Parallel scalable algorithms with mixed local-global strategy for global optimization problems

Authors:
Konstantin Barkalov;Vasily Ryabov;Sergey Sidorov
Affiliations:
Nizhni Novgorod State University, Nizhni Novgorod, Russia;Nizhni Novgorod State University, Nizhni Novgorod, Russia;Nizhni Novgorod State University, Nizhni Novgorod, Russia
Venue:
MTPP'10 Proceedings of the Second Russia-Taiwan conference on Methods and tools of parallel programming multicomputers
Year:
2010

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Abstract

This paper continues development of information-statistical approach to minimization of multiextremal functions in the case of non-convex constraints. Proposed approach is called index method. Solving multidimensional problem is reduced to solving equivalent single dimensional one. Dimension reduction is based on Peano curves that allow mapping multidimensional hyper cube onto the segment on real axis. We also use rotating Peano curves that allowed effectively parallelize algorithm to use hundreds of processors. Special attention was paid to mixed local-global strategy for algorithm convergence acceleration.