A robust SQP method for mathematical programs with linear complementarity constraints

Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10589-005-3075-y

Title:	A robust SQP method for mathematical programs with linear complementarity constraints
Authors:	Liu, X. Perakis, G. Sun, J.
Keywords:	Complementarity Constraint qualification Mathematical programs with equilibrium constraints Nondegeneracy Sequential quadratic programming
Issue Date:	2006
Citation:	Liu, X., Perakis, G., Sun, J. (2006). A robust SQP method for mathematical programs with linear complementarity constraints. Computational Optimization and Applications 34 (1) : 5-33. ScholarBank@NUS Repository. https://doi.org/10.1007/s10589-005-3075-y
Abstract:	The relationship between the mathematical program with linear complementarity constraints (MPLCC) and its inequality relaxation is studied. Based on this relationship, a new sequential quadratic programming (SQP) method is presented for solving the MPLCC. A certain SQP technique is introduced to deal with the possible inreasibility of quadratic programming subproblems. Global convergence results are derived without assuming the linear independence constraint qualification tor MPEC, the nondegeneracy condition, and any feasibility condition of the quadratic programming subproblems. Preliminary numerical results are reported. © 2005 Springer Science + Business Media, Inc. Manufactured in The Netherlands.
Source Title:	Computational Optimization and Applications
URI:	http://scholarbank.nus.edu.sg/handle/10635/44190
ISSN:	09266003
DOI:	10.1007/s10589-005-3075-y
Appears in Collections:	Staff Publications

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