Mathematical Modeling and Information Acquisition:  An      Integrated Approach for Dynamic Decision-Making
{'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}
Many operational problems encountered in practice require dynamic               decision-making based on incomplete information about the constantly            changing operating environment.  Often decision-makers have the                 opportunity to acquire additional information about the current state           of the system before making a decision.  Obtaining more information             enables the use of a more accurate and detailed model, thus improving           the quality of final decisions as measured, for instance, by the                expected payoff.  However, acquiring information is usually expensive           (especially if imputed costs for time delays are included), with                higher costs incurred for more accurate and extensive information.              Thus, gathering complete information may not always be cost effective.          The proposed research explores this cost-benefit tradeoff in contexts           where operations research models are employed for decision-making.              Rather than separate the problem specification from the model                   formulation and optimization, the two are treated in an integrated              manner.  A 'meta' model is defined for evaluating the tradeoff between          improving the quality of decisions through increased model precision            and the cost of information acquisition to achieve the increased                precision.  The problem of routing messages in a network is examined            in this framework and both optimal meta algorithms and good heuristic           approaches are proposed for solving the problem.                                                                                                                In a recent N.S.F. sponsored workshop entitled "OR - The Next Decade,"          one of the research topics emphasized was the development of a theory           on the trade-off between data gathering, model specification, and               decision-making.  The results from this research should advance                 knowledge in that area.
[{'FirstName': 'Anantaram', 'LastName': 'Balakrishnan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anantaram Balakrishnan', 'EmailAddress': 'anantb@mail.utexas.edu', 'NSF_ID': '000107134', 'StartDate': '04/15/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Andrew', 'LastName': 'Whinston', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrew B Whinston', 'EmailAddress': 'abw@uts.cc.utexas.edu', 'NSF_ID': '000186235', 'StartDate': '04/15/1988', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
{'Name': 'Purdue Research Foundation', 'CityName': 'WEST LAFAYETTE', 'ZipCode': '479064353', 'PhoneNumber': '3174946200', 'StreetAddress': '1281 WIN HENTSCHEL BLVD STE 2500', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IN04', 'ORG_UEI_NUM': 'C1G1LGYJF5G5', 'ORG_LGL_BUS_NAME': 'PURDUE RESEARCH FOUNDATION', 'ORG_PRNT_UEI_NUM': 'YRXVL4JYCEF5'}
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{'Code': '1454', 'Text': 'SYSTEMS THEORY'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8718634.xml'}