The Toronto Intelligent Decision Engineering Laboratory
Constraint Integer Programming

Constraint Integer Programming


J. Christopher Beck
Stefan Heinz
Wen-Yang Ku

Project description

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.

Start date

September 2011


University of Toronto Fellowship
TIDEL Research Assistantship


Coming soon.
University of Toronto Mechanical and Information Engineering