Interior Methods for Nonlinear Optimization
KTH Royal Institute of Technology · University of California, San Diego
Abstract
Abstract. Interior methods are an omnipresent, conspicuous feature of the constrained optimization landscape today, but it was not always so. Primarily in the form of barrier methods, interior-point techniques were popular during the 1960s for solving nonlinearly constrained problems. However, their use for linear programming was not even contemplated because of the total dominance of the simplex method. Vague but continuing anxiety about barrier methods eventually led to their abandonment in favor of newly emerging, apparently more efficient alternatives such as augmented Lagrangian and sequential quadratic programming methods. By the early 1980s, barrier methods were almost without exception regarded as a…
Citation impact
- FWCI
- 16.70
- Percentile
- 100%
- References
- 113
Authors
3Topics & keywords
- Interior point method
- Simplex algorithm
- Linear programming
- Mathematical optimization
- Nonlinear programming
- Mathematics
- Optimization problem
- Sequential quadratic programming
- Sustainable cities and communities