Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Thang, Tran Ngoc"'
We present an adaptive step-size method, which does not include line-search techniques, for solving a wide class of nonconvex multiobjective programming problems on an unbounded constraint set. We also prove convergence of a general approach under mo
Externí odkaz:
http://arxiv.org/abs/2402.06224
Controllable Pareto front learning (CPFL) approximates the Pareto solution set and then locates a Pareto optimal solution with respect to a given reference vector. However, decision-maker objectives were limited to a constraint region in practice, so
Externí odkaz:
http://arxiv.org/abs/2402.05955
Despite notable results on standard aerial datasets, current state-of-the-arts fail to produce accurate building footprints in dense areas due to challenging properties posed by these areas and limited data availability. In this paper, we propose a f
Externí odkaz:
http://arxiv.org/abs/2309.01656
The article proposes an exact approach to find the global solution of a nonconvex semivectorial bilevel optimization problem, where the objective functions at each level are pseudoconvex, and the constraints are quasiconvex. Due to its non-convexity,
Externí odkaz:
http://arxiv.org/abs/2304.10898
Pareto Front Learning (PFL) was recently introduced as an efficient method for approximating the entire Pareto front, the set of all optimal solutions to a Multi-Objective Optimization (MOO) problem. In the previous work, the mapping between a prefer
Externí odkaz:
http://arxiv.org/abs/2302.12487
Pareto Front Learning (PFL) was recently introduced as an effective approach to obtain a mapping function from a given trade-off vector to a solution on the Pareto front, which solves the multi-objective optimization (MOO) problem. Due to the inheren
Externí odkaz:
http://arxiv.org/abs/2212.01130
Publikováno v:
In Neural Networks January 2024 169:257-273
Publikováno v:
Journal of Intelligent & Fuzzy Systems, (Preprint), 1-11 (2020)
In this article, we use the monotonic optimization approach to propose an outcome-space outer approximation by copolyblocks for solving strictly quasiconvex multiobjective programming problems and especially in the case that the objective functions a
Externí odkaz:
http://arxiv.org/abs/2003.07549
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.