The Nonlinear Programming Solver

References

  • Akrotirianakis, I. and Rustem, B. (2005), “Globally Convergent Interior-Point Algorithm for Nonlinear Programming,” Journal of Optimization Theory and Applications, 125(3), 497–521.

  • Armand, P., Gilbert, J. C., and Jan-Jégou, S. (2002), “A BFGS-IP Algorithm for Solving Strongly Convex Optimization Problems with Feasibility Enforced by an Exact Penalty Approach,” Mathematical Programming, 92(3), 393–424.

  • Erway, J., Gill, P. E., and Griffin, J. D. (2007), “Iterative Solution of Augmented Systems Arising in Interior Point Methods,” SIAM Journal on Optimization, 18, 666–690.

  • Forsgren, A. and Gill, P. E. (1998), “Primal-Dual Interior Methods for Nonconvex Nonlinear Programming,” SIAM Journal on Optimization, 8, 1132–1152.

  • Forsgren, A., Gill, P. E., and Wright, M. H. (2002), “Interior Methods for Nonlinear Optimization,” SIAM Review, 44, 525–597.

  • Gill, P. E. and Robinson, D. P. (2010), “A Primal-Dual Augmented Lagrangian,” Computational Optimization and Applications, 47, 1–25.

  • Gould, N. I. M., Orban, D., and Toint, Ph. L. (2003), “CUTEr and SifDec: A Constrained and Unconstrained Testing Environment, Revised,” ACM Transactions on Mathematical Software, 29(4), 373–394.

  • Hock, W. and Schittkowski, K. (1981), Lecture Notes in Economics and Mathematical Systems: Test Examples for Nonlinear Programming Codes, Berlin: Springer-Verlag.

  • Nocedal, J. and Wright, S. J. (1999), Numerical Optimization, New York: Springer-Verlag.

  • Vanderbei, R. J. and Shanno, D. (1999), “An Interior-Point Algorithm for Nonconvex Nonlinear Programming,” Computational Optimization and Applications, 13, 231–252.

  • Wächter, A. and Biegler, L. T. (2006), “On the Implementation of an Interior-Point Filter Line-Search Algorithm for Large-Scale Nonlinear Programming,” Mathematical Programming, 106 (No. 1), 25–57.

  • Wright, S. J. (1997), Primal-Dual Interior-Point Methods, SIAM Publications.

  • Yamashita, H. (1998), “A Globally Convergent Primal-Dual Interior Point Method for Constrained Optimization,” Optimization Methods and Software, 10, 443–469.