Now showing items 1-10 of 1537
A Heuristic for Optimization of Metaheuristics by Means of Statistical Methods
The fine-tuning of the algorithms parameters, specially, in metaheuristics, is not always trivial and often is performed by ad hoc methods according to the problem under analysis. Usually, incorrect settings influence both ...
Metaheuristics for a crop rotation problem
This paper presents a mathematical model adapted from literature for the crop rotation problem with demand constraints (CRP-D). The main aim of the present work is to study metaheuristics and their performance in a real ...
Cat swarm optimization with different transfer functions for solving set covering problems
(Springer Verlag, 2016)
Cat swarm optimization with different binarization methods for solving set covering problems
(Springer Verlag, 2016)
Single, multi- and many-objective meta-heuristic algorithms applied to pattern recognition
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação em Ciência da Computação - PPGCCCâmpus São Carlos, 2019-07-10)
In the last few years, metaheuristic algorithms have been used for solving several problems in engineering, biology, physics, among others, since many of them can be modeled as being optimization tasks. Metaheuristic methods ...
A metaheuristic-driven approach to fine-tune Deep Boltzmann Machines
(Elsevier B.V., 2020-12-01)
Deep learning techniques, such as Deep Boltzmann Machines (DBMs), have received considerable attention over the past years due to the outstanding results concerning a variable range of domains. One of the main shortcomings ...
A comparison of metaheuristics algorithms for combinatorial optimization problems. application to phase balancing in electric distribution systems
(Planta Piloto de Ingeniería Química, 2011-06)
Metaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase ...
Meta-heuristic multi- and many-objective optimization techniques for solution of machine learning problems
Recently, multi- and many-objective meta-heuristic algorithms have received considerable attention due to their capability to solve optimization problems that require more than one fitness function. This paper presents a ...