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