Download or read book A Meta parallel Evolutionary System for Solving Optimization Problems written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Parallel Metaheuristics written by Enrique Alba and published by John Wiley & Sons. This book was released on 2005-10-03 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving complex optimization problems with parallel metaheuristics Parallel Metaheuristics brings together an international group of experts in parallelism and metaheuristics to provide a much-needed synthesis of these two fields. Readers discover how metaheuristic techniques can provide useful and practical solutions for a wide range of problems and application domains, with an emphasis on the fields of telecommunications and bioinformatics. This volume fills a long-existing gap, allowing researchers and practitioners to develop efficient metaheuristic algorithms to find solutions. The book is divided into three parts: * Part One: Introduction to Metaheuristics and Parallelism, including an Introduction to Metaheuristic Techniques, Measuring the Performance of Parallel Metaheuristics, New Technologies in Parallelism, and a head-to-head discussion on Metaheuristics and Parallelism * Part Two: Parallel Metaheuristic Models, including Parallel Genetic Algorithms, Parallel Genetic Programming, Parallel Evolution Strategies, Parallel Ant Colony Algorithms, Parallel Estimation of Distribution Algorithms, Parallel Scatter Search, Parallel Variable Neighborhood Search, Parallel Simulated Annealing, Parallel Tabu Search, Parallel GRASP, Parallel Hybrid Metaheuristics, Parallel Multi-Objective Optimization, and Parallel Heterogeneous Metaheuristics * Part Three: Theory and Applications, including Theory of Parallel Genetic Algorithms, Parallel Metaheuristics Applications, Parallel Metaheuristics in Telecommunications, and a final chapter on Bioinformatics and Parallel Metaheuristics Each self-contained chapter begins with clear overviews and introductions that bring the reader up to speed, describes basic techniques, and ends with a reference list for further study. Packed with numerous tables and figures to illustrate the complex theory and processes, this comprehensive volume also includes numerous practical real-world optimization problems and their solutions. This is essential reading for students and researchers in computer science, mathematics, and engineering who deal with parallelism, metaheuristics, and optimization in general.

Download or read book Optimization Using Evolutionary Algorithms and Metaheuristics written by Kaushik Kumar and published by CRC Press. This book was released on 2019-08-22 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metaheuristic optimization is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity. This is usually applied when two or more objectives are to be optimized simultaneously. This book is presented with two major objectives. Firstly, it features chapters by eminent researchers in the field providing the readers about the current status of the subject. Secondly, algorithm-based optimization or advanced optimization techniques, which are applied to mostly non-engineering problems, are applied to engineering problems. This book will also serve as an aid to both research and industry. Usage of these methodologies would enable the improvement in engineering and manufacturing technology and support an organization in this era of low product life cycle. Features: Covers the application of recent and new algorithms Focuses on the development aspects such as including surrogate modeling, parallelization, game theory, and hybridization Presents the advances of engineering applications for both single-objective and multi-objective optimization problems Offers recent developments from a variety of engineering fields Discusses Optimization using Evolutionary Algorithms and Metaheuristics applications in engineering

Download or read book Parallel Problem Solving from Nature PPSN XII written by Carlos Coello Coello and published by Springer. This book was released on 2012-08-27 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set LNCS 7491 and 7492 constitutes the refereed proceedings of the 12th International Conference on Parallel Problem Solving from Nature, PPSN 2012, held in Taormina, Sicily, Italy, in September 2012. The total of 105 revised full papers were carefully reviewed and selected from 226 submissions. The meeting began with 5 workshops which offered an ideal opportunity to explore specific topics in evolutionary computation, bio-inspired computing and metaheuristics. PPSN 2012 also included 8 tutorials. The papers are organized in topical sections on evolutionary computation; machine learning, classifier systems, image processing; experimental analysis, encoding, EDA, GP; multiobjective optimization; swarm intelligence, collective behavior, coevolution and robotics; memetic algorithms, hybridized techniques, meta and hyperheuristics; and applications.

Download or read book Metaheuristics written by El-Ghazali Talbi and published by John Wiley & Sons. This book was released on 2009-05-27 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

Download or read book Parallel Problem Solving from Nature PPSN XII written by Carlos Coello Coello and published by Springer. This book was released on 2012-08-27 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set LNCS 7491 and 7492 constitutes the refereed proceedings of the 12th International Conference on Parallel Problem Solving from Nature, PPSN 2012, held in Taormina, Sicily, Italy, in September 2012. The total of 105 revised full papers were carefully reviewed and selected from 226 submissions. The meeting began with 6 workshops which offered an ideal opportunity to explore specific topics in evolutionary computation, bio-inspired computing and metaheuristics. PPSN 2012 also included 8 tutorials. The papers are organized in topical sections on evolutionary computation; machine learning, classifier systems, image processing; experimental analysis, encoding, EDA, GP; multiobjective optimization; swarm intelligence, collective behavior, coevolution and robotics; memetic algorithms, hybridized techniques, meta and hyperheuristics; and applications.

Download or read book Evolutionary Multi Agent Systems written by Aleksander Byrski and published by Springer. This book was released on 2016-12-21 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses agent-based computing, concentrating in particular on evolutionary multi-agent systems (EMAS), which have been developed since 1996 at the AGH University of Science and Technology in Cracow, Poland. It provides the relevant background information on and a detailed description of this computing paradigm, along with key experimental results. Readers will benefit from the insightful discussion, which primarily concerns the efficient implementation of computing frameworks for developing EMAS and similar computing systems, as well as a detailed formal model. Theoretical deliberations demonstrating that computing with EMAS always helps to find the optimal solution are also included, rounding out the coverage.

Download or read book Parallel Problem Solving from Nature PPSN XIV written by Julia Handl and published by Springer. This book was released on 2016-08-30 with total page 1033 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.

Download or read book Parallel Problem Solving from Nature PPSN VI written by Marc Schoenauer and published by Springer Science & Business Media. This book was released on 2000-09-06 with total page 920 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Parallel Problem Solving from Nature, PPSN VI, held in Paris, France in September 2000. The 87 revised full papers presented together with two invited papers were carefully reviewed and selected from 168 submissions. The presentations are organized in topical sections on analysis and theory of evolutionary algorithms, genetic programming, scheduling, representations and operators, co-evolution, constraint handling techniques, noisy and non-stationary environments, combinatorial optimization, applications, machine learning and classifier systems, new algorithms and metaphors, and multiobjective optimization.

Download or read book Advances in Evolutionary and Deterministic Methods for Design Optimization and Control in Engineering and Sciences written by Edmondo Minisci and published by Springer. This book was released on 2018-07-02 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents up-to-date material on the state of the art in evolutionary and deterministic methods for design, optimization and control with applications to industrial and societal problems from Europe, Asia, and America. EUROGEN 2015 was the 11th of a series of International Conferences devoted to bringing together specialists from universities, research institutions and industries developing or applying evolutionary and deterministic methods in design optimization, with emphasis on solving industrial and societal problems. The conference was organised around a number of parallel symposia, regular sessions, and keynote lectures focused on surrogate-based optimization in aerodynamic design, adjoint methods for steady & unsteady optimization, multi-disciplinary design optimization, holistic optimization in marine design, game strategies combined with evolutionary computation, optimization under uncertainty, topology optimization, optimal planning, shape optimization, and production scheduling.

Download or read book Evolutionary Algorithms for Solving Multi Objective Problems written by Carlos A. Coello Coello and published by Springer Science & Business Media. This book was released on 2002 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: The solving of multi-objective problems (MOPs) has been a continuing effort by humans in many diverse areas, including computer science, engineering, economics, finance, industry, physics, chemistry, and ecology, among others. Many powerful and deterministic and stochastic techniques for solving these large dimensional optimization problems have risen out of operations research, decision science, engineering, computer science and other related disciplines. The explosion in computing power continues to arouse extraordinary interest in stochastic search algorithms that require high computational speed and very large memories. A generic stochastic approach is that of evolutionary algorithms (EA). Such algorithms have been demonstrated to be very powerful and generally applicable for solving different single objective problems. Their fundamental algorithmic structures can also be applied to solving many multi-objective problems. In this book, the various features of multi-objective evolutionary algorithms (MOEAs) are presented in an innovative and unique fashion, with detailed customized forms suggested for a variety of applications. Also, extensive MOEA discussion questions and possible research directions are presented at the end of each chapter. For additional information and supplementary teaching materials, please visit the authors' website at http://www.cs.cinvestav.mx/~EVOCINV/bookinfo.html.

Download or read book Evolutionary Optimization written by Ruhul Sarker and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques can deal with complex optimization problems better than traditional optimization techniques. However, most papers on the application of evolutionary computation techniques to Operations Research /Management Science (OR/MS) problems have scattered around in different journals and conference proceedings. They also tend to focus on a very special and narrow topic. It is the right time that an archival book series publishes a special volume which - cludes critical reviews of the state-of-art of those evolutionary com- tation techniques which have been found particularly useful for OR/MS problems, and a collection of papers which represent the latest devel- ment in tackling various OR/MS problems by evolutionary computation techniques. This special volume of the book series on Evolutionary - timization aims at filling in this gap in the current literature. The special volume consists of invited papers written by leading - searchers in the field. All papers were peer reviewed by at least two recognised reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.

Download or read book Meta Heuristics written by Ibrahim H. Osman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-heuristics have developed dramatically since their inception in the early 1980s. They have had widespread success in attacking a variety of practical and difficult combinatorial optimization problems. These families of approaches include, but are not limited to greedy random adaptive search procedures, genetic algorithms, problem-space search, neural networks, simulated annealing, tabu search, threshold algorithms, and their hybrids. They incorporate concepts based on biological evolution, intelligent problem solving, mathematical and physical sciences, nervous systems, and statistical mechanics. Since the 1980s, a great deal of effort has been invested in the field of combinatorial optimization theory in which heuristic algorithms have become an important area of research and applications. This volume is drawn from the first conference on Meta-Heuristics and contains 41 papers on the state-of-the-art in heuristic theory and applications. The book treats the following meta-heuristics and applications: Genetic Algorithms, Simulated Annealing, Tabu Search, Networks & Graphs, Scheduling and Control, TSP, and Vehicle Routing Problems. It represents research from the fields of Operations Research, Management Science, Artificial Intelligence and Computer Science.

Download or read book Evolutionary Multi Criterion Optimization written by Heike Trautmann and published by Springer. This book was released on 2017-02-17 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017 held in Münster, Germany in March 2017. The 33 revised full papers presented together with 13 poster presentations were carefully reviewed and selected from 72 submissions. The EMO 2017 aims to discuss all aspects of EMO development and deployment, including theoretical foundations; constraint handling techniques; preference handling techniques; handling of continuous, combinatorial or mixed-integer problems; local search techniques; hybrid approaches; stopping criteria; parallel EMO models; performance evaluation; test functions and benchmark problems; algorithm selection approaches; many-objective optimization; large scale optimization; real-world applications; EMO algorithm implementations.

Download or read book A Brief Introduction to Continuous Evolutionary Optimization written by Oliver Kramer and published by Springer Science & Business Media. This book was released on 2013-12-04 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the problem is available except via function evaluations. This work introduces a collection of heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. The book gives an introduction to evolution strategies and parameter control. Heuristic extensions are presented that allow optimization in constrained, multimodal and multi-objective solution spaces. An adaptive penalty function is introduced for constrained optimization. Meta-models reduce the number of fitness and constraint function calls in expensive optimization problems. The hybridization of evolution strategies with local search allows fast optimization in solution spaces with many local optima. A selection operator based on reference lines in objective space is introduced to optimize multiple conflictive objectives. Evolutionary search is employed for learning kernel parameters of the Nadaraya-Watson estimator and a swarm-based iterative approach is presented for optimizing latent points in dimensionality reduction problems. Experiments on typical benchmark problems as well as numerous figures and diagrams illustrate the behavior of the introduced concepts and methods.

Download or read book Parallel Problem Solving from Nature PPSN III written by Yuval Davidor and published by Springer. This book was released on 1994-09-21 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume comprises the 61 revised refereed papers accepted for presentation at the ICEC/PPSN III conferences held jointly in Jerusalem, Israel in October 1994. With the appearance of more and more powerful computers, there is increased interest in algorithms relying upon analogies to natural processes. This book presents a wealth of new theoretical and experimental results on artificial problem solving by applying evolutionary computation metaphors, including evolution strategies, evolutionary programming, genetic algorithms, genetic programming, and classifier systems. Topics such as simulated annealing, immune networks, neural networks, fuzzy systems, and complex, real-world optimization problems are also treated.

Download or read book Evolutionary Multi Criterion Optimization written by Ricardo H.C. Takahashi and published by Springer. This book was released on 2011-03-25 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2011, held in Ouro Preto, Brazil, in April 2011. The 42 revised full papers presented were carefully reviewed and selected from 83 submissions. The papers deal with fundamental questions of EMO theory, such as the development of algorithmically efficient tools for the evaluation of solution-set quality , the theoretical questions related to solution archiving and others. They report on the continuing effort in the development of algorithms, either for dealing with particular classes of problems or for new forms of processing the problem information. Almost one third of the papers is related to EMO applications in a diversity of fields. Eleven papers are devoted to promote the interaction with the related field of Multi-Criterion Decision Making (MCDM).