Genetic Programming Applied to Mixed Integer Programming

Abstract

We present the application of Genetic Programming (GP) in Branch and Bound (B&B) based Mixed Integer Linear Programming (MIP). The hybrid architecture introduced employs GP as a node selection expression generator: a GP run, embedded into the B&B process, exploits the characteristics of the particular MIP problem being solved, evolving a problem-specific node selection method. The evolved method replaces the default one for the rest of the B&B. The hybrid approach outperforms depth-first and breadth-first search, and compares well with the advanced Best Projection method. © Springer-Verlag 2004.