Efficient interval partitioning for constrained global optimization

Authors:
Chandra Sekhar Pedamallu;Linet Özdamar;Tibor Csendes;Tamás Vinkó
Affiliations:
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore and New England Biolabs Inc., Ipswich, USA;Department of Systems Engineering, Yeditepe University, Istanbul, Turkey;Institute of Informatics, University of Szeged, Szeged, Hungary;ESA/ESTEC, Advanced Concepts Team, Noordwijk, The Netherlands
Venue:
Journal of Global Optimization
Year:
2008

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Abstract

A new efficient interval partitioning approach to solve constrained global optimization problems is proposed. This involves a new parallel subdivision direction selection method as well as an adaptive tree search. The latter explores nodes (intervals in variable domains) using a restricted hybrid depth-first and best-first branching strategy. This hybrid approach is also used for activating local search to identify feasible stationary points. The new tree search management technique results in improved performance across standard solution and computational indicators when compared to previously proposed techniques. On the other hand, the new parallel subdivision direction selection rule detects infeasible and suboptimal boxes earlier than existing rules, and this contributes to performance by enabling earlier reliable deletion of such subintervals from the search space.