Results 11 to 20 of about 22,797 (304)
Disciplined Geodesically Convex Programming
CoRRConvex programming plays a fundamental role in machine learning, data science, and engineering. Testing convexity structure in nonlinear programs relies on verifying the convexity of objectives and constraints. Grant et al. (2006) introduced a framework, Disciplined Convex Programming (DCP), for automating this verification task for a wide range of ...
Andrew Cheng +2 more
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Convex approximations for complete integer recourse models [PDF]
, 2002 We consider convex approximations of the expected value function of a two-stage integer recourse problem. The convex approximations are obtained by perturbing the distribution of the random right-hand side vector.
Vlerk, Maarten H. van der +2 more
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LINEAR PROGRAMMING APPLIED TO A CONVEX PROGRAMMING TYPE
Pesquimat, 2014 In the present’s paper studying a strategy for a typo of convex problem, we treat a linear programming problem whose coefficient of decision variables in the objective function has a nonlinear behavior.
Edinson Raúl Montoro Alegre +3 more
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Componentwise Fractional Programming with Application to Resource Allocation [PDF]
Modeling, Identification and Control, 1983 A fractional programming problem is considered of the maximization of the ratio of a concave and a convex function, with each variable occurring in a single convex component constraint.
Kåre M. Mjelde
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Global Optimization for the Sum of Concave-Convex Ratios Problem
Journal of Applied Mathematics, 2014 This paper presents a branch and bound algorithm for globally solving the sum of concave-convex ratios problem (P) over a compact convex set. Firstly, the problem (P) is converted to an equivalent problem (P1).
XueGang Zhou, JiHui Yang
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Journal of Applied Mathematics, 2011 Convex multiobjective programming problems and multiplicative programming problems have important applications in areas such as finance, economics, bond portfolio optimization, engineering, and other fields. This paper presents a quite easy algorithm for
Le Quang Thuy +2 more
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A Multi-Step Inertial Proximal Peaceman-Rachford Splitting Method for Separable Convex Programming
IEEE Access, 2023 In this paper, we propose a multi-step inertial proximal Peaceman-Rachford splitting method (abbreviated as MIP-PRSM) for solving the two-block separable convex optimization problems with linear constraints, which is a unified framework for such Peaceman-
Hongyan Li, Dongmei Yu, Leifu Gao
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On Mixed-Integer Random Convex Programs [PDF]
, 2012 We consider a class of mixed-integer optimization problems subject to N randomly drawn convex constraints. We provide explicit bounds on the tails of the probability that the optimal solution found under these N constraints will become infeasible for the
D. Lyons +8 more
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Journal of Inequalities and Applications, 2023 In this paper, we present an inexact multiblock alternating direction method for the point-contact friction model of the force-optimization problem (FOP).
Yaling Zhang, Xuewen Mu
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Midcourse Guidance Trajectory Optimization of Interceptor Missile Based on Sequential Convex Programming [PDF]
Hangkong bingqi, 2023 Aiming at the trajectory optimization problem of interceptor midcourse guidance under strong nonlinear multi-constraint conditions, a trajectory optimization algorithm for fixed time constraints is proposed based on sequential convex programming method ...
Li Jiong, Zhang Jinlin, Shao Lei, Li Wanli, He Yangchao
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