Results 1 to 10 of about 1,804,722 (202)

Existence of Solutions for Nonconvex and Nonsmooth Vector Optimization Problems

open access: yesJournal of Inequalities and Applications, 2008
We consider the weakly efficient solution for a class of nonconvex and nonsmooth vector optimization problems in Banach spaces. We show the equivalence between the nonconvex and nonsmooth vector optimization problem and the vector variational-like ...
Nan-Jing Huang   +2 more
doaj   +3 more sources

On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks [PDF]

open access: yesQuantum, 2023
Classical algorithms are often not effective for solving nonconvex optimization problems where local minima are separated by high barriers. In this paper, we explore possible quantum speedups for nonconvex optimization by leveraging the $global$ effect ...
Yizhou Liu, Weijie J. Su, Tongyang Li
doaj   +1 more source

Fractional Versions of Hermite-Hadamard, Fejér, and Schur Type Inequalities for Strongly Nonconvex Functions

open access: yesJournal of Function Spaces, 2022
In modern world, most of the optimization problems are nonconvex which are neither convex nor concave. The objective of this research is to study a class of nonconvex functions, namely, strongly nonconvex functions.
Wenbo Xu   +4 more
doaj   +1 more source

Unified Algorithm Framework for Nonconvex Stochastic Optimization in Deep Neural Networks

open access: yesIEEE Access, 2021
This paper presents a unified algorithmic framework for nonconvex stochastic optimization, which is needed to train deep neural networks. The unified algorithm includes the existing adaptive-learning-rate optimization algorithms, such as Adaptive Moment ...
Yini Zhu, Hideaki Iiduka
doaj   +1 more source

Convergence rate for diminishing stepsize methods in nonconvex constrained optimization via ghost penalties

open access: yesAtti della Accademia Peloritana dei Pericolanti : Classe di Scienze Fisiche, Matematiche e Naturali, 2020
This is a companion paper to "Ghost penalties in nonconvex constrained optimization: Diminishing stepsizes and iteration complexity" (to appear in Mathematics of Operations Research).
Francisco Facchinei   +3 more
doaj   +1 more source

Joint Differential Evolution and Successive Convex Approximation in UAV-Enabled Mobile Edge Computing

open access: yesIEEE Access, 2022
UAV-enabled mobile edge computing (MEC) is an emerging technology to support resource-intensive yet delay-sensitive applications with edge clouds (ECs) deployed in the proximity to mobile users and UAVs served as computing base stations in the air.
Zhe Yu, Guoliang Fan
doaj   +1 more source

Resource Allocation for a Secure SWIPT Network Based on a Quantitative Energy Harvesting Mechanism

open access: yesSensors, 2023
Simultaneous wireless information and power transfer (SWIPT) technology can effectively extend the lifecycle of energy-constrained networks. In order to improve the energy harvesting (EH) efficiency and network performance in secure SWIPT networks, this ...
Long Zhu   +3 more
doaj   +1 more source

Greedy Sine-Cosine Non-Hierarchical Grey Wolf Optimizer for Solving Non-Convex Economic Load Dispatch Problems

open access: yesEnergies, 2022
Economic load dispatch (ELD) provides significant benefits to the operation of the power system. It appears to be a complex nonconvex optimization problem subject to several equal and unequal constraints.
Ali S. Alghamdi
doaj   +1 more source

Solution of an Economic Dispatch Problem Through Particle Swarm Optimization: A Detailed Survey – Part II

open access: yesIEEE Access, 2017
Although particle swarm optimization (PSO) in its standard form performs extremely well for less complicated convex optimization problems involving reduced search space, it fails in finding global optimal solutions for more complicated nonconvex ...
Ghulam Abbas   +5 more
doaj   +1 more source

A class of null space conditions for sparse recovery via nonconvex, non-separable minimizations

open access: yesResults in Applied Mathematics, 2019
For the problem of sparse recovery, it is widely accepted that nonconvex minimizations are better than ℓ1 penalty in enhancing the sparsity of solution.
Hoang Tran, Clayton Webster
doaj   +1 more source

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