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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)
Reducing the Experiments Required to Assess the Performance of Metaheuristic Algorithms
(Revista Computación y Sistemas; Vol. 14 No.1, 2010-09-30)
Abstract. When assessing experimentally the performance of metaheuristic algorithms on a set of hard instances of an NP-complete problem, the required time to carry out the experimentation can be very large. A means to ...
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 ...
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 ...
Meta-heuristic multi- and many-objective optimization techniques for solution of machine learning problems
(Wiley-Blackwell, 2017-12-01)
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 ...
Fine Tuning Deep Boltzmann Machines Through Meta-Heuristic Approaches
(Ieee, 2018-01-01)
The Deep learning framework has been widely used in different applications from medicine to engineering. However, there is a lack of works that manage to deal with the issue of hyperparameter fine-tuning, since machine ...
An efficient hybrid metaheuristics optimization technique applied to the AC electric transmission network expansion planning
(2021)
The transmission network expansion planning (TNEP) problem consists of determining the necessary infrastructure additions, within a planning horizon, to minimize an investment objective function while meeting some operational ...
Solving the 3D container ship loading planning problem by representation by rules and meta-heuristics
(2014-01-01)
This paper formulates the 3D containership loading planning problem (3D CLPP) and also proposes a new and compact representation to efficiently solve it. The key objective of stowage planning is to minimise the number of ...