## Articles by "Metaheuristic Algorithms"

Showing posts with label Metaheuristic Algorithms. Show all posts

### Artificial Bee Colony Optimization Algorithm Using MatLAB

Teachers:
Dr. H. T. Jadhav, Mayank Dadge - Language: English - Videos: 26 - Duration: 3 hours and 16 minutes.

This course is specifically developed for B. Tech. and M. Tech/MS students of all Engineering disciplines. Especially the students of Mechanical, Electrical, Automobile, Chemical, Aeronautical, Electronics, Computer science, Instrumentation, Mechatronics, Manufacturing, Robotics and Civil Engineering can learn MATLAB basics and solve Engineering Optimization problems in their area as part of mini-project or capstone project. In addition to this, the course is also useful to Ph. D. students of different engineering branches.

The course is designed in such a way that the student who is not well versed with MATLAB programing can learn the basics of MATLAB in the first part so that it is easy for him/her to understand MATLAB implementation of Artificial bee colony Algorithm to solve simple and advanced Engineering problems. The content is so organized that the learner should be able to understand Engineering optimization from scratch and solve research problems leading to publication in an international journal of high repute. It should be useful to students of all universities around the world.

What you’ll learn: Write MATLAB program to solve Engineering problems + Understand Artificial bee colony Optimization Algorithm (ABC) + Implement ABC Algorithm to solve benchmark problems + Implement ABC Algorithm to solve Mechanical Engineering problems + Design and develop MATLAB program using ABC Algorithm for Mechanical Engineering Optimization problem + Work on research problem leading to publication in international journals of high repute.

### Metaheuristic Optimization in Power Engineering

Jordan RadosavljeviÄ‡ ... 536 pages - Publisher: The Institution of Engineering and Technology (June, 2018) ... Language: English - ISBN-10: 1785615467 - ISBN-13: 978-1785615467.

A metaheuristic is a consistent set of ideas, concepts, and operators to design a heuristic optimization algorithm, that can provide a sufficiently good solution to an optimization problem with incomplete or imperfect information. Modern and emerging power systems, with the growing complexity of distributed and intermittent generation, are an important application for such methods. This book describes the principles of solving various problems in power engineering via the application of selected metaheuristic optimization methods including genetic algorithms, particle swarm optimization, and the gravitational search algorithm. Applications covered include power flow calculation; optimal power flow in transmission networks; optimal reactive power dispatch in transmission networks; combined economic and emission dispatch; optimal power flow in distribution networks; optimal volt/var control in distribution networks; optimal placement and sizing of distributed generation in distribution networks; optimal energy and operation management of microgrids; optimal coordination of directional overcurrent relays; and steady-state analysis of self-excited induction generators.

### Heuristics for Optimization and Learning

Farouk Yalaoui, Lionel Amodeo, El-Ghazali Talbi ... 649 pages - Language: English - Publisher: Springer; (December, 2020) ... AmazonSIN: B08QR86X4J.

This book is a new contribution aiming to give some last research findings in the field of optimization and computing. This work is in the same field target than our two previous books published: “Recent Developments in Metaheuristics” and “Metaheuristics for Production Systems”, books in Springer Series in Operations Research/Computer Science Interfaces. The challenge with this work is to gather the main contribution in three fields, optimization technique for production decision, general development for optimization and computing method and wider spread applications.

The number of researches dealing with decision maker tool and optimization method grows very quickly these last years and in a large number of fields. We may be able to read nice and worthy works from research developed in chemical, mechanical, computing, automotive and many other fields.

### A Practical Approach to Metaheuristics using LabVIEW and MATLAB

Pedro Ponce-Cruz, Arturo Molina GutiÃ©rrez, Ricardo A. RamÃ­rez-Mendoza, EfraÃ­n MÃ©ndez Flores, Alexandro Antonio Ortiz Espinoza, David Christopher Balderas Silva ... 178 pages - Publisher: Chapman and Hall/CRC; (June, 2020) ... Language: English - AmazonSIN: B08LGNKST8.

Metaheuristic optimization has become a prime alternative for solving complex optimization problems in several areas. Hence, practitioners and researchers have been paying extensive attention to those metaheuristic algorithms that are mainly based on natural phenomena. However, when those algorithms are implemented, there are not enough books that deal with theoretical and experimental problems in a friendly manner so this book presents a novel structure that includes a complete description of the most important metaheuristic optimization algorithms as well as a new proposal of a new metaheuristic optimization named earthquake optimization. This book also has several practical exercises and a toolbox for MATLAB® and a toolkit for LabVIEW are integrated as complementary material for this book. These toolkits allow readers to move from a simulation environment to an experimentation one very fast. This book is suitable for researchers, students, and professionals in several areas, such as economics, architecture, computer science, electrical engineering, and control systems.

The unique features of this book are as follows: Developed for researchers, undergraduate and graduate students, and practitioners + A friendly description of the main metaheuristic optimization algorithms + Theoretical and practical optimization examples + A new earthquake optimization algorithm + Updated state-of-the-art and research optimization projects.

### Hidden Semi-Markov Models: Theory, Algorithms and Applications

Shun-Zheng Yu ... 208 pages - AmazonSIN: B017A382CC ... Language: English - Publisher: Elsevier; (October, 2015).

Hidden semi-Markov models (HSMMs) are among the most important models in the area of artificial intelligence / machine learning. Since the first HSMM was introduced in 1980 for machine recognition of speech, three other HSMMs have been proposed, with various definitions of duration and observation distributions. Those models have different expressions, algorithms, computational complexities, and applicable areas, without explicitly interchangeable forms. Hidden Semi-Markov Models: Theory, Algorithms and Applications provides a unified and foundational approach to HSMMs, including various HSMMs (such as the explicit duration, variable transition, and residential time of HSMMs), inference and estimation algorithms, implementation methods and application instances. Learn new developments and state-of-the-art emerging topics as they relate to HSMMs, presented with examples drawn from medicine, engineering and computer science.

Discusses the latest developments and emerging topics in the field of HSMMs + Includes a description of applications in various areas including, Human Activity Recognition, Handwriting Recognition, Network + Traffic Characterization and Anomaly Detection, and Functional MRI Brain Mapping. + Shows how to master the basic techniques needed for using HSMMs and how to apply them.

### Hidden Markov Models: Methods and Protocols

David R. Westhead, M. S. Vijayabaskar ... 231 pages - ISBN-13: 978-1493967513 ... Publisher: Humana; (February, 2017) - Language: English - AmazonSIN: 1493967517.

This volume aims to provide a new perspective on the broader usage of Hidden Markov Models (HMMs) in biology. Hidden Markov Models: Methods and Protocols guides readers through chapters on biological systems; ranging from single biomolecule, cellular level, and to organism level and the use of HMMs in unravelling the complex mechanisms that govern these complex systems. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Authoritative and practical, Hidden Markov Models: Methods and Protocols aims to demonstrate the impact of HMM in biology and inspire new research.

### Artificial Intelligence for Humans, Vol. 2: Nature-Inspired Algorithms

Jeff Heaton ... 244 pages - Publisher: Heaton Research, Inc.; (August, 2014) ... Language: English - AmazonSIN: B00MYLNLSQ.

Nature can be a great source of inspiration for artificial intelligence algorithms because its technology is considerably more advanced than our own. Among its wonders are strong AI, nanotechnology, and advanced robotics. Nature can therefore serve as a guide for real-life problem solving. In this book, you will encounter algorithms influenced by ants, bees, genomes, birds, and cells that provide practical methods for many types of AI situations. Although nature is the muse behind the methods, we are not duplicating its exact processes. The complex behaviors in nature merely provide inspiration in our quest to gain new insights about data.

Artificial Intelligence for Humans is a book series meant to teach AI to those readers who lack an extensive mathematical background. The reader only needs knowledge of basic college algebra and computer programming. Additional topics are thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, and Python. Other languages are planned. No knowledge of biology is needed to read this book.

### Optimization in Machine Learning and Applications

Anand J. Kulkarni, Suresh Chandra Satapathy ... 197 pages - Publisher: Springer; (November, 2019) ... Language: English - AmazonSIN: B0825P5H9C.

This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.

### Nature-Inspired Methods for Metaheuristics Optimization: Algorithms and Applications

Fouad Bennis, Rajib Kumar Bhattacharjya ... 502 pages - Publisher: Springer; (January, 2020) ... Language: English - ASIN: B0843NX5CT.

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.

### Applications of Firefly Algorithm and its Variants: Case Studies and New Developments

Nilanjan Dey ... 266 pages - Publisher: Springer; (November, 2019) ... Language: English - AmazonSIN: B0818MWNQJ.

The book discusses advantages of the firefly algorithm over other well-known metaheuristic algorithms in various engineering studies. The book provides a brief outline of various application-oriented problem solving methods, like economic emission load dispatch problem, designing a fully digital controlled reconfigurable switched beam nonconcentric ring array antenna, image segmentation, span minimization in permutation flow shop scheduling, multi-objective load dispatch problems, image compression, etc., using FA and its variants. It also covers the use of the firefly algorithm to select features, as research has shown that the firefly algorithm generates precise and optimal results in terms of time and optimality. In addition, the book also explores the potential of the firefly algorithm to provide a solution to traveling salesman problem, graph coloring problem, etc.

### Deep Biometrics: Unsupervised and Semi-Supervised Learning

Richard Jiang, Chang-Tsun Li, Danny Crookes, Weizhi Meng, Christophe Rosenberger ... 320 pages - Publisher: Springer; January, 2020) ... Language: English - ASIN: B084D81NNG by Amazon.

This book highlights new advances in biometrics using deep learning toward deeper and wider background, deeming it “Deep Biometrics”. The book aims to highlight recent developments in biometrics using semi-supervised and unsupervised methods such as Deep Neural Networks, Deep Stacked Autoencoder, Convolutional Neural Networks, Generative Adversary Networks, and so on. The contributors demonstrate the power of deep learning techniques in the emerging new areas such as privacy and security issues, cancellable biometrics, soft biometrics, smart cities, big biometric data, biometric banking, medical biometrics, healthcare biometrics, and biometric genetics, etc. The goal of this volume is to summarize the recent advances in using Deep Learning in the area of biometric security and privacy toward deeper and wider applications.

Highlights the impact of deep learning over the field of biometrics in a wide area; Exploits the deeper and wider background of biometrics, such as privacy versus security, biometric big data, biometric genetics, and biometric diagnosis, etc.; Introduces new biometric applications such as biometric banking, internet of things, cloud computing, and medical biometrics.

### Metaheuristics for Portfolio Optimization

G. A. Vijayalakshmi Pai ... 316 pages - Publisher: Wiley-ISTE; (December 27, 2017) ... Language: English - ASIN: B078X252PR by Amazon.

The book is a monograph in the cross disciplinary area of Computational Intelligence in Finance and elucidates a collection of practical and strategic Portfolio Optimization models in Finance, that employ Metaheuristics for their effective solutions and demonstrates the results using MATLAB implementations, over live portfolios invested across global stock universes. The book has been structured in such a way that, even novices in finance or metaheuristics should be able to comprehend and work on the hybrid models discussed in the book.

### Practice of Optimisation Theory in Geotechnical Engineering

Zhen-Yu Yin, Yin-Fu Jin ... 356 pages - Publisher: Springer; (April, 2019) ... Language: English - ASIN: B07R6CD27W by Amazon.

This book presents the development of an optimization platform for geotechnical engineering, which is one of the key components in smart geotechnics. The book discusses the fundamentals of the optimization algorithm with constitutive models of soils. Helping readers easily understand the optimization algorithm applied in geotechnical engineering, this book first introduces the methodology of the optimization-based parameter identification, and then elaborates the principle of three newly developed efficient optimization algorithms, followed by the ideas of a variety of laboratory tests and formulations of constitutive models. Moving on to the application of optimization methods in geotechnical engineering, this book presents an optimization-based parameter identification platform with a practical and concise interface based on the above theories. The book is intended for undergraduate and graduate-level teaching in soil mechanics and geotechnical engineering and other related engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering and operations research fields.

### Advances in Metaheuristics Algorithms: Methods and Applications

Erik Cuevas, Daniel ZaldÃ­var, Marco PÃ©rez-Cisneros ... 218 pages - Publisher: Springer; (April, 2018) ... Language: English - ASIN: B07C3LK4K3 by Amazon.

This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms considered offer promising results, they are nevertheless still in their infancy. To grow and attain their full potential, new metaheuristic methods must be applied in a great variety of problems and contexts, so that they not only perform well in their reported sets of optimization problems, but also in new complex formulations. The only way to accomplish this is to disseminate these methods in various technical areas as optimization tools. In general, once a scientist, engineer or practitioner recognizes a problem as a particular instance of a more generic class, he/she can select one of several metaheuristic algorithms that guarantee an expected optimization performance. Unfortunately, the set of options are concentrated on algorithms whose popularity and high proliferation outstrip those of the new developments. This structure is important, because the authors recognize this methodology as the best way to help researchers, lecturers, engineers and practitioners solve their own optimization problems.

### Metaheuristics for Big Data Volume: 5

Clarisse Dhaenens, Laetitia Jourdan ... 213 pages - Publisher: Wiley-ISTE; (August, 2016) ... Language: English - ASIN: B01KZO6P4U by Amazon

Big Data is a new field, with many technological challenges to be understood in order to use it to its full potential. These challenges arise at all stages of working with Big Data, beginning with data generation and acquisition. The storage and management phase presents two critical challenges: infrastructure, for storage and transportation, and conceptual models. Finally, to extract meaning from Big Data requires complex analysis. Here the authors propose using metaheuristics as a solution to these challenges; they are first able to deal with large size problems and secondly flexible and therefore easily adaptable to different types of data and different contexts. The use of metaheuristics to overcome some of these data mining challenges is introduced and justified in the first part of the book, alongside a specific protocol for the performance evaluation of algorithms. An introduction to metaheuristics follows. The second part of the book details a number of data mining tasks, including clustering, association rules, supervised classification and feature selection, before explaining how metaheuristics can be used to deal with them. This book is designed to be self-contained, so that readers can understand all of the concepts discussed within it, and to provide an overview of recent applications of metaheuristics to knowledge discovery problems in the context of Big Data.

### An Introduction to Metaheuristics for Optimization

Bastien Chopard, Marco Tomassini ... 226 pages - Publisher: Springer; (November, 2018) ... Language: English - ISBN-10: 3319930729 - ISBN-13: 978-3319930725

The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.

### Advances in Metaheuristics: Applications in Engineering Sys.

Timothy Ganesan, Pandian Vasant, Irraivan Elamvazuthi ... 219 pages - Publisher: CRC Press; 1st edition (November, 2016) ... Language: English - ASIN: B01N7FM4RX by Amazon

Advances in Metaheuristics: Applications in Engineering Systems provides details on current approaches utilized in engineering optimization. It gives a comprehensive background on metaheuristic applications, focusing on main engineering sectors such as energy, process, and materials. It discusses topics such as algorithmic enhancements and performance measurement approaches, and provides insights into the implementation of metaheuristic strategies to multi-objective optimization problems. With this book, readers can learn to solve real-world engineering optimization problems effectively using the appropriate techniques from emerging fields including evolutionary and swarm intelligence, mathematical programming, and multi-objective optimization. The ten chapters of this book are divided into three parts. The first part discusses three industrial applications in the energy sector. The second focusses on process optimization and considers three engineering applications: optimization of a three-phase separator, process plant, and a pre-treatment process. The third and final part of this book covers industrial applications in material engineering, with a particular focus on sand mould-systems. It also includes discussions on the potential improvement of algorithmic characteristics via strategic algorithmic enhancements. This book helps fill the existing gap in literature on the implementation of metaheuristics in engineering applications and real-world engineering systems. It will be an important resource for engineers and decision-makers selecting and implementing metaheuristics to solve specific engineering problems.

### Handbook of Metaheuristics 3rd Edition

Michel Gendreau, Jean-Yves Potvin ... 604 pages - Publisher: Springer; 3rd edition (September, 2018) ... Language: English - ISBN-10: 331991085X - ISBN-13: 978-3319910857

The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book’s chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular. Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.

### Beyond Artificial Intelligence: The Disappearing Human-Machine...

Jan Romportl, Eva Zackova, Jozef Kelemen ... 219 pages - Publisher: Springer; (August, 2014) ... Language: English - ISBN-10: 3319096672 - ISBN-13: 978-3319096674

This book is an edited collection of chapters based on the papers presented at the conference “Beyond AI: Artificial Dreams” held in Pilsen in November 2012. The aim of the conference was to question deep-rooted ideas of artificial intelligence and cast critical reflection on methods standing at its foundations. Artificial Dreams epitomize our controversial quest for non-biological intelligence and therefore the contributors of this book tried to fully exploit such a controversy in their respective chapters, which resulted in an interdisciplinary dialogue between experts from engineering, natural sciences and humanities. While pursuing the Artificial Dreams, it has become clear that it is still more and more difficult to draw a clear divide between human and machine. And therefore this book tries to portrait such an image of what lies beyond artificial intelligence: we can see the disappearing human-machine divide, a very important phenomenon of nowadays technological society, the phenomenon which is often uncritically praised, or hypocritically condemned. And so this phenomenon found its place in the subtitle of the whole volume as well as in the title of the chapter of Kevin Warwick, one of the keynote speakers at “Beyond AI: Artificial Dreams”.

### Advancements in Applied Metaheuristic Computing

Nilanjan Dey ... 335 pages - Publisher: IGI Global; 1st edition (November, 2017) ... Language: English - ISBN-10: 9781522541516 - ISBN-13: 978-1522541516 ...

Metaheuristic algorithms are present in various applications for different domains. Recently, researchers have conducted studies on the effectiveness of these algorithms in providing optimal solutions to complicated problems. Advancements in Applied Metaheuristic Computing is a crucial reference source for the latest empirical research on methods and approaches that include metaheuristics for further system improvements, and it offers outcomes of employing optimization algorithms. Featuring coverage on a broad range of topics such as manufacturing, genetic programming, and medical imaging, this publication is ideal for researchers, academicians, advanced-level students, and technology developers seeking current research on the use of optimization algorithms in several applications.

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