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Solving discrete resource allocation problems using the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm
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Source Spring Simulation Multiconference archive
Proceedings of the 2007 spring simulation multiconference - Volume 3 table of contents
Norfolk, Virginia
SESSION: Optimization/decision analysis table of contents
Pages 55-62  
Year of Publication: 2007
ISBN:1-56555-314-4
Author
Otis Brooks  The Johns Hopkins University Applied Physics Laboratory, Laurel, MD
Sponsors
SCS : Society for Modeling and Simulation International
ACM/SIGSIM : Association for Computing Machinery/Special Interest Group on Simulation
Publisher
Bibliometrics
Downloads (6 Weeks): 4,   Downloads (12 Months): 21,   Citation Count: 0
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ABSTRACT

We investigate optimization techniques for solving a class of discrete resource allocation problems, including several discrete forms of Simultaneous Perturbation Stochastic Optimization (SPSA). We explore the rate-of-convergence for discrete SPSA in a stochastic setting. Finally, we consider some of the difficulties that can arise when discrete resource allocation problems include a stochastic component.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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