Mathematical Sciences: Theoretical and Algorithmic Studies  in Combinatorial Problem-Solving
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Mathematical programming is concerned with the optimization of                  functions in many variables subject to side constraints.  Combinatorial         optimization addresses the same problem with an additional complication         brought about by the inclusion of indivisible activities, i.e., by              variables that must assume integer values.  In purely combinatorial             problems, all variables must be integer.  Since its inception shortly           after World War II, mathematical programming ideas have been                    successfully utilized to formulate and to solve many complex planning           problems, with applications covering the entire range from the                  quantitative social sciences to engineering science.  The increased             ability to numerically solve mathematical programming problems has              brought about a greater demand to incorporate indivisible activities            into the planning models.  This research aims to extend the                     computational frontiers of combinatorial problem-solving as well as to          achieve a better mathematical understanding of combinatorial                    optimization problems.
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[{'Code': '1266', 'Text': 'APPLIED MATHEMATICS'}, {'Code': '1454', 'Text': 'SYSTEMS THEORY'}]
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