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Linear complementarity, linear and nonlinear programming
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The article was published on 1988-01-01 and is currently open access. It has received 1012 citations till now. The article focuses on the topics: Mixed complementarity problem & Complementarity theory.read more
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The debonding effect in saddles: comparison of the performance of Flügge's and Sanders' shell theories
TL;DR: In this paper, the authors used the linear complementarity problem (LCP) to calculate the unilateral contact stresses between the cylindrical vessels and the saddles by formulating the Linear Complementarity Problem.
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New projection-type methods for monotone LCP with finite termination
J. Z. Zhang,Naihua Xiu +1 more
TL;DR: Two new projection-type methods for the solution of monotone linear complementarity problem (LCP) are established, a combination of the extragradient method and the Newton method, which are globally and linearly convergent under the assumption of monotonicity.
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Properties of the solution set of absolute value equations and the related matrix classes
TL;DR: The absolute value equations problem is addressed by analysing properties of AVE and the corresponding solution set, and topological properties of the solution set are investigated, such as convexity, boundedness, connectedness, or whether it consists of finitely many solutions.
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Decomposition Algorithm of Linear Complementarity Problem and its Application for Simulation of Pulpwood Collisions in Debarking Drum
TL;DR: The problem of numerical simulation of pulpwood collisions in a debarking drum is regarded as the source of the contact problem and a new decomposition algorithm of a linear complementarity problem with a positive definite matrix of coefficients is substantiated.
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Determination of the collapse load of plastic structures by the use of an upper bounding algorithm
TL;DR: An upper bounding algorithm is applied to the problem of the elastoplastic analysis of structures expressed as linear complementarity problems and the time consuming procedure of solving large quadratic optimization problems can be avoided.