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Accession Number ADA573242
Title Stochastic Semidefinite Programming: Applications and Algorithms.
Publication Date Mar 2012
Media Count 13p
Personal Author K. A. Ariyawansa
Abstract Stochastic semidefinite programs (SSDP's) are a new class of optimization problems with a wide variety applications proposed by the PI and his doctoral students. The broad objective of this project was to develop applications of and algorithms for SSDP's. We have developed five classes of novel applications, and three classes of new algorithms. We have proved the convergence and polynomial complexity of the algorithms. We have also identified two new classes of optimization problems which may be useful for future research.
Keywords Algorithms
Computational complexity
Computer programming
Convergence
Interior point algorithms
Optimization
Polynomials
Semidefinite programming
Ssdp(Stochastic semifinite programs)
Stochastic processes
Stochastic programming
Stochastic semidefinite programming
Students

 
Source Agency Non Paid ADAS
NTIS Subject Category 72F - Statistical Analysis
62B - Computer Software
Corporate Author Washington State Univ., Pullman. Office of the Vice Provost for Research Grant and Research Development.
Document Type Technical report
Title Note Final rept. 26 Sep 2008-31 Dec 2011.
NTIS Issue Number 1317
Contract Number W911NF-08-1-0530

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