Distributed Computing And Optimization Techniques

Download or read book Optimization Techniques for Solving Complex Problems written by Enrique Alba and published by John Wiley & Sons. This book was released on 2009-03-23 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-world problems and modern optimization techniques to solve them Here, a team of international experts brings together core ideas for solving complex problems in optimization across a wide variety of real-world settings, including computer science, engineering, transportation, telecommunications, and bioinformatics. Part One—covers methodologies for complex problem solving including genetic programming, neural networks, genetic algorithms, hybrid evolutionary algorithms, and more. Part Two—delves into applications including DNA sequencing and reconstruction, location of antennae in telecommunication networks, metaheuristics, FPGAs, problems arising in telecommunication networks, image processing, time series prediction, and more. All chapters contain examples that illustrate the applications themselves as well as the actual performance of the algorithms.?Optimization Techniques for Solving Complex Problems is a valuable resource for practitioners and researchers who work with optimization in real-world settings.

Download or read book Distributed Computing and Optimization Techniques written by Sudhan Majhi and published by Springer Nature. This book was released on 2022-09-12 with total page 855 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces research presented at the International Conference on Distributed Computing and Optimization Techniques (ICDCOT–2021), a two-day conference, where researchers, engineers, and academicians from all over the world came together to share their experiences and findings on all aspects of distributed computing and its applications in diverse areas. The book includes papers on distributed computing, intelligent system, optimization method, mathematical modeling, fuzzy logic, neural networks, grid computing, load balancing, communication. It will be a valuable resource for students, academics, and practitioners in the industry working on distributed computing.

Download or read book Parallel and Distributed Computation: Numerical Methods written by Dimitri Bertsekas and published by Athena Scientific. This book was released on 2015-03-01 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt: This highly acclaimed work, first published by Prentice Hall in 1989, is a comprehensive and theoretically sound treatment of parallel and distributed numerical methods. It focuses on algorithms that are naturally suited for massive parallelization, and it explores the fundamental convergence, rate of convergence, communication, and synchronization issues associated with such algorithms. This is an extensive book, which aside from its focus on parallel and distributed algorithms, contains a wealth of material on a broad variety of computation and optimization topics. It is an excellent supplement to several of our other books, including Convex Optimization Algorithms (Athena Scientific, 2015), Nonlinear Programming (Athena Scientific, 1999), Dynamic Programming and Optimal Control (Athena Scientific, 2012), Neuro-Dynamic Programming (Athena Scientific, 1996), and Network Optimization (Athena Scientific, 1998). The on-line edition of the book contains a 95-page solutions manual.

Download or read book Parallel Combinatorial Optimization written by El-Ghazali Talbi and published by John Wiley & Sons. This book was released on 2006-10-27 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse range of industries. Each chapter is written by leading experts in the fields of parallel and distributed optimization. Collectively, the contributions serve as a complete reference to the field of combinatorial optimization, including details and findings of recent and ongoing investigations.

Download or read book Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers written by Stephen Boyd and published by Now Publishers Inc. This book was released on 2011 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.

Download or read book Optimization Methods Applied to Power Systems written by Francisco G. Montoya and published by MDPI. This book was released on 2019-07-26 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.

Download or read book Concurrent and Distributed Computing in Java written by Vijay K. Garg and published by John Wiley & Sons. This book was released on 2005-01-28 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concurrent and Distributed Computing in Java addresses fundamental concepts in concurrent computing with Java examples. The book consists of two parts. The first part deals with techniques for programming in shared-memory based systems. The book covers concepts in Java such as threads, synchronized methods, waits, and notify to expose students to basic concepts for multi-threaded programming. It also includes algorithms for mutual exclusion, consensus, atomic objects, and wait-free data structures. The second part of the book deals with programming in a message-passing system. This part covers resource allocation problems, logical clocks, global property detection, leader election, message ordering, agreement algorithms, checkpointing, and message logging. Primarily a textbook for upper-level undergraduates and graduate students, this thorough treatment will also be of interest to professional programmers.