AbstractComputational and storage costs of resolution of large sparse linear systems Ax=b can be performed by reducing the bandwidth of A. Bandwidth reduction consists of carrying out permutations of lines and columns so that they allow coefficients to remain near the main diagonal.When considering an adjacency matrix of a graph, bandwidth reduction can be considered in the sense of modifying the order in which the graph vertices are numbered. Heuristics for bandwidth reduction are revised in this study, aiming at determining which of them offers the higher bandwidth reduction with a reasonable computational cost. Specifically, metaheuristic-based heuristics are reviewed in this systematic review. Moreover, 29 metaheuristic-based heuristics...
Abstract Most research in algorithm design relies on worstcase analysis for performance com parison...
Since 1969 a standard approach to the reduction of matrix bandwidth and profile has been to grow roo...
Most research in algorithm design relies on worst-case analysis for performance comparisons. Unfortu...
AbstractComputational and storage costs of resolution of large sparse linear systems Ax=b can be per...
This paper studies heuristics for the bandwidth reduction of large-scale matrices in serial computat...
The problem of sparse matrix bandwidth reduction is addressed and solved with two approaches suitabl...
In this paper, a new viable bandwidth reduction algorithm for reducing the bandwidth of sparse symme...
Abstract. For a sparse symmetric matrix, there has been much attention given to algorithms for reduc...
Colloque avec actes et comité de lecture. internationale.International audience"Bandwidth minimizati...
A simple and efficient algorithm for the bandwidth reduction of sparse symmetric matrices is propose...
Most research in algorithm design relies on worst-case analysis for performance comparisons. Unfortu...
Introduction Given an undirected graph G = (V; E) on n vertices, a linear arrangement (also called ...
The bandwidth problem seeks for a simultaneous permutation of the rows and columns of the adjacency ...
The paper describes a new bandwidth reduction method for sparse matrices which promises to be both f...
Abstract — In this article we first review previous exact approaches as well as theoretical contribu...
Abstract Most research in algorithm design relies on worstcase analysis for performance com parison...
Since 1969 a standard approach to the reduction of matrix bandwidth and profile has been to grow roo...
Most research in algorithm design relies on worst-case analysis for performance comparisons. Unfortu...
AbstractComputational and storage costs of resolution of large sparse linear systems Ax=b can be per...
This paper studies heuristics for the bandwidth reduction of large-scale matrices in serial computat...
The problem of sparse matrix bandwidth reduction is addressed and solved with two approaches suitabl...
In this paper, a new viable bandwidth reduction algorithm for reducing the bandwidth of sparse symme...
Abstract. For a sparse symmetric matrix, there has been much attention given to algorithms for reduc...
Colloque avec actes et comité de lecture. internationale.International audience"Bandwidth minimizati...
A simple and efficient algorithm for the bandwidth reduction of sparse symmetric matrices is propose...
Most research in algorithm design relies on worst-case analysis for performance comparisons. Unfortu...
Introduction Given an undirected graph G = (V; E) on n vertices, a linear arrangement (also called ...
The bandwidth problem seeks for a simultaneous permutation of the rows and columns of the adjacency ...
The paper describes a new bandwidth reduction method for sparse matrices which promises to be both f...
Abstract — In this article we first review previous exact approaches as well as theoretical contribu...
Abstract Most research in algorithm design relies on worstcase analysis for performance com parison...
Since 1969 a standard approach to the reduction of matrix bandwidth and profile has been to grow roo...
Most research in algorithm design relies on worst-case analysis for performance comparisons. Unfortu...