Accession Number : ADA573242
Title : Stochastic Semidefinite Programming: Applications and Algorithms
Descriptive Note : Final rept. 26 Sep 2008-31 Dec 2011
Corporate Author : WASHINGTON STATE UNIV PULLMAN OFFICE OF THE VICE PROVOST FOR RESEARCH GRANT AND RESEARCH DEVELOPMENT
Personal Author(s) : Ariyawansa, K A
Full Text : http://www.dtic.mil/get-tr-doc/pdf?AD=ADA573242
Report Date : 03 Mar 2012
Pagination or Media Count : 13
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.
Descriptors : *COMPUTER PROGRAMMING , *STOCHASTIC PROCESSES , ALGORITHMS , CONVERGENCE , OPTIMIZATION , POLYNOMIALS , STUDENTS
Subject Categories : Statistics and Probability
Computer Programming and Software
Distribution Statement : APPROVED FOR PUBLIC RELEASE
