Results 121 to 130 of about 25,302 (170)
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Greedy by Chance - Stochastic Greedy Algorithms

2010 Sixth International Conference on Autonomic and Autonomous Systems, 2010
For many complex combinatorial optimization problems, obtaining good solutions quickly is of value either by itself or as part of an exact algorithm. Greedy algorithms to obtain such solutions are known for many problems. In this paper we present stochastic greedy algorithms which are perturbed versions of standard greedy algorithms, and report on ...
Viswanathan Kodaganallur, Anup K. Sen
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The Thresholding Greedy Algorithm, Greedy Bases, and Duality

Constructive Approximation, 2003
Let \(X\) be a Banach space with a normalized basis \((e_n)\) and biorthogonal functionals \((e_n^*)\) and let \(x\in X\). Order the nonzero scalars \(e_n^*(x)\) by decreasing the modulus (if \(| e_n^*(x)| =| e_m^*(x)| \) and ...
Dilworth, S. J.   +3 more
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Greedy Algorithms

2021
Sachi Nandan Mohanty   +2 more
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THREE "GREEDY" ALGORITHMS

Informatics in school, 2018
The article considers three logistic tasks (transportation problem, traveling salesman problem, pursuit problem), by the example of which the essence and features of “greedy” algorithms are shown. For the frst time, a solution was given to a transportation problem in the Mathcad Prime environment using the matrix method using units of measure.
V. F. Ochkov   +2 more
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Generalized Approximate Weak Greedy Algorithms

Mathematical Notes, 2005
The authors discuss so-called ``generalized approximate weak greedy algorithms'' (gAWGAs) in a Hilbert space, which describe the process of greedy expansions involving errors in calculation of the coefficients in terms of their absolut values. The concepts of ``dictionary'' in a real Hilbert space with inner product and of the ``gAWGA-expansion of an ...
Galatenko, V. V., Livshits, E. D.
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Greedy algorithms

2023
Patrick Bosc   +2 more
openaire   +1 more source

Greedy Approximation Algorithms

2013
Greedy strategy is a simple and natural method in the design of approximation algorithms. This chapter presents greedy approximation algorithms for very broad classes of maximization problems and minimization problems and analyzes their approximation bounds.
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Learning to select operators in meta-heuristics: An integration of Q-learning into the iterated greedy algorithm for the permutation flowshop scheduling problem

European Journal of Operational Research, 2023
Maryam Karimi-Mamaghan   +2 more
exaly  

The Greedy Algorithm

1999
In this chapter we study a method for optimizing over certain set systems, the so-called greedy algorithm. More precisely, it is used for maximizing a weight function on so-called independence systems, the classical instance being the system of spanning forests of a graph.
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