MCPLIB

MCPLIB: A Collection of Nonlinear Mixed Complementarity Problems. The origins and some motivational details of a collection of nonlinear mixed complementarity problems are given. This collection serves two purposes. Firstly, it gives a uniform basis for testing currently available and new algorithms for mixed complementarity problems. Function and Jacobian evaluations for the resulting problems are provided via a GAMS interface, making thorough testing of algorithms on practical complementarity problems possible. Secondly, it gives examples of how to formulate many popular problem formats as mixed complementarity problems and how to describe the resulting problems in GAMS format. We demonstrate the ease and power of formulating practical models in the MCP format. Given these examples, it is hoped that this collection will grow to include many problems that test complementarity algorithms more fully. The collection is available by anonymous ftp. Computational results using the PATH solver covering all of these problems are described


References in zbMATH (referenced in 96 articles )

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  1. Chen, Pin-Bo; Zhang, Peng; Zhu, Xide; Lin, Gui-Hua: Modified Jacobian smoothing method for nonsmooth complementarity problems (2020)
  2. Awwal, Aliyu Muhammed; Kumam, Poom; Bala Abubakar, Auwal: Spectral modified Polak-Ribiére-Polyak projection conjugate gradient method for solving monotone systems of nonlinear equations (2019)
  3. Liu, Jinkui; Feng, Yuming: A derivative-free iterative method for nonlinear monotone equations with convex constraints (2019)
  4. Xing, Weiwei; Zhang, Junqi; Song, Chongmin; Tin-Loi, Francis: A node-to-node scheme for three-dimensional contact problems using the scaled boundary finite element method (2019)
  5. Zhou, Zhengyong; Peng, Yunchan: The locally Chen-Harker-Kanzow-Smale smoothing functions for mixed complementarity problems (2019)
  6. Fan, Bin; Ma, Changfeng; Wu, Aidi; Wu, Chao: A Levenberg-Marquardt method for nonlinear complementarity problems based on nonmonotone trust region and line search techniques (2018)
  7. Gao, Peiting; He, Chuanjiang: An efficient three-term conjugate gradient method for nonlinear monotone equations with convex constraints (2018)
  8. Ou, Yigui; Li, Jingya: A new derivative-free SCG-type projection method for nonlinear monotone equations with convex constraints (2018)
  9. Tawhid, Mohamed A.; Gu, Wei-Zhe; Tran, Benjamin: A descent algorithm for generalized complementarity problems based on generalized Fischer-Burmeister functions (2018)
  10. Wang, Song: An interior penalty method for a large-scale finite-dimensional nonlinear double obstacle problem (2018)
  11. Zhao, Na; Ni, Tie: A nonmonotone smoothing Newton algorithm for solving general box constrained variational inequalities (2018)
  12. Bolzon, Gabriella: Complementarity problems in structural engineering: an overview (2017)
  13. Fan, Bin: A nonmonotone Levenberg-Marquardt method for nonlinear complementarity problems under local error bound (2017)
  14. Feng, Dexiang; Sun, Min; Wang, Xueyong: A family of conjugate gradient methods for large-scale nonlinear equations (2017)
  15. Gutierrez, Angel E. R.; Mazorche, Sandro R.; Herskovits, José; Chapiro, Grigori: An interior point algorithm for mixed complementarity nonlinear problems (2017)
  16. Hart, William E.; Laird, Carl D.; Watson, Jean-Paul; Woodruff, David L.; Hackebeil, Gabriel A.; Nicholson, Bethany L.; Siirola, John D.: Pyomo -- optimization modeling in Python (2017)
  17. Lamm, Michael; Lu, Shu; Budhiraja, Amarjit: Individual confidence intervals for solutions to expected value formulations of stochastic variational inequalities (2017)
  18. Liu, Jinkui; Li, Shengjie: Multivariate spectral DY-type projection method for convex constrained nonlinear monotone equations (2017)
  19. Liu, J. K.; Li, S. J.: A three-term derivative-free projection method for nonlinear monotone system of equations (2016)
  20. Sun, Min; Liu, Jing: New hybrid conjugate gradient projection method for the convex constrained equations (2016)

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