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Piecewise Sequential Quadratic Programming for Mathematical Programs with Nonlinear Complementarity Constraints

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Multilevel Optimization: Algorithms and Applications

Part of the book series: Nonconvex Optimization and Its Applications ((NOIA,volume 20))

Abstract

We describe some first- and second-order optimality conditions for mathematical programs with equilibrium constraints (MPEC). Mathematical programs with parametric nonlinear complementarity constraints are the focus. Of interest is the result that under a linear independence assumption that is standard in nonlinear programming, the otherwise combinatorial problem of checking whether a point is stationary for an MPEC is reduced to checking stationarity of single nonlinear program. We also present a piecewise sequential quadratic programming (PSQP) algorithm for solving MPEC. Local quadratic convergence is shown under the linear independence assumption and a second-order sufficient condition. Some computational results are given.

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© 1998 Kluwer Academic Publishers

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Luo, ZQ., Pang, JS., Ralph, D. (1998). Piecewise Sequential Quadratic Programming for Mathematical Programs with Nonlinear Complementarity Constraints. In: Migdalas, A., Pardalos, P.M., Värbrand, P. (eds) Multilevel Optimization: Algorithms and Applications. Nonconvex Optimization and Its Applications, vol 20. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0307-7_9

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  • DOI: https://doi.org/10.1007/978-1-4613-0307-7_9

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7989-8

  • Online ISBN: 978-1-4613-0307-7

  • eBook Packages: Springer Book Archive

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