Sensitivity Analysis of Queueing Systems
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Radhakisan Baheti', 'PO_EMAI': None, 'PO_PHON': None}
Sensitivity analysis of discrete event systems is an area that has              recently attracted the attention of a number of researchers.  Two               general approaches have been proposed, perturbation analysis and the            likelihood ratio method, that provide efficient estimates of parameter          sensitivities for analytically intractable systems.  Infinitesimal              perturbation analysis estimates in particular are very attractive               because they are easy to obtain, have small computational requirements          and low variance.  However, their usefulness is limited by the fact             that they are biased in many cases.                                                                                                                             The proposed research is to investigate the possibility of using                compensator identities in combination with perturbation methods in              order to derive unbiased, low variance sensitivity estimates.  Initial          success in deriving estimates for the second derivative of the mean             response time and of occupancy probabilities for the GI/G/1 queue               justify confidence in this approach.                                                                                                                            The results of this study will be directly applicable in all the cases          where discrete event simulation is used for sensitivity analysis and            optimization of real systems and more specifically in manufacturing             systems and data communication networks.
{'FirstName': 'Michael', 'LastName': 'Zazanis', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael A Zazanis', 'EmailAddress': 'zazanis@ecs.umass.edu', 'NSF_ID': '000092851', 'StartDate': '09/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'ZipCode': '602080001', 'PhoneNumber': '3125037955', 'StreetAddress': '633 CLARK ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'IL09', 'ORG_UEI_NUM': 'EXZVPWZBLUE8', 'ORG_LGL_BUS_NAME': 'NORTHWESTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '1454', 'Text': 'SYSTEMS THEORY'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8811003.xml'}