Nonlinearly-constrained optimization using heuristic penalty methods and asynchronous parallel generating set search

@inproceedings{Griffin2010NonlinearlyconstrainedOU,
  title={Nonlinearly-constrained optimization using heuristic penalty methods and asynchronous parallel generating set search},
  author={Joshua D. Griffin and Tamara G. Kolda},
  year={2010}
}
Many optimization problems are characterized by expensive objective and/or constraint function evaluations paired with a lack of derivative information. Direct search methods such as generating set search (GSS) are well understood and efficient for derivative-free optimization of unconstrained and linearly-constrained problems. This paper presents a study of heuristic algorithms that address the more difficult problem of general nonlinear constraints where derivatives for objective or… CONTINUE READING
Highly Cited
This paper has 25 citations. REVIEW CITATIONS
17 Citations
41 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 17 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 41 references

and Ph

  • N.I.M. Gould, D. Orban
  • L. Toint, CUTEr and SifDec: a constrained and…
  • 2003
Highly Influential
5 Excerpts

Generalized exponential penalty function for nonlinear programming

  • J. Qin, D. T. Nguyen
  • AIAA/ASME/ASCE/AHS/ASC Structures, Structural…
  • 1994
Highly Influential
4 Excerpts

On the exactness of a class of nondifferentiable penalty functions

  • G. Di Pillo, L. Grippo
  • Journal of Optimization Theory and Applications…
  • 1988
Highly Influential
4 Excerpts

On solving multifacility location problems using a hyperboloid approximation procedure

  • J. Eyster, J. White, W. Wierwille
  • AIIE Transactions, 5
  • 1973
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…