Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Santiago Enrique Conant Pablos"'
Autor:
Mohammad Saif Wajid, Hugo Terashima-Marin, Peyman Najafirad, Santiago Enrique Conant Pablos, Mohd Anas Wajid
Publikováno v:
Journal of Open Innovation: Technology, Market and Complexity, Vol 10, Iss 2, Pp 100297- (2024)
The increasing popularity of digital twins, alongside the rapid evolution of connectivity driven by the Internet of Things, highlights their potential to greatly aid in the development of smart cities. Digital twins are employed more commonly as smar
Externí odkaz:
https://doaj.org/article/e9e7ed4eeb814af1a9ec41cf34bdce21
Autor:
Enrique Díaz de León-Hicks, Santiago Enrique Conant-Pablos, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín
Publikováno v:
Applied Sciences, Vol 13, Iss 7, p 4601 (2023)
In the algorithm selection problem, where the task is to identify the most suitable solving technique for a particular situation, most methods used as performance mapping mechanisms have been relatively simple models such as logistic regression or ne
Externí odkaz:
https://doaj.org/article/eff56cb8dd7040d287d6fbc9828e0ca1
Autor:
Xavier Sánchez-Díaz, José Carlos Ortiz-Bayliss, Ivan Amaya, Jorge M. Cruz-Duarte, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín
Publikováno v:
Applied Sciences, Vol 11, Iss 21, p 10209 (2021)
Recent years have witnessed a growing interest in automatic learning mechanisms and applications. The concept of hyper-heuristics, algorithms that either select among existing algorithms or generate new ones, holds high relevance in this matter. Curr
Externí odkaz:
https://doaj.org/article/5c14838d268843179edafee591028c85
Autor:
Santiago Enrique Conant-Pablos, Iván Amaya, Hugo Terashima-Marín, José Carlos Ortiz-Bayliss, Carlos A. Coello Coello, Luis Fernando Plata-González
Publikováno v:
Soft Computing. 23:12711-12728
The assessment of strengths and weaknesses of a solver is often limited by the diversity of the cases where it is tested upon. As such, it is paramount to have a versatile tool which finds the problem instances where such a solver excels/fails. In th
Autor:
Hugo Terashima-Marín, Andres Eduardo Gutierrez-Rodríguez, Santiago Enrique Conant-Pablos, José Carlos Ortiz-Bayliss, Jorge M. Cruz-Duarte, Iván Amaya
Publikováno v:
Applied Sciences, Vol 11, Iss 2749, p 2749 (2021)
Applied Sciences
Volume 11
Issue 6
Applied Sciences
Volume 11
Issue 6
Many of the works conducted on algorithm selection strategies—methods that choose a suitable solving method for a particular problem—start from scratch since only a few investigations on reusable components of such methods are found in the litera
Autor:
Ivan Amaya, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín, José Carlos Ortiz-Bayliss, Jorge M. Cruz-Duarte
Publikováno v:
CEC
Literature is prolific with metaheuristics for solving continuous optimisation problems. But, in practice, it is difficult to choose one appropriately. Moreover, it is necessary to determine a good enough set of parameters for the selected approach.
Autor:
Hugo Terashima-Marín, Frumen Olivas, Santiago Enrique Conant-Pablos, José Carlos Ortiz-Bayliss, Ivan Amaya
Publikováno v:
CEC
Hyper-heuristics are potent techniques that represent the synergy of low-level heuristics when solving optimization problems. This synergy usually leads to better solutions. Similarly, fuzzy logic has been successfully applied to several domains, tha
Autor:
Frumen Olivas, Iván Amaya, Hugo Terashima-Marín, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos
Publikováno v:
Computational Intelligence and Neuroscience
Computational Intelligence and Neuroscience, Vol 2021 (2021)
Computational Intelligence and Neuroscience, Vol 2021 (2021)
Hyperheuristics rise as powerful techniques that get good results in less computational time than exact methods like dynamic programming or branch and bound. These exact methods promise the global best solution, but with a high computational time. In
Autor:
Ivan Amaya, Jorge M. Cruz-Duarte, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín, Fernando Garza-Santisteban, José Carlos Ortiz-Bayliss
Publikováno v:
SSCI
Hyper-heuristics stand as a novel tool that combines low-level heuristics into robust solvers. However, training cost is a drawback that hinders their applicability. In this work, we analyze the effect of training with different problem sizes, to det
Publikováno v:
Computational Intelligence and Neuroscience, Vol 2018 (2018)
Computational Intelligence and Neuroscience
Computational Intelligence and Neuroscience
When solving constraint satisfaction problems (CSPs), it is a common practice to rely on heuristics to decide which variable should be instantiated at each stage of the search. But, this ordering influences the search cost. Even so, and to the best o