Results 41 to 50 of about 4,530,250 (344)
Manifold Optimization Over the Set of Doubly Stochastic Matrices: A Second-Order Geometry [PDF]
, 2018 Convex optimization is a well-established research area with applications in almost all fields. Over the decades, multiple approaches have been proposed to solve convex programs.
Douik, Ahmed, Hassibi, Babak
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Multimodularity, Convexity, and Optimization Properties [PDF]
Mathematics of Operations Research, 2000 In this paper we investigate the properties of multimodular functions. In doing so we give elementary proofs for properties already established by Hajek and we generalize some of his results. In particular, we extend the relation between convexity and multimodularity to some convex subsets of ℤm. We also obtain general optimization results for average
Altman, Eitan +2 more
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Distributed Online Convex Optimization With Time-Varying Coupled Inequality Constraints [PDF]
IEEE Transactions on Signal Processing, 2019 This paper considers distributed online optimization with time-varying coupled inequality constraints. The global objective function is composed of local convex cost and regularization functions and the coupled constraint function is the sum of local ...
Xinlei Yi +3 more
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ROBOTIC MOTION PLANNING USING CONVEX OPTIMIZATION METHODS
Iraqi Journal for Computers and Informatics, 2019 Collision avoidance techniques tend to derive the robot away of the obstacles in minimal total travel distance. Most of the collision avoidance algorithms have trouble get stuck in a local minimum.
Thaker Nayl
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Solving Multiobjective Mixed Integer Convex Optimization Problems
SIAM Journal on Optimization, 2020 Multiobjective mixed integer convex optimization refers to mathematical programming problems where more than one convex objective function needs to be optimized simultaneously and some of the varia...
M. Santis +3 more
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Convex Optimization on Banach Spaces [PDF]
Foundations of Computational Mathematics, 2015 Greedy algorithms which use only function evaluations are applied to convex optimization in a general Banach space $X$. Along with algorithms that use exact evaluations, algorithms with approximate evaluations are treated. A priori upper bounds for the convergence rate of the proposed algorithms are given.
Ronald A. DeVore, Vladimir Temlyakov
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Some Inequalities of Generalized p-Convex Functions concerning Raina’s Fractional Integral Operators
Journal of Mathematics, 2021 Convex functions play an important role in pure and applied mathematics specially in optimization theory. In this paper, we will deal with well-known class of convex functions named as generalized p-convex functions.
Changyue Chen +2 more
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Digital Chemical Engineering, 2023 With increasing digitalization and vertical integration of chemical process systems, nonconvex optimization problems often emerge in chemical engineering applications, yet require specialized optimization techniques.
Yingwei Yuan, Kamil A. Khan
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Energy Informatics, 2021 Non-convex scheduling of energy production allows for more complex models that better describe the physical nature of the energy production system. Solutions to non-convex optimization problems can only be guaranteed to be local optima.
Jakob Bjørnskov +5 more
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Applied Sciences, 2016 Convex 1-D first-order total variation (TV) denoising is an effective method for eliminating signal noise, which can be defined as convex optimization consisting of a quadratic data fidelity term and a non-convex regularization term.
Cancan Yi, Yong Lv, Zhang Dang, Han Xiao
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