Testing Solution Algorithms for Bilevel Programming         Transportation Models in a Mixed Economic System
{'Code': '04040400', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}
{'SignBlockName': 'Thomas Baerwald', 'PO_EMAI': None, 'PO_PHON': None}
Attempts to develop models to predict the impacts of public                policies on the actions of individuals and private organizations have           been complicated by the fact that private actors generally pursue their         own interests, while public-sector agencies operate consistently with           what they perceive to be the collective public interest.  Governmental          development of a transportation system, for example, will have impacts          on movements and facility locations of individuals and corporations,            which in turn will affect performance on the transport system and               create new demands on it.  In the last decade, regional scientists and          economists have begun development of bi-level mathematical models that          represent and simulate the interaction between public and private               decisions.  Tests of these models have been small examples, because             efficient procedures (algorithms) have not been developed to determine          optimal solutions when large data sets (such as those that would                represent real-world problems) are used.  This project will develop and         test new algorithms to solve large bi-level programming models for              mixed public-private transportation systems.  The research will proceed         in three steps.  First, a large-scale bi-level transportation planning          model linking public- and private-sector decisions will be refined.             Second, a set of solution algorithms will be developed and tested to            enable the model's use on a supercomputer with data on a large Korean           transportation network.  Finally, the validity of the model and the             solution algorithm as a means of establishing public policies will be           analyzed.                                                                            Theoretical and methodological benefits will result from this              project.  Theoretical advances will be made by determining the extent           to which bi-level programming models help explain and predict public            and private interactions and by assessing how they can assist in the            formation of public policy.  Methodological advances will be made               through development of one or more efficient solution algorithms for            bi-level models when using supercomputers.  Better assessments of the           speed and costs of such models also will be available.  This research           therefore will expand our understandings of how public- and private-            sector actors relate in modern settlements, and it will increase our            knowledge of how mathematical modelling procedures can be used to               address complex social problems.
{'FirstName': 'Tschangho', 'LastName': 'Kim', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tschangho J Kim', 'EmailAddress': 'tjohnkim@illinois.edu', 'PI_PHON': '2172445369', 'NSF_ID': '000168346', 'StartDate': '09/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Illinois at Urbana-Champaign', 'CityName': 'URBANA', 'ZipCode': '618013620', 'PhoneNumber': '2173332187', 'StreetAddress': '506 S WRIGHT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'IL13', 'ORG_UEI_NUM': 'Y8CWNJRCNN91', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ILLINOIS', 'ORG_PRNT_UEI_NUM': None}
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[{'Code': '1352', 'Text': 'Geography and Spatial Sciences'}, {'Code': '5942', 'Text': 'KOREA'}, {'Code': '9120', 'Text': 'CROSS-DIRECTORATE PROGRAMS'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8718146.xml'}