Applied Algebra, Algebraic Algorithms and Error-Correcting Codes: 12th International Symposium, AAECC-12, Toulouse, France, June, 23-27, 1997, Proceedings (Lecture Notes in Computer Science)
This book constitutes the strictly refereed proceedings of the 12th International Symposium on Applied Algebra, Algebraic Algorithms and Error-Correcting Codes, AAECC-12, held in Toulouse, France, June 1997.
The 27 revised full papers presented were carefully selected by the program committee for inclusion in the volume. The papers address a broad range of current issues in coding theory and computer algebra spanning polynomials, factorization, commutative algebra, real geometry, group theory, etc. on the mathematical side as well as software systems, telecommunication, complexity theory, compression, signal processing, etc. on the computer science and engineering side.
Sunday, June 7, 2009
Applied Algebra, Algebraic Algorithms and Error-Correcting Codes: 12th International Symposium, AAECC-12, Toulouse, France, June, 23-27, 1997, Proceed
Feasibility and Infeasibility in Optimization:: Algorithms and Computational Methods (International Series in Operations Research & Management Science
Constrained optimization models are core tools in business, science, government, and the military with applications including airline scheduling, control of petroleum refining operations, investment decisions, and many others. Constrained optimization models have grown immensely in scale and complexity in recent years as inexpensive computing power has become widely available. Models now frequently have many complicated interacting constraints, giving rise to a host of issues related to feasibility and infeasibility. For example, it is sometimes difficult to find any feasible point at all for a large model, or even to accurately determine if one exists, e.g. for nonlinear models. If the model is feasible, how quickly can a solution be found? If the model is infeasible, how can the cause be isolated and diagnosed? Can a repair to restore feasibility be carried out automatically? Researchers have developed numerous algorithms and computational methods in recent years to address such issues, with a number of surprising spin-off applications in fields such as artificial intelligence and computational biology. Over the same time period, related approaches and techniques relating to feasibility and infeasibility of constrained problems have arisen in the constraint programming community.
Feasibility and Infeasibility in Optimization is a timely expository book that summarizes the state of the art in both classical and recent algorithms related to feasibility and infeasibility in optimization, with a focus on practical methods. All model forms are covered, including linear, nonlinear, and mixed-integer programs. Connections to related work in constraint programming are shown. Part I of the book addresses algorithms for seeking feasibility quickly, including new methods for the difficult cases of nonlinear and mixed-integer programs. Part II provides algorithms for analyzing infeasibility by isolating minimal infeasible (or maximum feasible) subsets of constraints, or by finding the best repair for the infeasibility. Infeasibility analysis algorithms have arisen primarily over the last two decades, and the book covers these in depth and detail. Part III describes applications in numerous areas outside of direct infeasibility analysis such as finding decision trees for data classification, analyzing protein folding, radiation treatment planning, automated test assembly, etc.
A main goal of the book is to impart an understanding of the methods so that practitioners can make immediate use of existing algorithms and software, and so that researchers can extend the state of the art and find new applications. The book is of interest to researchers, students, and practitioners across the applied sciences who are working on optimization problems.
Computer Algorithms: Introduction to Design and Analysis (Addison-Wesley Series in Computer Science)
Computer Algorithms: Introduction to Design and Analysis (Addison-Wesley Series in Computer Science)
Drawing upon combined decades of teaching experience, Professors Sara Baase and Allen Van Gelder have extensively revised this best seller on algorithm design and analysis to make it the most current and accessible book available. This edition features an increased emphasis on algorithm design techniques such as divide-and-conquer and greedy algorithms, along with the addition of new topics and exercises. It continues the tradition of solid mathematical analysis and clear writing style that made it so popular in previous editions.
Customer Review: poorly executed text
This textbook is a mess. It is not elegant or clear, and their coverage of certain topics is confusing and deviates from standard practice. If your algorithms class is using this text, find some friends to pool together and get a copy for the exercises if they are used, otherwise take the book from MIT by Rivest et al out of the library and read that.
Introduction to Algorithms
Customer Review: Worst book I ever read
I would have rated "0 stars " if poosible in the selection.
Since this is the textbook for my course I have to deal with this book. The way things are mentioned in this book I doubt whether the authors have even understood the concepts right. I think that the authors themselves are confused while writing this book.
If this book is for your course, drop the course before it is too late.
