Constraint Integer Programming
J. Christopher Beck
Complex scheduling problems are challenging and studied by researchers from different communities such as mixed integer programming (MIP) and constraint programming (CP).
The interest of combining modeling and solving techniques from MIP and CP has arisen recently, because such a hybrid approach has shown to be successful on solving optimization
problems that were difficult with either of the two approaches alone. Constraint integer programming (CIP), unlike decomposition approaches that decompose a problem into a master
problem (MIP) and subproblems (CP), is a lower level integration of MIP and CP where all involved algorithms are performed on a single search tree. The main objective of this
project is to further develop CIP that utilize the complementary strengths of MIP and CP, as well as applying CIP to solve hard scheduling problems efficiently.
University of Toronto Fellowship
TIDEL Research Assistantship