Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Erika Yesenia Avila-Melgar"'
Autor:
Marta Lilia Erana-Diaz, Marco Antonio Cruz-Chavez, Rafael Rivera-Lopez, Beatriz Martinez-Bahena, Erika Yesenia Avila-Melgar, Martin Heriberto Cruz-Rosales
Publikováno v:
IEEE Access, Vol 8, Pp 117063-117079 (2020)
In this paper, a computational methodology combining the simulated annealing algorithm with two machine learning techniques to select a near-optimal safeguard set for business risk response is presented. First, a mathematical model with four types of
Externí odkaz:
https://doaj.org/article/24ba6df4c2484129a496f4a5ebc76c16
Grid-Based Hybrid Genetic Approach to Relaxed Flexible Flow Shop with Sequence-Dependent Setup Times
Autor:
Erika Yesenia Avila Melgar, Marta Lilia Erana Diaz, Marco Antonio Cruz-Chavez, Martin H. Cruz-Rosales, Fredy Juarez-Perez, Rafael Rivera-Lopez
Publikováno v:
Applied Sciences; Volume 12; Issue 2; Pages: 607
Applied Sciences, Vol 12, Iss 607, p 607 (2022)
Applied Sciences, Vol 12, Iss 607, p 607 (2022)
In this paper, a hybrid genetic algorithm implemented in a grid environment to solve hard instances of the flexible flow shop scheduling problem with sequence-dependent setup times is introduced. The genetic algorithm takes advantage of the distribut
Autor:
Erika Yesenia Avila-Melgar, Marco Antonio Cruz-Chávez, Beatriz Martínez-Bahena, Marta Lilia Eraña-Díaz, Martín H. Cruz-Rosales
Publikováno v:
Applied Soft Computing. 135:109986
Autor:
Fredy Juárez-Pérez, Rafael Rivera-López, Marco Antonio Cruz-Chávez, Abelardo Rodriguez-Leon, Martin-Heriberto Cruz-Rosales, Erika-Yesenia Avila-Melgar
Publikováno v:
2010 IEEE Electronics, Robotics and Automotive Mechanics Conference.
In this work is defined a scheme of two stages for sending population segments of one Parallel Genetic Algorithm (PGA) to the nodes of an experimental grid called “Tarantula miniGrid”. The technique used to link the clusters and to configure the
Autor:
Martín H. Cruz-Rosales, Marco Antonio Cruz-Chávez, Federico Alonso-Pecina, Jesus del C. Peralta-Abarca, Erika Yesenia Ávila-Melgar, Beatriz Martínez-Bahena, Juana Enríquez-Urbano
Publikováno v:
Applied Sciences, Vol 12, Iss 2, p 542 (2022)
This work presents a metaheuristic with distributed processing that finds solutions for an optimization model of the university course timetabling problem, where collective communication and point-to-point communication are applied, which are used to
Externí odkaz:
https://doaj.org/article/577e9d205cf948cebda465341f58f233
Grid-Based Hybrid Genetic Approach to Relaxed Flexible Flow Shop with Sequence-Dependent Setup Times
Autor:
Fredy Juárez-Pérez, Marco Antonio Cruz-Chávez, Rafael Rivera-López, Erika Yesenia Ávila-Melgar, Marta Lilia Eraña-Díaz, Martín H. Cruz-Rosales
Publikováno v:
Applied Sciences, Vol 12, Iss 2, p 607 (2022)
In this paper, a hybrid genetic algorithm implemented in a grid environment to solve hard instances of the flexible flow shop scheduling problem with sequence-dependent setup times is introduced. The genetic algorithm takes advantage of the distribut
Externí odkaz:
https://doaj.org/article/76ed40b0fe8d413eaefa5e59e238f86a
Autor:
Marco Antonio Cruz-Chávez, Pedro Moreno-Bernal, Rafael Rivera-López, Erika Yesenia Ávila-Melgar, Beatriz Martínez-Bahena, Martín H. Cruz-Rosales
Publikováno v:
Applied Sciences, Vol 10, Iss 18, p 6190 (2020)
Planning corridors for new facilities such as pipeline or transmission lines through geographical spaces is a topographical constraint optimization problem. The corridor planning problem requires finding an optimal route or a set of alternative paths
Externí odkaz:
https://doaj.org/article/1cc1019f595043d0a4b5d15bae240e32