Recent advances in large-scale nonlinear optimization
In this talk I will describe some important recent advances in nonlinear optimization, paying particular attention to the large-scale case. We will see that considerable progress has been made in algorithms for large unconstrained problems, and that a variety of efficient codes is beginning to emerge. I will also describe advances in trust region algorithms for constrained optimization, and show how they are leading to large-scale implementations. I will briefly touch on the topic of interior-point methods for nonlinear programming - a research area that is likely to bring a fresh point of view to nonlinear programming. Finally I will describe important advances in software, such as the LANCELOT package and the CUTE testing system, as well as the Minpack-2 library which will be the first nonlinear optimization package that addresses issues arising in high-performance computation.
- OSTI ID:
- 36343
- Report Number(s):
- CONF-9408161--
- Country of Publication:
- United States
- Language:
- English
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