Wednesday, 15:45 - 16:10 h, Room: H 2032


Theodore Ralphs
Dip and DipPy: Towards a generic decomposition-based MIP solver

Coauthors: Matthew Galati, Michael O'Sullivan, Jiadong Wang


DIP is a software framework for simplifying the implementation of a range of decomposition-based algorithms for solving mixed integer linear optimization problems. It is based on an underlying theoretical framework that unifies a number of decomposition methods, such as Dantzig-Wolfe decomposition, Lagrangian elaxation, and cutting plane methods. Recent efforts have focused on the development of a generic decomposition-based solver, capable of automatically detecting block structure and utilizing an appropriate decomposition method to solve the problem. DipPy is a modeling language front end to DIP, which allows block structure to be explicitly identified in cases where such block structure is known to the modeler. This is done in a very natural way, making it easy for unsophisticated users to experiment with powerful methods such as column generation. In this talk, we discuss the latest developments and present computational results.


Talk 2 of the invited session Wed.3.H 2032
"Branch-and-price I: Generic solvers" [...]
Cluster 11
"Integer & mixed-integer programming" [...]


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