"Linear programming attracted the interest of mathematicians during and after World War II when the first computers were constructed and methods for solving large linear programming problems were ...sought in connection with specific practical problems - for example, providing logistical support for the U.S. Armed Forces or modeling national economies. Early attempts to apply linear programming methods to solve practical problems failed to satisfy expectations. There were various reasons for the failure. One of them, which is the central topic of this book, was the inexactness of the data used to create the models. This phenomenon, inherent in most pratical problems, has been dealt with in several ways. At first, linear programming models used ""average"" values of inherently vague coefficients, but the optimal solutions of these models were not always optimal for the original problem itself. Later researchers developed the stochastic linear programming approach, but this too has its limitations. Recently, interest has been given to linear programming problems with data given as intervals, convex sets and/or fuzzy sets. The individual results of these studies have been promising, but the literature has not presented a unified theory. Linear Optimization Problems with Inexact Data attempts to present a comprehensive treatment of linear optimization with inexact data, summarizing existing results and presenting new ones within a unifying framework."
Who are computer hackers? What is free software? And what does the emergence of a community dedicated to the production of free and open source software--and to hacking as a technical, aesthetic, and ...moral project--reveal about the values of contemporary liberalism? Exploring the rise and political significance of the free and open source software (F/OSS) movement in the United States and Europe, Coding Freedom details the ethics behind hackers' devotion to F/OSS, the social codes that guide its production, and the political struggles through which hackers question the scope and direction of copyright and patent law. In telling the story of the F/OSS movement, the book unfolds a broader narrative involving computing, the politics of access, and intellectual property.
E. Gabriella Coleman tracks the ways in which hackers collaborate and examines passionate manifestos, hacker humor, free software project governance, and festive hacker conferences. Looking at the ways that hackers sustain their productive freedom, Coleman shows that these activists, driven by a commitment to their work, reformulate key ideals including free speech, transparency, and meritocracy, and refuse restrictive intellectual protections. Coleman demonstrates how hacking, so often marginalized or misunderstood, sheds light on the continuing relevance of liberalism in online collaboration.
Kalman filter, particle filter, IMM, PDA, ITS, random sets... The number of useful object-tracking methods is exploding. But how are they related? How do they help track everything from aircraft, ...missiles and extra-terrestrial objects to people and lymphocyte cells? How can they be adapted to novel applications? Fundamentals of Object Tracking tells you how. Starting with the generic object-tracking problem, it outlines the generic Bayesian solution. It then shows systematically how to formulate the major tracking problems – maneuvering, multiobject, clutter, out-of-sequence sensors – within this Bayesian framework and how to derive the standard tracking solutions. This structured approach makes very complex object-tracking algorithms accessible to the growing number of users working on real-world tracking problems and supports them in designing their own tracking filters under their unique application constraints. The book concludes with a chapter on issues critical to successful implementation of tracking algorithms, such as track initialization and merging.
Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such ...problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution.
The golden ticket Fortnow, Lance
2013., 20130327, 2013, 2013-03-27, c2013
eBook
The P-NP problem is the most important open problem in computer science, if not all of mathematics.The Golden Ticketprovides a nontechnical introduction to P-NP, its rich history, and its algorithmic ...implications for everything we do with computers and beyond. In this informative and entertaining book, Lance Fortnow traces how the problem arose during the Cold War on both sides of the Iron Curtain, and gives examples of the problem from a variety of disciplines, including economics, physics, and biology. He explores problems that capture the full difficulty of the P-NP dilemma, from discovering the shortest route through all the rides at Disney World to finding large groups of friends on Facebook. But difficulty also has its advantages. Hard problems allow us to safely conduct electronic commerce and maintain privacy in our online lives.
The Golden Ticketexplores what we truly can and cannot achieve computationally, describing the benefits and unexpected challenges of the P-NP problem.
We introduce a generalized value function of a mixed-integer program, which is simultaneously parameterized by its objective and right-hand side. We describe its fundamental properties, which we ...exploit through three algorithms to calculate it. We then show how this generalized value function can be used to reformulate two classes of mixed-integer optimization problems: two-stage stochastic mixed-integer programming and multifollower bilevel mixed-integer programming. For both of these problem classes, the generalized value function approach allows the solution of instances that are significantly larger than those solved in the literature in terms of the total number of variables and number of scenarios.
The two-volume open access book set LNCS 14576 + 14577 constitutes the proceedings of the 33rd European Symposium on Programming, ESOP 2024, which was held during April 6-11, 2024, in Luxemburg, as ...part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2024. The 25 full papers and 1 fresh perspective paper presented in these proceedings were carefully reviewed and selected from 72 submissions. The papers were organized in topical sections as follows: Part I: Effects and modal types; bidirectional typing and session types; dependent types; Part II: Quantum programming and domain-specific languages; verification; program analysis; abstract interpretation.
The two-volume open access book set LNCS 14576 + 14577 constitutes the proceedings of the 33rd European Symposium on Programming, ESOP 2024, which was held during April 6-11, 2024, in Luxemburg, as ...part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2024. The 25 full papers and 1 fresh perspective paper presented in these proceedings were carefully reviewed and selected from 72 submissions. The papers were organized in topical sections as follows: Part I: Effects and modal types; bidirectional typing and session types; dependent types; Part II: Quantum programming and domain-specific languages; verification; program analysis; abstract interpretation.
