Download or read book Parallel Quasi newton Algorithms for Large scale Optimization written by National University of Singapore. Dept. of Information Systems and Computer Science and published by . This book was released on 1995 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Multi-step, multi-directional parallel quasi-Newton (QN) methods for unconstrained optimization problems are presented in this paper. These algorithms generate several QN directions at each iteration, different line search strategies are then applied in parallel along each search direction. Numerical experiments are carried out over a wide range of standard test functions. Computational results show that a reduction of 94% and 70% in the number of iterations and function/gradient evaluations respectively could be achieved by the new parallel algorithm. Furthermore, a speedup factor of 1.69 in CPU time could also be realized comparing with serial QN methods."
Download or read book A Parallel Quasi Newton Method for Partially Separable Large scale Minimization written by University of Illinois at Urbana-Champaign. Center for Supercomputing Research and Development and published by . This book was released on 1990 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "A simplified version of the parallel quasi-Newton method introduced in [ChHa88] for solving partially separable problems is proposed in this paper. The method is compared to the conventional BFGS method and to the quasi-Newton method with a partitioned BFGS updating scheme proposed in [GrTo81] [GrTo82a]; the results show this simplified version is not only economical in computer storage but also very efficient in solving large-scale partially separable problems. This algorithm has had some preliminary testing on an Alliant FX/8 minisupercomputer, and the results are reported."
Download or read book Quasi Newton Algorithms for Non smooth Online Strongly Convex Optimization written by Mark Franklin Godwin and published by . This book was released on 2011 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growing prevalence of networked systems with local sensing and computational capability will result in an increasing array of online and large scale optimization problems. We adopt the framework of online convex optimization that allows for the optimization of an arbitrary sequence of convex functions subject to a single convex constraint set. We identify quasi-Newton algorithms as a promising class of algorithms to solve online strongly convex optimization problems. We first examine the relationships between several known algorithms for convex functions that satisfy a [alpha]-exp-concave assumption. Next we present two new quasi-Newton algorithms for non-smooth strongly convex functions and show how these algorithms can be parallelized given a summed objective function. Our new algorithms require fewer parameters and have provably tighter bounds then similar known algorithms. Also, our bounds are not a function of the number of iterations, but instead a function of the sequence of strongly convex parameters that correspond to a sequence of strongly convex functions. We then extend these algorithms to use a block diagonal hessian approximation. An algorithm with a fully diagonal hessian approximation results in a large scale quasi-Newton algorithm for online convex optimization. Our results can be translated to convergence bounds and optimization algorithms that solve non-smooth strongly convex functions. We perform numerical experiments on test functions of different dimension and compare our algorithms to similar known algorithms. These experiments show our algorithms perform well in the majority of test cases we consider. We apply our algorithms to online portfolio optimization with a l2-norm regularized constant-rebalanced portfolio model and compare our algorithm to known methods. In addition, a heuristic algorithm for online vehicle routing is presented. Although online vehicle routing does not fit within the framework of online convex optimization, the work provided significant insight into online optimization and provides a future source of ideas and motivation. Finally, we provide conclusions and discuss future research directions.
Download or read book Parallel Optimization written by Yair Censor and published by Oxford University Press, USA. This book was released on 1997 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a unique pathway to methods of parallel optimization by introducing parallel computing ideas into both optimization theory and into some numerical algorithms for large-scale optimization problems. The three parts of the book bring together relevant theory, careful study of algorithms, and modeling of significant real world problems such as image reconstruction, radiation therapy treatment planning, financial planning, transportation and multi-commodity network flow problems, planning under uncertainty, and matrix balancing problems.
Download or read book Algorithms for Continuous Optimization written by E. Spedicato and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NATO Advanced Study Institute on "Algorithms for continuous optimiza tion: the state of the art" was held September 5-18, 1993, at II Ciocco, Barga, Italy. It was attended by 75 students (among them many well known specialists in optimiza tion) from the following countries: Belgium, Brasil, Canada, China, Czech Republic, France, Germany, Greece, Hungary, Italy, Poland, Portugal, Rumania, Spain, Turkey, UK, USA, Venezuela. The lectures were given by 17 well known specialists in the field, from Brasil, China, Germany, Italy, Portugal, Russia, Sweden, UK, USA. Solving continuous optimization problems is a fundamental task in computational mathematics for applications in areas of engineering, economics, chemistry, biology and so on. Most real problems are nonlinear and can be of quite large size. Devel oping efficient algorithms for continuous optimization has been an important field of research in the last 30 years, with much additional impetus provided in the last decade by the availability of very fast and parallel computers. Techniques, like the simplex method, that were already considered fully developed thirty years ago have been thoroughly revised and enormously improved. The aim of this ASI was to present the state of the art in this field. While not all important aspects could be covered in the fifty hours of lectures (for instance multiob jective optimization had to be skipped), we believe that most important topics were presented, many of them by scientists who greatly contributed to their development.
Download or read book Large scale Numerical Optimization written by Thomas Frederick Coleman and published by SIAM. This book was released on 1990-01-01 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers from a workshop held at Cornell University, Oct. 1989, and sponsored by Cornell's Mathematical Sciences Institute. Annotation copyright Book News, Inc. Portland, Or.
Download or read book Optimization Techniques And Applications Icota 95 written by G Z Liu and published by World Scientific. This book was released on 1995-09-01 with total page 1718 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent of powerful computers and novel mathematical programming techniques, the multidisciplinary field of optimization has advanced to the stage that quite complicated systems can be addressed. The conference was organized to provide a platform for the exchange of new ideas and information and for identifying needs for future research. The contributions covered both theoretical techniques and a rich variety of case studies to which optimization can be usefully applied.
Download or read book Large Scale Optimization with Applications written by and published by Springer Science & Business Media. This book was released on 1997 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Parallel Computing and Statistics written by Erricos John Kontoghiorghes and published by CRC Press. This book was released on 2005-12-21 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological improvements continue to push back the frontier of processor speed in modern computers. Unfortunately, the computational intensity demanded by modern research problems grows even faster. Parallel computing has emerged as the most successful bridge to this computational gap, and many popular solutions have emerged based on its concepts
Download or read book Preconditioning Subspace Quasi newton Method for Large Scale Unconstrained Optimization written by Hong Seng Sim and published by . This book was released on 2011 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Quasi Newton Algorithms for Large Scale Nonlinear Systems written by Dennis Jay VandenBrink and published by . This book was released on 1983 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Very Large Scale Computation in the 21st Century written by Jill P. Mesirov and published by SIAM. This book was released on 1991-01-01 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text on very large scale computation in the 21st century covers such topics as: challenges in the natural sciences and physics; chemistry; fluid dynamics; astrophysics; biology; challenges in engineering; challenges in algorithm design; and challenges in system design.
Download or read book Parallel Solution of Large scale Optimization Problems written by Robert Stephen Maier and published by . This book was released on 1990 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computational Science ICCS 2009 written by Gabrielle Allen and published by Springer. This book was released on 2009-05-20 with total page 1030 pages. Available in PDF, EPUB and Kindle. Book excerpt: “There is something fascinating about science. One gets such wholesale returns of conjecture out of such a tri?ing investment of fact. ” Mark Twain, Life on the Mississippi The challenges in succeeding with computational science are numerous and deeply a?ect all disciplines. NSF’s 2006 Blue Ribbon Panel of Simulation-Based 1 Engineering Science (SBES) states ‘researchers and educators [agree]: com- tational and simulation engineering sciences are fundamental to the security and welfare of the United States. . . We must overcome di?culties inherent in multiscale modeling, the development of next-generation algorithms, and the design. . . of dynamic data-driven application systems. . . We must determine better ways to integrate data-intensive computing, visualization, and simulation. - portantly,wemustoverhauloureducationalsystemtofostertheinterdisciplinary study. . . The payo?sformeeting these challengesareprofound. ’The International Conference on Computational Science 2009 (ICCS 2009) explored how com- tational sciences are not only advancing the traditional hard science disciplines, but also stretching beyond, with applications in the arts, humanities, media and all aspects of research. This interdisciplinary conference drew academic and industry leaders from a variety of ?elds, including physics, astronomy, mat- matics,music,digitalmedia,biologyandengineering. Theconferencealsohosted computer and computational scientists who are designing and building the - ber infrastructure necessary for next-generation computing. Discussions focused on innovative ways to collaborate and how computational science is changing the future of research. ICCS 2009: ‘Compute. Discover. Innovate. ’ was hosted by the Center for Computation and Technology at Louisiana State University in Baton Rouge.
Download or read book Parallel algorithms for large scale nonlinear optimization written by Kang Hoh Phua and published by . This book was released on 1996 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Multi-step, multi-directional parallel variable metric (PVM) methods for unconstrained optimization problems are presented in this paper. These algorithms generate several VM directions at each iteration, different line search and scaling strategies are then applied in parallel along each search direction. In comparison to some serial VM methods, computational results show that a reduction of 200% or more in terms of number of iterations and function/gradient evaluations respectively could be achieved by the new parallel algorithm over a wide range of 63 test problems. In particular, when the complexity, or the size of the problem increases, greater savings could be achieved by the proposed parallel algorithm. In fact, the speedup factors gained by our PVM algorithms could be as high as 28 times for some test problems."
Download or read book Iterative Methods for Optimization written by C. T. Kelley and published by SIAM. This book was released on 1999-01-01 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke-Jeeves, implicit filtering, MDS, and Nelder-Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages.
Download or read book Large Scale PDE Constrained Optimization written by Lorenz T. Biegler and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal design, optimal control, and parameter estimation of systems governed by partial differential equations (PDEs) give rise to a class of problems known as PDE-constrained optimization. The size and complexity of the discretized PDEs often pose significant challenges for contemporary optimization methods. With the maturing of technology for PDE simulation, interest has now increased in PDE-based optimization. The chapters in this volume collectively assess the state of the art in PDE-constrained optimization, identify challenges to optimization presented by modern highly parallel PDE simulation codes, and discuss promising algorithmic and software approaches for addressing them. These contributions represent current research of two strong scientific computing communities, in optimization and PDE simulation. This volume merges perspectives in these two different areas and identifies interesting open questions for further research.
