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/dtic/tr/fulltext/u2/a573242.pdf

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