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Multiparametric Linear Complementarity Problems [PDF]
Proceedings of the 45th IEEE Conference on Decision and Control, 2006 The linear complementarity problem (LCP) is a general problem that unifies linear and quadratic programs and bimatrix games. In this paper, we present an efficient algorithm for the solution to multiparametric linear complementarity problems (pLCPs) that are defined by positive semi-definite matrices. This class of problems includes the multiparametric
Colin N. Jones, Manfred Morrari
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A Sequential Convex Programming Approach to Solving Quadratic Programs and Optimal Control Problems With Linear Complementarity Constraints [PDF]
IEEE Control Systems Letters, 2021 Mathematical programs with complementarity constraints are notoriously difficult to solve due to their nonconvexity and lack of constraint qualifications in every feasible point.
J. Hall +3 more
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Results in Applied Mathematics, 2022 This paper is concerned with solving linear complementarity problems (LCP) arising in many scientific and engineering fields. We propose an accelerated double-relaxation two-sweep modulus-based matrix splitting (ADRTMMS) iteration method by applying ...
Zhengge Huang, Jingjing Cui
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Preconditioned conjugate gradient methods for absolute value equations
Journal of Numerical Analysis and Approximation Theory, 2020 We investigate the NP-hard absolute value equations (AVE), \(Ax-B|x| =b\), where \(A,B\) are given symmetric matrices in \(\mathbb{R}^{n\times n}, \ b\in \mathbb{R}^{n}\).
Nassima Anane, Mohamed Achache
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SIAM Journal on Optimization, 2020 We introduce a new feasible corrector-predictor (CP) interior-point algorithm (IPA), which is suitable for solving linear complementarity problem (LCP) with $P_{*} (\kappa)$-matrices.
Zsolt Darvay +3 more
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Algorithms, 2016 Our purpose of this paper is to solve a class of stochastic linear complementarity problems (SLCP) with finitely many elements. Based on a new stochastic linear complementarity problem function, a new semi-smooth least squares reformulation of the ...
Zhimin Liu, Shouqiang Du, Ruiying Wang
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Discrete approximation of two-stage stochastic and distributionally robust linear complementarity problems [PDF]
Mathematical programming, 2017 In this paper, we propose a discretization scheme for the two-stage stochastic linear complementarity problem (LCP) where the underlying random data are continuously distributed.
Xiaojun Chen, Hailin Sun, Huifu Xu
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A class of singular Ro-matrices and extensions to semidefinite linear complementarity problems [PDF]
Yugoslav Journal of Operations Research, 2013 For ARnxn and qRn, the linear complementarity problem LCP(A, q) is to determine if there is xRn such that x ≥ 0; y = Ax + q ≥ 0 and xT y = 0. Such an x is called a solution of LCP(A,q).
Sivakumar K.C.
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Improved Full-Newton-Step Infeasible Interior-Point Method for Linear Complementarity Problems
Croatian Operational Research Review, 2016 We present an Infeasible Interior-Point Method for monotone Linear Complementarity Problem (LCP) which is an improved version of the algorithm given in [13]. In the earlier version, each iteration consisted of one feasibility step and few centering steps.
Goran Lešaja, Mustafa Ozen
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Journal of Mathematics, 2014 We consider a class of absolute-value linear complementarity problems. We propose a new approximation reformulation of absolute value linear complementarity problems by using a nonlinear penalized equation.
Yuan Li, Hai-Shan Han, Dan-Dan Yang
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