since various NIAs and their multidisciplinary applications in the mechanical engineering and electrical engineering sectors; and in machine learning, image processing, data mining, and wireless networks are dealt with in detail in this book, it can act as a handy reference guide. Among the subjects of the 12 chapters are: A novel method based on TRIZ to map real-world problems to nature problems Applications of cuckoo search algorithm for optimization problems Performance analysis of nature-inspired algorithms in breast cancer diagnosis Nature-inspired computation in data mining Hybrid bat-genetic algorithm–based novel optimal wavelet filter for compression of image data Efficiency of finding best solutions through ant colony optimization techniques Applications of hybridized algorithms and novel algorithms in the field of machine learning. Audience: Researchers and graduate students in mechanical engineering, electrical engineering, machine learning, image processing, data mining, and wireless networks will find this book very useful.