Designing Efficient And Accurate Parallel Genetic Algorithms PDF Download
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| Author | : Erick Cantú-Paz |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 171 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 146154369X |
Download Efficient and Accurate Parallel Genetic Algorithms Book in PDF, ePub and Kindle
As genetic algorithms (GAs) become increasingly popular, they are applied to difficult problems that may require considerable computations. In such cases, parallel implementations of GAs become necessary to reach high-quality solutions in reasonable times. But, even though their mechanics are simple, parallel GAs are complex non-linear algorithms that are controlled by many parameters, which are not well understood. Efficient and Accurate Parallel Genetic Algorithms is about the design of parallel GAs. It presents theoretical developments that improve our understanding of the effect of the algorithm's parameters on its search for quality and efficiency. These developments are used to formulate guidelines on how to choose the parameter values that minimize the execution time while consistently reaching solutions of high quality. Efficient and Accurate Parallel Genetic Algorithms can be read in several ways, depending on the readers' interests and their previous knowledge about these algorithms. Newcomers to the field will find the background material in each chapter useful to become acquainted with previous work, and to understand the problems that must be faced to design efficient and reliable algorithms. Potential users of parallel GAs that may have doubts about their practicality or reliability may be more confident after reading this book and understanding the algorithms better. Those who are ready to try a parallel GA on their applications may choose to skim through the background material, and use the results directly without following the derivations in detail. These readers will find that using the results can help them to choose the type of parallel GA that best suits their needs, without having to invest the time to implement and test various options. Once that is settled, even the most experienced users dread the long and frustrating experience of configuring their algorithms by trial and error. The guidelines contained herein will shorten dramatically the time spent tweaking the algorithm, although some experimentation may still be needed for fine-tuning. Efficient and Accurate Parallel Genetic Algorithms is suitable as a secondary text for a graduate level course, and as a reference for researchers and practitioners in industry.
| Author | : Erick Cantu-Paz |
| Publisher | : |
| Total Pages | : 306 |
| Release | : 1999 |
| Genre | : |
| ISBN | : |
Download Designing Efficient and Accurate Parallel Genetic Algorithms Book in PDF, ePub and Kindle
| Author | : |
| Publisher | : |
| Total Pages | : |
| Release | : 1938 |
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Download Glada jul, härlige jul. 70 jullekar, julhymner och julsånger för piano Book in PDF, ePub and Kindle
| Author | : Gabriel Luque |
| Publisher | : Springer |
| Total Pages | : 173 |
| Release | : 2011-06-15 |
| Genre | : Technology & Engineering |
| ISBN | : 3642220843 |
Download Parallel Genetic Algorithms Book in PDF, ePub and Kindle
This book is the result of several years of research trying to better characterize parallel genetic algorithms (pGAs) as a powerful tool for optimization, search, and learning. Readers can learn how to solve complex tasks by reducing their high computational times. Dealing with two scientific fields (parallelism and GAs) is always difficult, and the book seeks at gracefully introducing from basic concepts to advanced topics. The presentation is structured in three parts. The first one is targeted to the algorithms themselves, discussing their components, the physical parallelism, and best practices in using and evaluating them. A second part deals with the theory for pGAs, with an eye on theory-to-practice issues. A final third part offers a very wide study of pGAs as practical problem solvers, addressing domains such as natural language processing, circuits design, scheduling, and genomics. This volume will be helpful both for researchers and practitioners. The first part shows pGAs to either beginners and mature researchers looking for a unified view of the two fields: GAs and parallelism. The second part partially solves (and also opens) new investigation lines in theory of pGAs. The third part can be accessed independently for readers interested in applications. The result is an excellent source of information on the state of the art and future developments in parallel GAs.
| Author | : David E. Goldberg |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 259 |
| Release | : 2013-03-14 |
| Genre | : Computers |
| ISBN | : 1475736436 |
Download The Design of Innovation Book in PDF, ePub and Kindle
7 69 6 A DESIGN APPROACH TO PROBLEM DIFFICULTY 71 1 Design and Problem Difficulty 71 2 Three Misconceptions 72 3 Hard Problems Exist 76 4 The 3-Way Decomposition and Its Core 77 The Core of Intra-BB Difficulty: Deception 5 77 6 The Core of Inter-BB Difficulty: Scaling 83 7 The Core of Extra-BB Difficulty: Noise 88 Crosstalk: All Roads Lead to the Core 8 89 9 From Multimodality to Hierarchy 93 10 Summary 100 7 ENSURING BUILDING BLOCK SUPPLY 101 1 Past Work 101 2 Facetwise Supply Model I: One BB 102 Facetwise Supply Model II: Partition Success 103 3 4 Population Size for BB Supply 104 Summary 5 106 8 ENSURING BUILDING BLOCK GROWTH 109 1 The Schema Theorem: BB Growth Bound 109 2 Schema Growth Somewhat More Generally 111 3 Designing for BB Market Share Growth 112 4 Selection Press ure for Early Success 114 5 Designing for Late in the Day 116 The Schema Theorem Works 6 118 A Demonstration of Selection Stall 7 119 Summary 122 8 9 MAKING TIME FOR BUILDING BLOCKS 125 1 Analysis of Selection Alone: Takeover Time 126 2 Drift: When Selection Chooses for No Reason 129 3 Convergence Times with Multiple BBs 132 4 A Time-Scales Derivation of Critical Locus 142 5 A Little Model of Noise-Induced Run Elongation 143 6 From Alleles to Building Blocks 147 7 Summary 148 10 DECIDING WELL 151 1 Why is Decision Making a Problem? 151
| Author | : I.C. Parmee |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 385 |
| Release | : 2011-06-27 |
| Genre | : Computers |
| ISBN | : 0857293389 |
Download Adaptive Computing in Design and Manufacture VI Book in PDF, ePub and Kindle
The Adaptive Computing in Design and Manufacture conference series has become a well-established, largely application-oriented meeting recognised by several UK Engineering Institutions and the International Society of Genetic and Evolutionary Computing. The main theme of the series relates to the integration of evolutionary and adaptive computing technologies with design and manufacturing processes whilst also taking into account complementary advanced computing technologies. Evolutionary and adaptive computing techniques continue to increase their penetration of industrial and commercial practice as awareness of their powerful search, exploration and optimisation capabilities becomes ever more prevalent, and increasing desk-top computational capability renders stochastic population-based search a far more viable proposition. There has been a significant increase in the development and integration of commercial software tools utilising adaptive computing technologies and the emergence of related commercial research and consultancy organisations supporting the introduction of best practice in terms of industrial utilisation. The book is comprised of selected papers that cover a diverse set of industrial application areas including engineering design and design environments and manufacturing process design, scheduling and control. Various aspects of search, exploration and optimisation are investigated in the context of integration with industrial processes including multi-objective and constraint satisfaction, development and utilization of meta-models, algorithm and strategy development and human-centric evolutionary approaches. The role of agent-based and neural net technologies in terms of supporting search processes and providing an alternative simulation environment is also explored. This collection of papers will be of particular interest to both industrial researchers and practitioners in addition to the academic research communities across engineering, operational research and computer science.
| Author | : Raj Subbu |
| Publisher | : World Scientific |
| Total Pages | : 193 |
| Release | : 2004 |
| Genre | : Computers |
| ISBN | : 9812794859 |
Download Network-based Distributed Planning Using Coevolutionary Algorithms Book in PDF, ePub and Kindle
In this book, efficient and scalable coevolutionary algorithms for distributed, network-based decision-making, which utilize objective functions are developed in a networked environment where internode communications are a primary factor in system performance. A theoretical foundation for this class of coevolutionary algorithms is introduced using techniques from stochastic process theory and mathematical analysis. A case study in distributed, network-based decision-making presents an implementation and detailed evaluation of the coevolutionary decision-making framework that incorporates distributed evolutionary agents and mobile agents. The methodology discussed in this book can have a fundamental impact on the principles and practice of engineering in the distributed, network-based environment that is emerging within and among corporate enterprise systems. In addition, the conceptual framework of the approach to distributed decision systems described may have much wider implications for network-based systems and applications. Contents: Background and Related Work; Problem Formulation and Analysis; Theory and Analysis of Evolutionary Optimization; Theory and Analysis of Distributed Coevolutionary Optimization; Performance Evaluation Based on Ideal Objectives; Coevolutionary Virtual Design Environment; Evaluation and Analysis. Readership: Researchers and engineers in artificial intelligence, evolutionary computation and decision sciences.
| Author | : Nadia Nedjah |
| Publisher | : Nova Publishers |
| Total Pages | : 250 |
| Release | : 2005 |
| Genre | : Computers |
| ISBN | : 9781594544057 |
Download Evolutionary Machine Design Book in PDF, ePub and Kindle
In recent years, genetic programming has attracted many researcher's attention and so became a consolidated methodology to automatically create new competitive computer programs. Concise and efficient synthesis of a variety of systems has been generated by evolutionary computations. Evolvable hardware is a growing discipline. It allows one to evolve creative and novel hardware architectures given the expected input/output behaviour. There are two kinds of evolvable hardware: extrinsic and intrinsic. The former relies on a simulated evolutionary process to evaluate the characteristics of the evolved designs while the latter uses hardware itself to do so. Usually, reconfigurable hardware such FPGA and FPAA are exploited. One of the main problems that still faces researchers in the field of evolutionary machine design is the scalability. This book is devoted to reporting innovative and significant progress in automatic machine design. Theoretical as well as practical chapters are contemplated. The scalability problem in evolutionary machine designs is addresses. The content of this book is divided into two main parts: evolvable hardware and genetic programming; and evolutionary designs. In the following, we give a brief description of the main contribution of each of the included chapters.
| Author | : Janusz Kacprzyk |
| Publisher | : Springer |
| Total Pages | : 1637 |
| Release | : 2015-05-28 |
| Genre | : Technology & Engineering |
| ISBN | : 3662435055 |
Download Springer Handbook of Computational Intelligence Book in PDF, ePub and Kindle
The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.
| Author | : Ajith Abraham |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 326 |
| Release | : 2005-04-22 |
| Genre | : Computers |
| ISBN | : 9781852337872 |
Download Evolutionary Multiobjective Optimization Book in PDF, ePub and Kindle
Evolutionary Multi-Objective Optimization is an expanding field of research. This book brings a collection of papers with some of the most recent advances in this field. The topic and content is currently very fashionable and has immense potential for practical applications and includes contributions from leading researchers in the field. Assembled in a compelling and well-organised fashion, Evolutionary Computation Based Multi-Criteria Optimization will prove beneficial for both academic and industrial scientists and engineers engaged in research and development and application of evolutionary algorithm based MCO. Packed with must-find information, this book is the first to comprehensively and clearly address the issue of evolutionary computation based MCO, and is an essential read for any researcher or practitioner of the technique.
