Advanced Optimization by Nature-Inspired Algorithms
Title | Advanced Optimization by Nature-Inspired Algorithms PDF eBook |
Author | Omid Bozorg-Haddad |
Publisher | Springer |
Total Pages | 159 |
Release | 2017-06-30 |
Genre | Technology & Engineering |
ISBN | 9811052212 |
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 Optimization in Advanced Manufacturing Processes and Systems
Title | Nature-Inspired Optimization in Advanced Manufacturing Processes and Systems PDF eBook |
Author | Ganesh M. Kakandikar |
Publisher | CRC Press |
Total Pages | 279 |
Release | 2020-12-08 |
Genre | Technology & Engineering |
ISBN | 1000258386 |
The manufacturing system is going through substantial changes and developments in light of Industry 4.0. Newer manufacturing technologies are being developed and applied. There is a need to optimize these techniques when applied in different circumstances with respect to materials, tools, product configurations, and process parameters. This book covers computational intelligence applied to manufacturing. It discusses nature-inspired optimization of processes and their design and development in manufacturing systems. It explores all manufacturing processes, at both macro and micro levels, and offers manufacturing philosophies. Nonconventional manufacturing, real industry problems and case studies, research on generative processes, and relevance of all this to Industry 4.0 is also included. Researchers, students, academicians, and industry professionals will find this reference title very useful.
Nature-Inspired Optimization Algorithms
Title | Nature-Inspired Optimization Algorithms PDF eBook |
Author | Xin-She Yang |
Publisher | Elsevier |
Total Pages | 277 |
Release | 2014-02-17 |
Genre | Computers |
ISBN | 0124167454 |
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 Methods for Metaheuristics Optimization
Title | Nature-Inspired Methods for Metaheuristics Optimization PDF eBook |
Author | Fouad Bennis |
Publisher | Springer Nature |
Total Pages | 503 |
Release | 2020-01-17 |
Genre | Business & Economics |
ISBN | 3030264580 |
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 Metaheuristic Algorithms for Engineering Optimization Applications
Title | Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications PDF eBook |
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.
Nature-Inspired Algorithms and Applied Optimization
Title | Nature-Inspired Algorithms and Applied Optimization PDF eBook |
Author | Xin-She Yang |
Publisher | Springer |
Total Pages | 330 |
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 Algorithms for Optimisation
Title | Nature-Inspired Algorithms for Optimisation PDF eBook |
Author | Raymond Chiong |
Publisher | Springer |
Total Pages | 524 |
Release | 2009-05-02 |
Genre | Technology & Engineering |
ISBN | 3642002676 |
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.