Multi Objective Swarm Intelligent Systems
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Author | : Leandro dos Santos Coelho |
Publisher | : Springer Science & Business Media |
Total Pages | : 228 |
Release | : 2009-11-19 |
Genre | : Computers |
ISBN | : 3642051642 |
This book covers the latest in multi-objective swarm intelligence and cooperative behavior. It contains innovative and intriguing applications as well as additions to the methodology and theory of genetic programming.
Author | : Carlos Coello Coello |
Publisher | : Springer Science & Business Media |
Total Pages | : 296 |
Release | : 2009-09-28 |
Genre | : Mathematics |
ISBN | : 3642036244 |
The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining.
Author | : Seyedali Mirjalili |
Publisher | : Springer |
Total Pages | : 58 |
Release | : 2019-07-24 |
Genre | : Technology & Engineering |
ISBN | : 3030248356 |
This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.
Author | : Thu Bui, Lam |
Publisher | : IGI Global |
Total Pages | : 496 |
Release | : 2008-05-31 |
Genre | : Technology & Engineering |
ISBN | : 1599045001 |
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.
Author | : Khosrow-Pour, D.B.A., Mehdi |
Publisher | : IGI Global |
Total Pages | : 1456 |
Release | : 2018-09-28 |
Genre | : Computers |
ISBN | : 1522573690 |
As modern technologies continue to develop and evolve, the ability of users to adapt with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies through artificial intelligence and computer simulation is necessary to fully realize the potential of tools in the 21st century. Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction provides emerging research in advanced trends in robotics, AI, simulation, and human-computer interaction. Readers will learn about the positive applications of artificial intelligence and human-computer interaction in various disciples such as business and medicine. This book is a valuable resource for IT professionals, researchers, computer scientists, and researchers invested in assistive technologies, artificial intelligence, robotics, and computer simulation.
Author | : Bijaya Ketan Panigrahi |
Publisher | : Springer Science & Business Media |
Total Pages | : 538 |
Release | : 2011-02-04 |
Genre | : Technology & Engineering |
ISBN | : 364217390X |
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.
Author | : Janga Reddy Manne |
Publisher | : LAP Lambert Academic Publishing |
Total Pages | : 284 |
Release | : 2010 |
Genre | : Artificial intelligence |
ISBN | : 9783838302201 |
Traditional optimization methods are no longer adequate to solve complex real life problems, as most of them involve nonlinear, discontinuous, non- differentiable, nonconvex, multiobjective functions with mixed variables in their model formulation. Over the last few years, the use of nature inspired meta-heuristic algorithms for systems optimization has increased tremendously, and "swarm intelligence and evolutionary computing techniques" are rapidly emerging as powerful tools for solving practical problems. This book describes efficient computational techniques based on Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Differential Evolution (DE) principles for single and multiple criterion optimization; and hybrid soft-computing techniques such as PSO Neural Network (PSO-NN), Adaptive Network Fuzzy Inference System (ANFIS) for hydrologic forecasting and demonstrates their applications to case studies in reservoir systems operation. This book is intended for people who are willing to learn new technology to solve complex real life problems and especially useful to professional in water resources field.
Author | : Patrick Siarry |
Publisher | : Springer |
Total Pages | : 202 |
Release | : 2014-11-27 |
Genre | : Computers |
ISBN | : 3319129708 |
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.
Author | : Patrick Siarry |
Publisher | : Springer |
Total Pages | : 132 |
Release | : 2016-11-25 |
Genre | : Computers |
ISBN | : 3319503073 |
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Conference on Swarm Intelligence Based Optimization, ICSIBO 2016, held in Mulhouse, France, in June 2016. The 9 full papers presented were carefully reviewed and selected from 20 submissions. They are centered around the following topics: 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 forging, 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.
Author | : Satchidananda Dehuri |
Publisher | : |
Total Pages | : |
Release | : 2015 |
Genre | : |
ISBN | : 9783662463109 |
The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO. .