PyVMCON

Python implementation of the [VMCON] non-linear constrained optimisation algorithm.

Contents:

• The VMCON Algorithm
  • The Problem
  • The Lagrangian
  • Initialisation of VMCON
  • The Quadratic Programming Problem
  • The Convergence Test
  • The Line Search
  • The Broyden-Fletcher-Goldfarb-Shanno (BFGS) Quasi-Newton Update
  • The VMCON Algorithm
• PyVMCON Example
• PyVMCON API Reference
  • PyVMCON

References

[VMCON]

Crane, R. L., Hillstrom, K. E., & Minkoff, M.. Solution of the general nonlinear programming problem with subroutine VMCON. [VMCON1; in FORTRAN for IBM 370/168]. United States. https://doi.org/10.2172/5206574

[Powell1978]

Powell, M. J. D. (1978). A fast algorithm for nonlinearly constrained optimization calculations. In G. A. Watson (Ed.), Numerical Analysis (pp. 144–157). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/BFb0067703

[diamond2016cvxpy]

Diamond, S., & Boyd, S. (2016). CVXPY: A Python-embedded modeling language for convex optimization. Journal of Machine Learning Research, 17(83), 1–5.

[osqp]

Stellato, B., Banjac, G., Goulart, P., Bemporad, A., & Boyd, S. (2020). OSQP: an operator splitting solver for quadratic programs. Mathematical Programming Computation, 12(4), 637–672. https://doi.org/10.1007/s12532-020-00179-2

Indices and tables

• Index

• Module Index

• Search Page