Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Adriana Menchaca-Mendez"'
Autor:
Adriana Menchaca-Mendez, Elizabeth Montero, Luis Miguel Antonio, Saul Zapotecas-Martinez, Carlos A. Coello Coello, Maria-Cristina Riff
Publikováno v:
IEEE Access, Vol 7, Pp 18267-18283 (2019)
Convergence and diversity of solutions play an essential role in the design of multi-objective evolutionary algorithms (MOEAs). Among the available diversity mechanisms, the $\epsilon $ -dominance has shown a proper balance between convergence and di
Externí odkaz:
https://doaj.org/article/ece314f911f2436d899969ed4f79b1c6
Publikováno v:
IEEE Access, Vol 6, Pp 63382-63401 (2018)
One of the main disadvantages of evolutionary multi-objective algorithms (EMOAs) based on hypervolume is the computational cost of the hypervolume computation. This deficiency gets worse either when an EMOA calculates the hypervolume several times or
Externí odkaz:
https://doaj.org/article/523313f999f74ce3a9f4f6a39c71073b
Autor:
Elizabeth Montero, Adriana Menchaca-Mendez, Carlos A. Coello Coello, Saúl Zapotecas-Martínez, María Cristina Riff, Luis Miguel Antonio
Publikováno v:
IEEE Access, Vol 7, Pp 18267-18283 (2019)
Convergence and diversity of solutions play an essential role in the design of multi-objective evolutionary algorithms (MOEAs). Among the available diversity mechanisms, the $\epsilon $ -dominance has shown a proper balance between convergence and di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::93b352c4799d17bf6aa38508dec292fc
https://ieeexplore.ieee.org/document/8637162/
https://ieeexplore.ieee.org/document/8637162/
Publikováno v:
CEC
The multi-objective evolutionary algorithm based on decomposition (MOEA/D) has attracted the attention of several investigators working on multi-objective optimization. At each iteration, MOEA/D generates an offspring solution from a parent’s neigh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::955c79d25773717560440d7b85625ac8
https://doi.org/10.1109/cec48606.2020.9185715
https://doi.org/10.1109/cec48606.2020.9185715
Autor:
Saúl Zapotecas-Martínez, Luis Miguel García-Velázquez, Carlos A. Coello Coello, Adriana Menchaca-Mendez
Publikováno v:
Swarm and Evolutionary Computation. 68:100979
Design of experiments is a branch of statistics that has been employed in different areas of knowledge. A particular case of experimental designs is uniform mixture design. A uniform mixture design method aims to spread points (mixtures) uniformly di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54e5cf6c3cd2d803b06ffaeb2409ca60
https://doi.org/10.1016/j.swevo.2021.100979
https://doi.org/10.1016/j.swevo.2021.100979
Publikováno v:
IEEE Access, Vol 6, Pp 63382-63401 (2018)
One of the main disadvantages of evolutionary multi-objective algorithms (EMOAs) based on hypervolume is the computational cost of the hypervolume computation. This deficiency gets worse either when an EMOA calculates the hypervolume several times or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e579384342e31a333a1605b8e27d867e
https://doi.org/10.1109/access.2018.2877402
https://doi.org/10.1109/access.2018.2877402
Publikováno v:
Mathematics, Vol 10, Iss 19, p 19 (2022)
Mathematics; Volume 10; Issue 1; Pages: 19
Mathematics; Volume 10; Issue 1; Pages: 19
One of the major limitations of evolutionary algorithms based on the Lebesgue measure for multi-objective optimization is the computational cost required to approximate the Pareto front of a problem. Nonetheless, the Pareto compliance property of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53591aa23bdbd020cfc9ba725ab51cfd
https://doi.org/10.3390/math10010019
https://doi.org/10.3390/math10010019
Publikováno v:
Information Sciences. 332:131-152
In this paper, we study three selection mechanisms based on the maximin fitness function and we propose another one. These selection mechanisms give rise to the following MOEAs: "MC-MOEA", "MD-MOEA", "MH-MOEA" and "MAH-MOEA". We validated them using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2830a4ddff04d6e7a95bc06f35daa216
https://doi.org/10.1016/j.ins.2015.11.008
https://doi.org/10.1016/j.ins.2015.11.008
Publikováno v:
Soft Computing. 21:861-884
In this paper, we are interested in selection mechanisms based on the hypervolume indicator with a particular emphasis on the mechanism used in an improved version of the S metric selection evolutionary multi-objective algorithm (SMS-EMOA) called iSM
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66521b45341cbfc0e66399d044cf6b88
https://doi.org/10.1007/s00500-015-1819-x
https://doi.org/10.1007/s00500-015-1819-x
Publikováno v:
CEC
In this paper, we propose a new selection scheme for Multi-Objective Evolutionary Algorithms (MOEAs) based on the Δ ρ indicator. Our new selection scheme is incorporated into a MOEA giving rise to the “Δρ-MOEA.” Perhaps, one of the most impor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53419dedcab189b7f69e15596f1f394c
https://doi.org/10.1109/cec.2016.7744265
https://doi.org/10.1109/cec.2016.7744265