Download or read book Swarm Stability and Optimization written by Veysel Gazi and published by Springer Science & Business Media. This book was released on 2011-02-01 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Swarming species such as flocks of birds or schools of fish exhibit fascinating collective behaviors during migration and predator avoidance. Similarly, engineered multi-agent dynamic systems such as groups of autonomous ground, underwater, or air vehicles (“vehicle swarms”) exhibit sophisticated collective behaviors while maneuvering. In this book we show how to model and control a wide range of such multi-agent dynamic systems and analyze their collective behavior using both stability theoretic and simulation-based approaches. In particular, we investigate problems such as group aggregation, social foraging, formation control, swarm tracking, distributed agreement, and engineering optimization inspired by swarm behavior.

Download or read book Particle Swarm Optimization Stability Analysis written by Ouboti Seydou Eyanaa Djaneye-Boundjou and published by . This book was released on 2013 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimizing a multidimensional function -- uni-modal or multi-modal -- is a problem that regularly comes about in engineering and science. Evolutionary Computation techniques, including Evolutionary Algorithm and Swarm Intelligence (SI), are biological systems inspired search methods often used to solve optimization problems. In this thesis, the SI technique Particle Swarm Optimization (PSO) is studied. Convergence and stability of swarm optimizers have been subject of PSO research. Here, using discrete-time adaptive control tools found in literature, an adaptive particle swarm optimizer is developed. An error system is devised and a controller is designed to adaptively drive the error to zero. The controller features a function approximator, used here as a predictor to estimate future signals. Through Lyapunov's direct method, it is shown that the devised error system is ultimately uniformly bounded and the adaptive optimizer is stable. Moreover, through LaSalle-Yoshizawa theorem, it is also shown that the error system goes to zero as time evolves. Experiments are performed on a variety of benchmark functions and results for comparison purposes between the adaptive optimizer and other algorithms found in literature are provided.

Download or read book Swarm Intelligence Optimization written by Abhishek Kumar and published by John Wiley & Sons. This book was released on 2021-01-07 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resource optimization has always been a thrust area of research, and as the Internet of Things (IoT) is the most talked about topic of the current era of technology, it has become the need of the hour. Therefore, the idea behind this book was to simplify the journey of those who aspire to understand resource optimization in the IoT. To this end, included in this book are various real-time/offline applications and algorithms/case studies in the fields of engineering, computer science, information security, and cloud computing, along with the modern tools and various technologies used in systems, leaving the reader with a high level of understanding of various techniques and algorithms used in resource optimization.

Download or read book Advanced Intelligent Computing Theories and Applications written by De-Shuang Huang and published by Springer Science & Business Media. This book was released on 2007-08-09 with total page 1397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, in conjunction with the two volumes CICS 0002 and LNCS 4681, constitutes the refereed proceedings of the Third International Conference on Intelligent Computing held in Qingdao, China, in August 2007. The 139 full papers published here were carefully reviewed and selected from among 2,875 submissions. These papers offer important findings and insights into the field of intelligent computing.

Download or read book Handbook of Swarm Intelligence written by Bijaya Ketan Panigrahi and published by Springer Science & Business Media. This book was released on 2011-02-04 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.

Download or read book Particle Swarm Optimization for the Minimization of Power Losses and Voltage Stability in Distribution Networks written by Vernon K. Butler and published by . This book was released on 2015 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Particle Swarm Optimization written by Maurice Clerc and published by John Wiley & Sons. This book was released on 2013-03-04 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book devoted entirely to Particle Swarm Optimization (PSO), which is a non-specific algorithm, similar to evolutionary algorithms, such as taboo search and ant colonies. Since its original development in 1995, PSO has mainly been applied to continuous-discrete heterogeneous strongly non-linear numerical optimization and it is thus used almost everywhere in the world. Its convergence rate also makes it a preferred tool in dynamic optimization.

Download or read book Exploratory Particle Swarm Optimization written by Armin Rashvand and published by . This book was released on 2015 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this research is to propose, implement, and analyze a new particle swarm optimization (PSO) algorithm with enhanced exploration, referred to as exploratory particle swarm optimization (ExPSO). We use the PSO and ExPSO algorithms to optimize tuning parameters for a passivity-based impedance controller on a hip robot simulation model which is used for testing a prosthetic leg. ExPSO has features in common with negative reinforcement particle swarm optimization (NPSO); both algorithms use not only individuals' successes, but also their mistakes, to modify individual velocities in the search space. NPSO uses mistakes to avoid poor solutions, but ExPSO uses mistakes to increase exploration. The 2005 Congress on Evolutionary Computation (CEC 2005) benchmark problems are used to evaluate the performance and parameter tuning of PSO and ExPSO. We find that ExPSO can arrive at optimum solutions better and faster than PSO and NPSO, especially for high-dimensional and complex problems. ExPSO can find solutions that are up to 55% better in terms of cost function values. For the problems that we tested, the standard form for ExPSO which is based on standard PSO (SPSO), namely ExSPSO, can solve 10 out of 38 benchmarks better than SPSO. SPSO can solve 7 out of 38 benchmarks better than ExSPSO, and both algorithms can solve 21 out of 38 benchmarks equally well. Additionally, analytical convergence conditions for ExPSO are derived.

Download or read book Particle Swarm Optimization and Intelligence Advances and Applications written by Parsopoulos, Konstantinos E. and published by IGI Global. This book was released on 2010-01-31 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents the most recent and established developments of Particle swarm optimization (PSO) within a unified framework by noted researchers in the field"--Provided by publisher.

Download or read book Particle Swarm Optimization written by Christopher Wesley Cleghorn and published by . This book was released on 2017 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Particle swarm optimization (PSO) is a well-known stochastic population-based search algorithm, originally developed by Kennedy and Eberhart in 1995. Given PSO's success at solving numerous real world problems, a large number of PSO variants have been proposed. However, unlike the original PSO, most variants currently have little to no existing theoretical results. This lack of a theoretical underpinning makes it difficult, if not impossible, for practitioners to make informed decisions about the algorithmic setup. This thesis focuses on the criteria needed for particle stability, or as it is often refereed to as, particle convergence. While new PSO variants are proposed at a rapid rate, the theoretical analysis often takes substantially longer to emerge, if at all. In some situation the theoretical analysis is not performed as the mathematical models needed to actually represent the PSO variants become too complex or contain intractable subproblems. It is for this reason that a rapid means of determining approximate stability criteria that does not require complex mathematical modeling is needed. This thesis presents an empirical approach for determining the stability criteria for PSO variants. This approach is designed to provide a real world depiction of particle stability by imposing absolutely no simplifying assumption on the underlying PSO variant being investigated. This approach is utilized to identify a number of previously unknown stability criteria. This thesis also contains novel theoretical derivations of the stability criteria for both the fully informed PSO and the unified PSO. The theoretical models are then empirically validated utilizing the aforementioned empirical approach in an assumption free context. The thesis closes with a substantial theoretical extension of current PSO stability research. It is common practice within the existing theoretical PSO research to assume that, in the simplest case, the personal and neighborhood best positions are stagnant. However, in this thesis, stability criteria are derived under a mathematical model where by the personal best and neighborhood best positions are treated as convergent sequences of random variables. It is also proved that, in order to derive stability criteria, no weaker assumption on the behavior of the personal and neighborhood best positions can be made. The theoretical extension presented caters for a large range of PSO variants.

Download or read book Stochastic Global Optimization written by Gade Pandu Rangaiah and published by World Scientific. This book was released on 2010 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ch. 1. Introduction / Gade Pandu Rangaiah -- ch. 2. Formulation and illustration of Luus-Jaakola optimization procedure / Rein Luus -- ch. 3. Adaptive random search and simulated annealing optimizers : algorithms and application issues / Jacek M. Jezowski, Grzegorz Poplewski and Roman Bochenek -- ch. 4. Genetic algorithms in process engineering : developments and implementation issues / Abdunnaser Younes, Ali Elkamel and Shawki Areibi -- ch. 5. Tabu search for global optimization of problems having continuous variables / Sim Mong Kai, Gade Pandu Rangaiah and Mekapati Srinivas -- ch. 6. Differential evolution : method, developments and chemical engineering applications / Chen Shaoqiang, Gade Pandu Rangaiah and Mekapati Srinivas -- ch. 7. Ant colony optimization : details of algorithms suitable for process engineering / V.K. Jayaraman [und weitere] -- ch. 8. Particle swarm optimization for solving NLP and MINLP in chemical engineering / Bassem Jarboui [und weitere] -- ch. 9. An introduction to the harmony search algorithm / Gordon Ingram and Tonghua Zhang -- ch. 10. Meta-heuristics : evaluation and reporting techniques / Abdunnaser Younes, Ali Elkamel and Shawki Areibi -- ch. 11. A hybrid approach for constraint handling in MINLP optimization using stochastic algorithms / G.A. Durand [und weitere] -- ch. 12. Application of Luus-Jaakola optimization procedure to model reduction, parameter estimation and optimal control / Rein Luus -- ch. 13. Phase stability and equilibrium calculations in reactive systems using differential evolution and tabu search / Adrian Bonilla-Petriciolet [und weitere] -- ch. 14. Differential evolution with tabu list for global optimization : evaluation of two versions on benchmark and phase stability problems / Mekapati Srinivas and Gade Pandu Rangaiah -- ch. 15. Application of adaptive random search optimization for solving industrial water allocation problem / Grzegorz Poplewski and Jacek M. Jezowski -- ch. 16. Genetic algorithms formulation for retrofitting heat exchanger network / Roman Bochenek and Jacek M. Jezowski -- ch. 17. Ant colony optimization for classification and feature selection / V.K. Jayaraman [und weitere] -- ch. 18. Constraint programming and genetic algorithm / Prakash R. Kotecha, Mani Bhushan and Ravindra D. Gudi -- ch. 19. Schemes and implementations of parallel stochastic optimization algorithms application of tabu search to chemical engineering problems / B. Lin and D.C. Miller

Download or read book Swarm Intelligence Based Optimization written by Patrick Siarry and published by Springer. This book was released on 2014-11-27 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 1st International Conference on Swarm Intelligence Based Optimization, ICSIBO 2014, held in Mulhouse, France, in May 2014. The 20 full papers presented were carefully reviewed and selected from 48 submissions. Topics of interest presented and discussed in the conference focuses on the theoretical progress of swarm intelligence metaheuristics and their applications in areas such as: theoretical advances of swarm intelligence metaheuristics, combinatorial, discrete, binary, constrained, multi-objective, multi-modal, dynamic, noisy, and large-scale optimization, artificial immune systems, particle swarms, ant colony, bacterial foraging, artificial bees, fireflies algorithm, hybridization of algorithms, parallel/distributed computing, machine learning, data mining, data clustering, decision making and multi-agent systems based on swarm intelligence principles, adaptation and applications of swarm intelligence principles to real world problems in various domains.

Download or read book Nature Inspired Computation and Swarm Intelligence written by Xin-She Yang and published by Academic Press. This book was released on 2020-04-24 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence. Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others

Download or read book Computational Intelligence in Power Engineering written by Ajith Abraham and published by Springer. This book was released on 2010-09-08 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence (CI) is one of the most important powerful tools for research in the diverse fields of engineering sciences ranging from traditional fields of civil, mechanical engineering to vast sections of electrical, electronics and computer engineering and above all the biological and pharmaceutical sciences. The existing field has its origin in the functioning of the human brain in processing information, recognizing pattern, learning from observations and experiments, storing and retrieving information from memory, etc. In particular, the power industry being on the verge of epoch changing due to deregulation, the power engineers require Computational intelligence tools for proper planning, operation and control of the power system. Most of the CI tools are suitably formulated as some sort of optimization or decision making problems. These CI techniques provide the power utilities with innovative solutions for efficient analysis, optimal operation and control and intelligent decision making. This edited volume deals with different CI techniques for solving real world Power Industry problems. The technical contents will be extremely helpful for the researchers as well as the practicing engineers in the power industry.

Download or read book Encyclopedia of Machine Learning written by Claude Sammut and published by Springer Science & Business Media. This book was released on 2011-03-28 with total page 1061 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.

Download or read book New Optimization Techniques in Engineering written by Godfrey C. Onwubolu and published by Springer. This book was released on 2013-03-14 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presently, general-purpose optimization techniques such as Simulated Annealing, and Genetic Algorithms, have become standard optimization techniques. Concerted research efforts have been made recently in order to invent novel optimization techniques for solving real life problems, which have the attributes of memory update and population-based search solutions. The book describes a variety of these novel optimization techniques which in most cases outperform the standard optimization techniques in many application areas. New Optimization Techniques in Engineering reports applications and results of the novel optimization techniques considering a multitude of practical problems in the different engineering disciplines – presenting both the background of the subject area and the techniques for solving the problems.

Download or read book Small Signal Stability Modelling and Optimization of Microgrids written by Simon Eberlein and published by BoD – Books on Demand. This book was released on 2021-08-31 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: The stability of power systems and microgrids is compromised by the increasing penetration with power electronic devices, such as wind turbines, photovoltaics and batteries. A simulation and optimization environment for such low-inertia systems is created. It is investigated how accurate the models need to be to capture the prevailing modes. An evolutionary algorithm tailored to optimization problems with computationally intensive fitness evaluation is proposed in order to optimized the controller parameters of grid-forming and grid-supporting distributed generators. It becomes apparent that microgrids dominated by grid-forming inverters are very stable systems when well-designed and optimized controllers are used. Model simplifications, such as the neglect of inner control loops of inverters, must be examined carefully, as they can lead to an inaccurate stability assessment.