A glass-box interactive machine learning approach for solving NP-hard problems with the human-in-the-loop
The goal of Machine Learning to automatically learn from data, extract knowledge and to
make decisions without any human intervention. Such automatic (aML) approaches show …
make decisions without any human intervention. Such automatic (aML) approaches show …
Metaheuristic-based heuristics for symmetric-matrix bandwidth reduction: a systematic review
Computational 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 …
performed by reducing the bandwidth of A. Bandwidth reduction consists of carrying out …
[كتاب][B] Advances in bio-inspired computing for combinatorial optimization problems
CM Pintea - 2014 - Springer
” Advances in Bio-inspired Combinatorial Optimization Problems” illustrates several recent
bio-inspired efficient algorithms for solving NP-hard problems. Theoretical bio-inspired …
bio-inspired efficient algorithms for solving NP-hard problems. Theoretical bio-inspired …
An ant colony hyperheuristic approach for matrix bandwidth reduction
This paper considers the bandwidth reduction problem for large-scale matrices in serial
computations. A heuristic for bandwidth reduction reorders the rows and columns of a given …
computations. A heuristic for bandwidth reduction reorders the rows and columns of a given …
Population-based iterated greedy algorithm for the S-labeling problem
The iterated greedy metaheuristic generates a sequence of solutions by iterating over a
constructive heuristic using destruction and construction phases. In the last few years, it has …
constructive heuristic using destruction and construction phases. In the last few years, it has …
The bandwidths of a matrix. a survey of algorithms
The bandwidth, average bandwidth, envelope, profile and antibandwidth of the matrices
have been the subjects of study for at least 45 years. These problems have generated …
have been the subjects of study for at least 45 years. These problems have generated …
An evaluation of heuristic methods for the bandwidth reduction of large-scale graphs
This paper studies the bandwidth reduction problem for large-scale sparse matrices in serial
computations. A heuristic for bandwidth reduction reorders the rows and columns of a given …
computations. A heuristic for bandwidth reduction reorders the rows and columns of a given …
Iterated Local Search with Tabu Search for the Bandwidth Reduction Problem in Graphs
This paper addresses the bandwidth reduction problem in graphs, which is relevant in
several applications, such as reducing memory consumption and computational cost in …
several applications, such as reducing memory consumption and computational cost in …
Reducing the bandwidth of a sparse matrix with a genetic algorithm
The matrix bandwidth minimization problem (MBMP) consists in finding a permutation of the
lines and columns of a given sparse matrix in order to keep the non-zero elements in a band …
lines and columns of a given sparse matrix in order to keep the non-zero elements in a band …
Soft computing approaches on the bandwidth problem
The Matrix Bandwidth Minimization Problem (MBMP) seeks for a simultaneous reordering of
the rows and the columns of a square matrix such that the nonzero entries are collected …
the rows and the columns of a square matrix such that the nonzero entries are collected …