A limited-memory algorithm for bound-constrained optimization
- Univ. of Colorado, Boulder, CO (United States). Computer Science Dept.
- Northwestern Univ., Evanston, IL (United States). Dept. of Electrical Engineering and Computer Science
An algorithm for solving large nonlinear optimization problems with simple bounds is described. It is based on the gradient projection method and uses a limited-memory BFGS matrix to approximate the Hessian of the objective function. We show how to take advantage of the form of the limited-memory approximation to implement the algorithm efficiently. The results of numerical tests on a set of large problems are reported.
- Research Organization:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- W-31109-ENG-38
- OSTI ID:
- 204262
- Report Number(s):
- MCS-P404-1293; ON: DE96007638; TRN: 96:002130
- Resource Relation:
- Other Information: PBD: [1996]
- Country of Publication:
- United States
- Language:
- English
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