Computational Intelligence For Optimization

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Computational Intelligence for Optimization

Nirwan Ansari,Edwin Hou
Computational Intelligence for Optimization Book PDF

Author : Nirwan Ansari,Edwin Hou
Publisher : Springer Science & Business Media
Page : 228 pages
File Size : 54,5 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461563310

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Computational Intelligence for Optimization by Nirwan Ansari,Edwin Hou Pdf

The field of optimization is interdisciplinary in nature, and has been making a significant impact on many disciplines. As a result, it is an indispensable tool for many practitioners in various fields. Conventional optimization techniques have been well established and widely published in many excellent textbooks. However, there are new techniques, such as neural networks, simulated anneal ing, stochastic machines, mean field theory, and genetic algorithms, which have been proven to be effective in solving global optimization problems. This book is intended to provide a technical description on the state-of-the-art development in advanced optimization techniques, specifically heuristic search, neural networks, simulated annealing, stochastic machines, mean field theory, and genetic algorithms, with emphasis on mathematical theory, implementa tion, and practical applications. The text is suitable for a first-year graduate course in electrical and computer engineering, computer science, and opera tional research programs. It may also be used as a reference for practicing engineers, scientists, operational researchers, and other specialists. This book is an outgrowth of a couple of special topic courses that we have been teaching for the past five years. In addition, it includes many results from our inter disciplinary research on the topic. The aforementioned advanced optimization techniques have received increasing attention over the last decade, but relatively few books have been produced.

Computational Intelligence in Optimization

Yoel Tenne,Chi-Keong Goh
Computational Intelligence in Optimization Book PDF

Author : Yoel Tenne,Chi-Keong Goh
Publisher : Springer Science & Business Media
Page : 412 pages
File Size : 47,6 Mb
Release : 2010-06-30
Category : Technology & Engineering
ISBN : 9783642127755

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Computational Intelligence in Optimization by Yoel Tenne,Chi-Keong Goh Pdf

This collection of recent studies spans a range of computational intelligence applications, emphasizing their application to challenging real-world problems. Covers Intelligent agent-based algorithms, Hybrid intelligent systems, Machine learning and more.

Computational Intelligence in Expensive Optimization Problems

Yoel Tenne,Chi-Keong Goh
Computational Intelligence in Expensive Optimization Problems Book PDF

Author : Yoel Tenne,Chi-Keong Goh
Publisher : Springer Science & Business Media
Page : 800 pages
File Size : 55,8 Mb
Release : 2010-03-10
Category : Technology & Engineering
ISBN : 9783642107016

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Computational Intelligence in Expensive Optimization Problems by Yoel Tenne,Chi-Keong Goh Pdf

In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc. Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary algorithms, neural networks and fuzzy logic, which often perform well in such settings. This is the first book to introduce the emerging field of computational intelligence in expensive optimization problems. Topics covered include: dedicated implementations of evolutionary algorithms, neural networks and fuzzy logic. reduction of expensive evaluations (modelling, variable-fidelity, fitness inheritance), frameworks for optimization (model management, complexity control, model selection), parallelization of algorithms (implementation issues on clusters, grids, parallel machines), incorporation of expert systems and human-system interface, single and multiobjective algorithms, data mining and statistical analysis, analysis of real-world cases (such as multidisciplinary design optimization). The edited book provides both theoretical treatments and real-world insights gained by experience, all contributed by leading researchers in the respective fields. As such, it is a comprehensive reference for researchers, practitioners, and advanced-level students interested in both the theory and practice of using computational intelligence for expensive optimization problems.

Intelligent Computational Optimization in Engineering

Mario Köppen,Gerald Schaefer,Ajith Abraham
Intelligent Computational Optimization in Engineering Book PDF

Author : Mario Köppen,Gerald Schaefer,Ajith Abraham
Publisher : Springer
Page : 400 pages
File Size : 51,6 Mb
Release : 2011-07-15
Category : Technology & Engineering
ISBN : 9783642217050

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Intelligent Computational Optimization in Engineering by Mario Köppen,Gerald Schaefer,Ajith Abraham Pdf

We often come across computational optimization virtually in all branches of engineering and industry. Many engineering problems involve heuristic search and optimization, and, once discretized, may become combinatorial in nature, which gives rise to certain difficulties in terms of solution procedure. Some of these problems have enormous search spaces, are NP-hard and hence require heuristic solution techniques. Another difficulty is the lack of ability of classical solution techniques to determine appropriate optima of non-convex problems. Under these conditions, recent advances in computational optimization techniques have been shown to be advantageous and successful compared to classical approaches. This Volume presents some of the latest developments with a focus on the design of algorithms for computational optimization and their applications in practice. Through the chapters of this book, researchers and practitioners share their experience and newest methodologies with regard to intelligent optimization and provide various case studies of the application of intelligent optimization techniques in real-world applications.This book can serve as an excellent reference for researchers and graduate students in computer science, various engineering disciplines and the industry.

Computational Optimization, Methods and Algorithms

Slawomir Koziel,Xin-She Yang
Computational Optimization Methods and Algorithms Book PDF

Author : Slawomir Koziel,Xin-She Yang
Publisher : Springer
Page : 292 pages
File Size : 51,6 Mb
Release : 2011-06-17
Category : Technology & Engineering
ISBN : 9783642208591

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Computational Optimization, Methods and Algorithms by Slawomir Koziel,Xin-She Yang Pdf

Computational optimization is an important paradigm with a wide range of applications. In virtually all branches of engineering and industry, we almost always try to optimize something - whether to minimize the cost and energy consumption, or to maximize profits, outputs, performance and efficiency. In many cases, this search for optimality is challenging, either because of the high computational cost of evaluating objectives and constraints, or because of the nonlinearity, multimodality, discontinuity and uncertainty of the problem functions in the real-world systems. Another complication is that most problems are often NP-hard, that is, the solution time for finding the optimum increases exponentially with the problem size. The development of efficient algorithms and specialized techniques that address these difficulties is of primary importance for contemporary engineering, science and industry. This book consists of 12 self-contained chapters, contributed from worldwide experts who are working in these exciting areas. The book strives to review and discuss the latest developments concerning optimization and modelling with a focus on methods and algorithms for computational optimization. It also covers well-chosen, real-world applications in science, engineering and industry. Main topics include derivative-free optimization, multi-objective evolutionary algorithms, surrogate-based methods, maximum simulated likelihood estimation, support vector machines, and metaheuristic algorithms. Application case studies include aerodynamic shape optimization, microwave engineering, black-box optimization, classification, economics, inventory optimization and structural optimization. This graduate level book can serve as an excellent reference for lecturers, researchers and students in computational science, engineering and industry.

Multi-Objective Optimization in Computational Intelligence: Theory and Practice

Thu Bui, Lam,Alam, Sameer
Multi Objective Optimization in Computational Intelligence Theory and Practice Book PDF

Author : Thu Bui, Lam,Alam, Sameer
Publisher : IGI Global
Page : 496 pages
File Size : 51,5 Mb
Release : 2008-05-31
Category : Technology & Engineering
ISBN : 9781599045009

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Multi-Objective Optimization in Computational Intelligence: Theory and Practice by Thu Bui, Lam,Alam, Sameer Pdf

Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.

Intelligent Computing & Optimization

Pandian Vasant,Ivan Zelinka,Gerhard-Wilhelm Weber
Intelligent Computing Optimization Book PDF

Author : Pandian Vasant,Ivan Zelinka,Gerhard-Wilhelm Weber
Publisher : Springer Nature
Page : 1020 pages
File Size : 53,6 Mb
Release : 2021-12-30
Category : Technology & Engineering
ISBN : 9783030932473

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Intelligent Computing & Optimization by Pandian Vasant,Ivan Zelinka,Gerhard-Wilhelm Weber Pdf

This book includes the scientific results of the fourth edition of the International Conference on Intelligent Computing and Optimization which took place at December 30–31, 2021, via ZOOM. The conference objective was to celebrate “Compassion and Wisdom” with researchers, scholars, experts and investigators in Intelligent Computing and Optimization worldwide, to share knowledge, experience, innovation—marvelous opportunity for discourse and mutuality by novel research, invention and creativity. This proceedings encloses the original and innovative scientific fields of optimization and optimal control, renewable energy and sustainability, artificial intelligence and operational research, economics and management, smart cities and rural planning, meta-heuristics and big data analytics, cyber security and blockchains, IoTs and Industry 4.0, mathematical modelling and simulation, health care and medicine.

Computational Intelligence

Andries P. Engelbrecht
Computational Intelligence Book PDF

Author : Andries P. Engelbrecht
Publisher : John Wiley & Sons
Page : 628 pages
File Size : 43,7 Mb
Release : 2007-10-22
Category : Technology & Engineering
ISBN : 0470512504

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Computational Intelligence by Andries P. Engelbrecht Pdf

Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. Engelbrecht provides readers with a wide knowledge of Computational Intelligence (CI) paradigms and algorithms; inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without any difficulty through a single Java class as part of the CI library. Key features of this second edition include: A tutorial, hands-on based presentation of the material. State-of-the-art coverage of the most recent developments in computational intelligence with more elaborate discussions on intelligence and artificial intelligence (AI). New discussion of Darwinian evolution versus Lamarckian evolution, also including swarm robotics, hybrid systems and artificial immune systems. A section on how to perform empirical studies; topics including statistical analysis of stochastic algorithms, and an open source library of CI algorithms. Tables, illustrations, graphs, examples, assignments, Java code implementing the algorithms, and a complete CI implementation and experimental framework. Computational Intelligence: An Introduction, Second Edition is essential reading for third and fourth year undergraduate and postgraduate students studying CI. The first edition has been prescribed by a number of overseas universities and is thus a valuable teaching tool. In addition, it will also be a useful resource for researchers in Computational Intelligence and Artificial Intelligence, as well as engineers, statisticians, operational researchers, and bioinformaticians with an interest in applying AI or CI to solve problems in their domains. Check out http://www.ci.cs.up.ac.za for examples, assignments and Java code implementing the algorithms.

Applied Optimization and Swarm Intelligence

Eneko Osaba,Xin-She Yang
Applied Optimization and Swarm Intelligence Book PDF

Author : Eneko Osaba,Xin-She Yang
Publisher : Springer Nature
Page : 236 pages
File Size : 43,5 Mb
Release : 2021-05-17
Category : Technology & Engineering
ISBN : 9789811606625

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Applied Optimization and Swarm Intelligence by Eneko Osaba,Xin-She Yang Pdf

This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence.

Foundations of Computational Intelligence Volume 3

Ajith Abraham,Aboul-Ella Hassanien,Patrick Siarry,Andries Engelbrecht
Foundations of Computational Intelligence Volume 3 Book PDF

Author : Ajith Abraham,Aboul-Ella Hassanien,Patrick Siarry,Andries Engelbrecht
Publisher : Springer Science & Business Media
Page : 531 pages
File Size : 44,9 Mb
Release : 2009-04-27
Category : Computers
ISBN : 9783642010842

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Foundations of Computational Intelligence Volume 3 by Ajith Abraham,Aboul-Ella Hassanien,Patrick Siarry,Andries Engelbrecht Pdf

Global optimization is a branch of applied mathematics and numerical analysis that deals with the task of finding the absolutely best set of admissible conditions to satisfy certain criteria / objective function(s), formulated in mathematical terms. Global optimization includes nonlinear, stochastic and combinatorial programming, multiobjective programming, control, games, geometry, approximation, algorithms for parallel architectures and so on. Due to its wide usage and applications, it has gained the attention of researchers and practitioners from a plethora of scientific domains. Typical practical examples of global optimization applications include: Traveling salesman problem and electrical circuit design (minimize the path length); safety engineering (building and mechanical structures); mathematical problems (Kepler conjecture); Protein structure prediction (minimize the energy function) etc. Global Optimization algorithms may be categorized into several types: Deterministic (example: branch and bound methods), Stochastic optimization (example: simulated annealing). Heuristics and meta-heuristics (example: evolutionary algorithms) etc. Recently there has been a growing interest in combining global and local search strategies to solve more complicated optimization problems. This edited volume comprises 17 chapters, including several overview Chapters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of global optimization. Besides research articles and expository papers on theory and algorithms of global optimization, papers on numerical experiments and on real world applications were also encouraged. The book is divided into 2 main parts.

Artificial Intelligence for Business Optimization

Bhuvan Unhelkar,Tad Gonsalves
Artificial Intelligence for Business Optimization Book PDF

Author : Bhuvan Unhelkar,Tad Gonsalves
Publisher : CRC Press
Page : 295 pages
File Size : 52,9 Mb
Release : 2021-08-09
Category : Business & Economics
ISBN : 9781000409475

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Artificial Intelligence for Business Optimization by Bhuvan Unhelkar,Tad Gonsalves Pdf

This book explains how AI and Machine Learning can be applied to help businesses solve problems, support critical thinking and ultimately create customer value and increase profit. By considering business strategies, business process modeling, quality assurance, cybersecurity, governance and big data and focusing on functions, processes, and people’s behaviors it helps businesses take a truly holistic approach to business optimization. It contains practical examples that make it easy to understand the concepts and apply them. It is written for practitioners (consultants, senior executives, decision-makers) dealing with real-life business problems on a daily basis, who are keen to develop systematic strategies for the application of AI/ML/BD technologies to business automation and optimization, as well as researchers who want to explore the industrial applications of AI and higher-level students.

Handbook of Machine Learning for Computational Optimization

Vishal Jain,Sapna Juneja,Abhinav Juneja,Ramani Kannan
Handbook of Machine Learning for Computational Optimization Book PDF

Author : Vishal Jain,Sapna Juneja,Abhinav Juneja,Ramani Kannan
Publisher : CRC Press
Page : 295 pages
File Size : 48,6 Mb
Release : 2021-11-02
Category : Technology & Engineering
ISBN : 9781000455670

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Handbook of Machine Learning for Computational Optimization by Vishal Jain,Sapna Juneja,Abhinav Juneja,Ramani Kannan Pdf

Focuses on new machine learning developments that can lead to newly developed applications Uses a predictive and futuristic approach which makes Machine Learning a promising tool for business processes and sustainable solutions Promotes newer algorithms which are more efficient and reliable for a new dimension in discovering certain latent domains of applications Discusses the huge potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making Offers many real-time case studies

High-Performance Simulation-Based Optimization

Thomas Bartz-Beielstein,Bogdan Filipič,Peter Korošec,El-Ghazali Talbi
High Performance Simulation Based Optimization Book PDF

Author : Thomas Bartz-Beielstein,Bogdan Filipič,Peter Korošec,El-Ghazali Talbi
Publisher : Springer
Page : 291 pages
File Size : 43,6 Mb
Release : 2019-06-01
Category : Technology & Engineering
ISBN : 9783030187644

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High-Performance Simulation-Based Optimization by Thomas Bartz-Beielstein,Bogdan Filipič,Peter Korošec,El-Ghazali Talbi Pdf

This book presents the state of the art in designing high-performance algorithms that combine simulation and optimization in order to solve complex optimization problems in science and industry, problems that involve time-consuming simulations and expensive multi-objective function evaluations. As traditional optimization approaches are not applicable per se, combinations of computational intelligence, machine learning, and high-performance computing methods are popular solutions. But finding a suitable method is a challenging task, because numerous approaches have been proposed in this highly dynamic field of research. That’s where this book comes in: It covers both theory and practice, drawing on the real-world insights gained by the contributing authors, all of whom are leading researchers. Given its scope, if offers a comprehensive reference guide for researchers, practitioners, and advanced-level students interested in using computational intelligence and machine learning to solve expensive optimization problems.

Computational Intelligence, Optimization and Inverse Problems with Applications in Engineering

Gustavo Mendes Platt,Xin-She Yang,Antônio José Silva Neto
Computational Intelligence Optimization and Inverse Problems with Applications in Engineering Book PDF

Author : Gustavo Mendes Platt,Xin-She Yang,Antônio José Silva Neto
Publisher : Springer
Page : 284 pages
File Size : 48,6 Mb
Release : 2018-09-25
Category : Technology & Engineering
ISBN : 9783319964331

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Computational Intelligence, Optimization and Inverse Problems with Applications in Engineering by Gustavo Mendes Platt,Xin-She Yang,Antônio José Silva Neto Pdf

This book focuses on metaheuristic methods and its applications to real-world problems in Engineering. The first part describes some key metaheuristic methods, such as Bat Algorithms, Particle Swarm Optimization, Differential Evolution, and Particle Collision Algorithms. Improved versions of these methods and strategies for parameter tuning are also presented, both of which are essential for the practical use of these important computational tools. The second part then applies metaheuristics to problems, mainly in Civil, Mechanical, Chemical, Electrical, and Nuclear Engineering. Other methods, such as the Flower Pollination Algorithm, Symbiotic Organisms Search, Cross-Entropy Algorithm, Artificial Bee Colonies, Population-Based Incremental Learning, Cuckoo Search, and Genetic Algorithms, are also presented. The book is rounded out by recently developed strategies, or hybrid improved versions of existing methods, such as the Lightning Optimization Algorithm, Differential Evolution with Particle Collisions, and Ant Colony Optimization with Dispersion – state-of-the-art approaches for the application of computational intelligence to engineering problems. The wide variety of methods and applications, as well as the original results to problems of practical engineering interest, represent the primary differentiation and distinctive quality of this book. Furthermore, it gathers contributions by authors from four countries – some of which are the original proponents of the methods presented – and 18 research centers around the globe.

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

Modestus O. Okwu,Lagouge K. Tartibu
Metaheuristic Optimization Nature Inspired Algorithms Swarm and Computational Intelligence Theory and Applications Book PDF

Author : Modestus O. Okwu,Lagouge K. Tartibu
Publisher : Springer Nature
Page : 192 pages
File Size : 52,7 Mb
Release : 2020-11-13
Category : Technology & Engineering
ISBN : 9783030611118

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Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications by Modestus O. Okwu,Lagouge K. Tartibu Pdf

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.