Results 271 to 280 of about 5,277,522 (305)
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Journal of Algorithms, 1993
Summary: Let \(\Gamma_ 0\) be a set of \(n\) halfspaces in \(E^ d\) (where the dimension \(d\) is fixed) and let \(m\) be a parameter, \(n\leq m\leq n^{\lfloor d/2\rfloor}\). We show that \(\Gamma_ 0\) can be preprocessed in time and space \(0(m^{1+\delta}\)) (for any fixed \(\delta>0\)) so that given a vector \(c\in E^ d\) and another set \(\Gamma_ q\)
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Summary: Let \(\Gamma_ 0\) be a set of \(n\) halfspaces in \(E^ d\) (where the dimension \(d\) is fixed) and let \(m\) be a parameter, \(n\leq m\leq n^{\lfloor d/2\rfloor}\). We show that \(\Gamma_ 0\) can be preprocessed in time and space \(0(m^{1+\delta}\)) (for any fixed \(\delta>0\)) so that given a vector \(c\in E^ d\) and another set \(\Gamma_ q\)
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Computing, 1980
Two methods for solving an optimization problem with piecewise linear, convex, and continuous objective function and linear restrictions are described. The first one represents a generalization of the ordinary Simplex-Algorithm by Dantzig, the second one an adaptation of the Reduced Gradient Method by P. Wolfe to the discussed problem.
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Two methods for solving an optimization problem with piecewise linear, convex, and continuous objective function and linear restrictions are described. The first one represents a generalization of the ordinary Simplex-Algorithm by Dantzig, the second one an adaptation of the Reduced Gradient Method by P. Wolfe to the discussed problem.
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Optimal Linearization in Holography
Applied Optics, 1969Optimal linearization in holography is studied from the nonlinear system theory point of view. A generalized optimal linearization method for a physical photographic emulsion is presented. A generalized first-order amplitude transmittance (i.e., the generalized transfer function) with respect to the input irradiance is determined.
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Abstract Optimal Linear Filtering
SIAM Journal on Control and Optimization, 2000The linear optimal filtering problems in infinite-dimensional Hilbert spaces and their extensions are investigated. The quality functional is allowed to be a general quadratic functional defined by a possibly degenerate operator. The solutions of the stable and the causal filtering problems are obtained.
Vladimir N. Fomin, Michael V. Ruzhansky
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LINEAR SCHEDULING IS NEARLY OPTIMAL
Parallel Processing Letters, 1991This paper deals with the problem of finding optimal schedulings for uniform dependence algorithms. Given a convex domain, let Tf be the total time needed to execute all computations using the free (greedy) schedule and let Tl be the total time needed to execute all computations using the optimal linear schedule.
Darte, Alain +2 more
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10 optimizations on linear search
Communications of the ACM, 2016The operations side of the story.
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Linear and Integer Linear Optimization
1999This is a textbook about linear and integer linear optimization. The major goal is to develop the theory of linear and integer linear optimization in a unified manner and then demonstrate how to use this theory to solve very large real world problems.
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1994
Abstract Optimization is itself a large area within the field of applied mathematics. It deals with the minimization and maximization of functions with or without constraints and has many different applications. A large number of these applications belong to the area of operations research within the economic sciences.
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Abstract Optimization is itself a large area within the field of applied mathematics. It deals with the minimization and maximization of functions with or without constraints and has many different applications. A large number of these applications belong to the area of operations research within the economic sciences.
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An Interval Sequential Linear Programming for Nonlinear Robust Optimization Problems
Applied Mathematical Modelling, 2022Jiachang Tang, Chengji Mi, Haibo Liu
exaly