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Introduction to Nature-Inspired Optimization

Introduction to Nature-Inspired Optimization
A Book

by George Lindfield,John Penny

  • Publisher : Academic Press
  • Release : 2017-08-10
  • Pages : 256
  • ISBN : 0128036664
  • Language : En, Es, Fr & De
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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

Nature-Inspired Optimization Algorithms
A Book

by Xin-She Yang

  • Publisher : Elsevier
  • Release : 2014-02-17
  • Pages : 300
  • ISBN : 0124167454
  • Language : En, Es, Fr & De
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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 Optimization Algorithms

Nature-Inspired Optimization Algorithms
A Book

by Vasuki A

  • Publisher : CRC Press
  • Release : 2020-05-31
  • Pages : 260
  • ISBN : 1000076601
  • Language : En, Es, Fr & De
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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 Optimization Algorithms for Fuzzy Controlled Servo Systems

Nature-Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems
A Book

by Radu-Emil Precup,Radu-Codrut David

  • Publisher : Butterworth-Heinemann
  • Release : 2019-05-15
  • Pages : 220
  • ISBN : 0128163585
  • Language : En, Es, Fr & De
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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

Nature-Inspired Methods for Metaheuristics Optimization

Nature-Inspired Methods for Metaheuristics Optimization
Algorithms and Applications in Science and Engineering

by Fouad Bennis,Rajib Kumar Bhattacharjya

  • Publisher : Springer Nature
  • Release : 2020-01-17
  • Pages : 502
  • ISBN : 3030264580
  • Language : En, Es, Fr & De
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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.

Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization
A Book

by Javier Del Ser Lorente,Eneko Osaba

  • Publisher : BoD – Books on Demand
  • Release : 2018-07-18
  • Pages : 70
  • ISBN : 1789233283
  • Language : En, Es, Fr & De
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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 Optimizers

Nature-Inspired Optimizers
Theories, Literature Reviews and Applications

by Seyedali Mirjalili,Jin Song Dong,Andrew Lewis

  • Publisher : Springer
  • Release : 2019-02-01
  • Pages : 238
  • ISBN : 3030121275
  • Language : En, Es, Fr & De
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This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. Each chapter offers a comprehensive description of a specific algorithm, from the mathematical model to its practical application. Different kind of optimization problems are solved in this book, including those related to path planning, image processing, hand gesture detection, among others. All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms. Source codes for most of the proposed techniques have been included as supplementary materials on a dedicated webpage.

Nature-Inspired Algorithms and Applied Optimization

Nature-Inspired Algorithms and Applied Optimization
A Book

by Xin-She Yang

  • Publisher : Springer
  • Release : 2017-10-08
  • Pages : 330
  • ISBN : 3319676695
  • Language : En, Es, Fr & De
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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
Theory and Applications

by Srikanta Patnaik,Xin-She Yang,Kazumi Nakamatsu

  • Publisher : Springer
  • Release : 2017-03-07
  • Pages : 494
  • ISBN : 3319509209
  • Language : En, Es, Fr & De
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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.

Advanced Optimization by Nature-Inspired Algorithms

Advanced Optimization by Nature-Inspired Algorithms
A Book

by Omid Bozorg-Haddad

  • Publisher : Springer
  • Release : 2017-06-30
  • Pages : 159
  • ISBN : 9811052212
  • Language : En, Es, Fr & De
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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.

Nature-Inspired Algorithms for Optimisation

Nature-Inspired Algorithms for Optimisation
A Book

by Raymond Chiong

  • Publisher : Springer
  • Release : 2009-05-02
  • Pages : 516
  • ISBN : 3642002676
  • Language : En, Es, Fr & De
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Nature-Inspired Algorithms have been gaining much popularity in recent years due to the fact that many real-world optimisation problems have become increasingly large, complex and dynamic. The size and complexity of the problems nowadays require the development of methods and solutions whose efficiency is measured by their ability to find acceptable results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This volume 'Nature-Inspired Algorithms for Optimisation' is a collection of the latest state-of-the-art algorithms and important studies for tackling various kinds of optimisation problems. It comprises 18 chapters, including two introductory chapters which address the fundamental issues that have made optimisation problems difficult to solve and explain the rationale for seeking inspiration from nature. The contributions stand out through their novelty and clarity of the algorithmic descriptions and analyses, and lead the way to interesting and varied new applications.

Discrete Problems in Nature Inspired Algorithms

Discrete Problems in Nature Inspired Algorithms
A Book

by Anupam Prof. Shukla,Ritu Tiwari

  • Publisher : CRC Press
  • Release : 2017-12-15
  • Pages : 310
  • ISBN : 1351260863
  • Language : En, Es, Fr & De
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This book includes introduction of several algorithms which are exclusively for graph based problems, namely combinatorial optimization problems, path formation problems, etc. Each chapter includes the introduction of the basic traditional nature inspired algorithm and discussion of the modified version for discrete algorithms including problems pertaining to discussed algorithms.

Nature Inspired Optimization Techniques for Image Processing Applications

Nature Inspired Optimization Techniques for Image Processing Applications
A Book

by Jude Hemanth,Valentina Emilia Balas

  • Publisher : Springer
  • Release : 2018-09-19
  • Pages : 297
  • ISBN : 3319960024
  • Language : En, Es, Fr & De
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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.

Harmony Search and Nature Inspired Optimization Algorithms

Harmony Search and Nature Inspired Optimization Algorithms
Theory and Applications, ICHSA 2018

by Neha Yadav,Anupam Yadav,Jagdish Chand Bansal,Kusum Deep,Joong Hoon Kim

  • Publisher : Springer
  • Release : 2018-08-23
  • Pages : 1238
  • ISBN : 981130761X
  • Language : En, Es, Fr & De
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The book covers different aspects of real-world applications of optimization algorithms. It provides insights from the Fourth International Conference on Harmony Search, Soft Computing and Applications held at BML Munjal University, Gurgaon, India on February 7–9, 2018. It consists of research articles on novel and newly proposed optimization algorithms; the theoretical study of nature-inspired optimization algorithms; numerically established results of nature-inspired optimization algorithms; and real-world applications of optimization algorithms and synthetic benchmarking of optimization algorithms.

Mathematical Foundations of Nature-Inspired Algorithms

Mathematical Foundations of Nature-Inspired Algorithms
A Book

by Xin-She Yang,Xing-Shi He

  • Publisher : Springer
  • Release : 2019-05-08
  • Pages : 107
  • ISBN : 3030169367
  • Language : En, Es, Fr & De
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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.

Search and Optimization by Metaheuristics

Search and Optimization by Metaheuristics
Techniques and Algorithms Inspired by Nature

by Ke-Lin Du,M. N. S. Swamy

  • Publisher : Birkhäuser
  • Release : 2016-07-20
  • Pages : 434
  • ISBN : 3319411926
  • Language : En, Es, Fr & De
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This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.

Nature-Inspired Computing

Nature-Inspired Computing
Physics and Chemistry-Based Algorithms

by Nazmul H. Siddique,Hojjat Adeli

  • Publisher : CRC Press
  • Release : 2017-05-19
  • Pages : 596
  • ISBN : 1482244837
  • Language : En, Es, Fr & De
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Nature-Inspired Computing: Physics and Chemistry-Based Algorithms provides a comprehensive introduction to the methodologies and algorithms in nature-inspired computing, with an emphasis on applications to real-life engineering problems. The research interest for Nature-inspired Computing has grown considerably exploring different phenomena observed in nature and basic principles of physics, chemistry, and biology. The discipline has reached a mature stage and the field has been well-established. This endeavour is another attempt at investigation into various computational schemes inspired from nature, which are presented in this book with the development of a suitable framework and industrial applications. Designed for senior undergraduates, postgraduates, research students, and professionals, the book is written at a comprehensible level for students who have some basic knowledge of calculus and differential equations, and some exposure to optimization theory. Due to the focus on search and optimization, the book is also appropriate for electrical, control, civil, industrial and manufacturing engineering, business, and economics students, as well as those in computer and information sciences. With the mathematical and programming references and applications in each chapter, the book is self-contained, and can also serve as a reference for researchers and scientists in the fields of system science, natural computing, and optimization.

Nature-inspired Metaheuristic Algorithms

Nature-inspired Metaheuristic Algorithms
A Book

by Xin-She Yang

  • Publisher : Luniver Press
  • Release : 2010
  • Pages : 148
  • ISBN : 1905986289
  • Language : En, Es, Fr & De
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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.

Biologically Inspired Optimization Methods

Biologically Inspired Optimization Methods
An Introduction

by Mattias Wahde

  • Publisher : WIT Press
  • Release : 2008-08-14
  • Pages : 240
  • ISBN : 1845641485
  • Language : En, Es, Fr & De
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Biologically inspired optimization methods constitute a rapidly expanding field of research, with new applications appearing on an almost daily basis, as optimization problems of ever-increasing complexity appear in science and technology. This book provides a general introduction to such optimization methods, along with descriptions of the biological systems upon which the methods are based. The book also covers classical optimization methods, making it possible for the reader to determine whether a classical optimization method or a biologically inspired one is most suitable for a given problem.

Nature Inspired Optimization for Image Processing

Nature Inspired Optimization for Image Processing
A Book

by Vasuki A

  • Publisher : CRC Press
  • Release : 2020-07-09
  • Pages : 280
  • ISBN : 9780367255985
  • Language : En, Es, Fr & De
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Nature Inspired Optimization Algorithms is a comprehensive book on the most popular optimization algorithms that are based on nature. It starts with an overview of optimization and goes from the classical to the latest swarm intelligence algorithm. Nature has a rich abundance of flora and fauna that inspired the development of nature inspired optimization techniques. 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 behaviour. Nature provides us with simple solutions to complex problems in an effective and adaptive manner. This book is a valuable resource for engineers, researchers, faculty and students who are devising optimum solutions to any type of problem. The problems range from computer science to economics covering diverse areas that require maximizing output and minimizing resources and this is the crux of all optimization algorithms. The book is a lucid description of fifteen of the existing important optimization algorithms that are based on swarm intelligence and superior in performance. Features: Detailed description of the algorithms along with pseudocode and flowchart Easily translatable to program code that is also readily available in Mathworks website for some of the algorithms Simple examples to demonstrate the optimization strategies have been given wherever possible that makes understanding easier Standard applications and benchmark datasets for testing and validating the algorithms have been enumerated This book is a reference for under-graduate and post-graduate students. It will be useful to faculty members teaching the subject on optimization. It 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.