Parallel cross-entropy optimization

The Cross-Entropy (CE) method is a modern and effective optimization method well suited to parallel implementations. There is a vast array of problems today, some of which are highly complex and can take weeks or even longer to solve using current optimization techniques. This paper presents a general method for designing parallel CE algorithms for Multiple Instruction Multiple Data (MIMD) distributed memory machines using the Message Passing Interface (MPI) library routines. We provide examples of its performance for two well-known test-cases: the (discrete) Max-Cut problem and (continuous) Rosenbrock problem. Speedup factors and a comparison to sequential CE methods are reported.

• Type: Conference
• Year: 2007
• Where: WSC
• Authors: Gareth E. Evans, Jonathan M. Keith, Dirk P. Kroese
• Keywords: Effective Optimization Method, Modeling And Simulation, Parallel Ce Algorithms, Sequential Ce Methods, WSC 2007