Zobrazeno 1 - 10
of 6 490
pro vyhledávání: '"Continuous optimization"'
Autor:
H. F. Oviedo Leon, S. Guerrero
Publikováno v:
Trends in Computational and Applied Mathematics, Vol 25, Iss 1 (2024)
This paper proposes a family of line--search methods to deal with weighted orthogonal procrustes problems. In particular, the proposed family uses a search direction based on a convex combination between the Euclidean gradient and the Riemannian grad
Externí odkaz:
https://doaj.org/article/3145df55c3b44fbf8a26f91e98f7cfc2
Publikováno v:
Electronic Research Archive, Vol 32, Iss 5, Pp 2994-3015 (2024)
Running time analysis of evolutionary algorithms for continuous optimization is one research challenge in the field of evolutionary algorithms (EAs). However, the theoretical analysis results have rarely been applied to evolutionary algorithms for co
Externí odkaz:
https://doaj.org/article/f66156c15b2149eabdf7841e55862df8
Akademický článek
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Publikováno v:
AIMS Mathematics, Vol 8, Iss 12, Pp 30244-30268 (2023)
We introduce the Multi-objective Java Macaque Algorithm for tackling complex multi-objective optimization (MOP) problems. Inspired by the natural behavior of Java Macaque monkeys, the algorithm employs a unique selection strategy based on social hier
Externí odkaz:
https://doaj.org/article/70a6590a6db045b0b68da12ea550b372
Publikováno v:
Mathematics, Vol 12, Iss 17, p 2640 (2024)
Causal structure learning plays a crucial role in the current field of artificial intelligence, yet existing causal structure learning methods are susceptible to interference from data sample noise and often become trapped in local optima. To address
Externí odkaz:
https://doaj.org/article/0d58c24f8c144008a4ab3f17f3fffd2e
Publikováno v:
Mathematics, Vol 12, Iss 16, p 2570 (2024)
To overcome the limitations of single-type intelligent optimization algorithms prone to becoming stuck in local optima for complex problems, a hybrid intelligent optimization algorithm named SDIQ is proposed. This algorithm combines simulated anneali
Externí odkaz:
https://doaj.org/article/c9451f9686af4b49b0a6dc588042acb6
Autor:
Nándor Bándi, Noémi Gaskó
Publikováno v:
PeerJ Computer Science, Vol 10, p e1785 (2024)
This article introduces a new hybrid hyper-heuristic framework that deals with single-objective continuous optimization problems. This approach employs a nested Markov chain on the base level in the search for the best-performing operators and their
Externí odkaz:
https://doaj.org/article/b68ab23436be4220be5158a84fea3e75
Publikováno v:
Complex & Intelligent Systems, Vol 9, Iss 5, Pp 5251-5266 (2023)
Abstract Fitness landscape analysis devotes to characterizing different properties of optimization problems, such as evolvability, sharpness, and neutrality. Although several landscape features have been proposed, only a few of them can be used in pr
Externí odkaz:
https://doaj.org/article/74eeb66ca99e4353b949c6d710c62884