Results 31 to 40 of about 2,017,112 (308)
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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A Note on Optimality Conditions for DC Programs Involving Composite Functions
Abstract and Applied Analysis, 2014 By using the formula of the ε-subdifferential for the sum of a convex function with a composition of convex functions, some necessary and sufficient optimality conditions for a DC programming problem involving a composite function are obtained.
Xiang-Kai Sun, Hong-Yong Fu
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Journal of Inequalities and Applications, 2019 In this paper, we first introduce a new algorithm which involves projecting each iteration to solve a split feasibility problem with paramonotone equilibria and using unconstrained convex optimization.
Q. L. Dong +4 more
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Convex Matroid Optimization [PDF]
SIAM Journal on Discrete Mathematics, 2003 We consider a problem of optimizing convex functionals over matroid bases. It is richly expressive and captures certain quadratic assignment and clustering problems. While generally NP-hard, we show it is polynomial time solvable when a suitable parameter is restricted.
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Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods [PDF]
, 2009 In this paper we give a general framework for isotone optimization. First we discuss a generalized version of the pool-adjacent-violators algorithm (PAVA) to minimize a separable convex function with simple chain constraints.
de Leeuw, Jan +6 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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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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Convex optimization using quantum oracles [PDF]
Quantum, 2020 We study to what extent quantum algorithms can speed up solving convex optimization problems. Following the classical literature we assume access to a convex set via various oracles, and we examine the efficiency of reductions between the different ...
Joran van Apeldoorn +3 more
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Journal of Statistical Software, 2014 Convex optimization now plays an essential role in many facets of statistics. We briefly survey some recent developments and describe some implementations of these methods in R .
Roger Koenker, Ivan Mizera
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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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