Efficient Algorithms for Multiple Instance Combinatorial    Problems
{'Code': '05010100', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
{'SignBlockName': 'Dana S. Richards', 'PO_EMAI': None, 'PO_PHON': None}
This project will focus largely on problems of multiple instance                network flow computations. Many important, non-trivial combinatorial            problems can be cast and solved as a sequence of closely related                network flow computations.  Recent results have led to improved                 efficiency in computing such sequences, and in turn this has lead to            faster solutions to important combinatorial problems.  This project             will extend recent work, concentrating on general methods to specific           important combinatorial problems.  In particular, two general classes           of sequence will be assumed:  parametric network flow problems, where           the sequence is generated by changing the capacities of certain edges,          and multiple source-sink problems, where the sequence are generated by          changing the choices of source and sink nodes.
{'FirstName': 'Daniel', 'LastName': 'Gusfield', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Daniel Gusfield', 'EmailAddress': 'gusfield@cs.ucdavis.edu', 'NSF_ID': '000311391', 'StartDate': '07/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
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[{'Code': '1454', 'Text': 'SYSTEMS THEORY'}, {'Code': '2860', 'Text': 'THEORY OF COMPUTING'}, {'Code': '9120', 'Text': 'CROSS-DIRECTORATE PROGRAMS'}]
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