Abstract
In this paper a parallel version of an attraction based branch-and-bound method for global optimization is presented. The method has been implemented and tested using a parallel Scali system. Some well known test functions as well as two practical problems were used for the testing. The results show the prospectiveness of dynamic load balancing for the distributed parallelization of the considered algorithm.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Bibliography
Madsen, K.: Real versus interval methods for global optimization, Presentation at the Conference Celebrating the 60th Birthday of M. J. D. Powell, Cambridge, July 1996.
Madsen, K. and Žilinskas, J.: Evaluating performance of attraction based subdivision method for global optimization, In: Second International Conference “Simulation, Gaming, Training and Business Process Reengineering in Operations”, RTU, Latvia, 2000, pp. 38–42.
Gudmundsson, S.: Parallel Global Optimization, M.Sc. Thesis, IMM, Technical University of Denmark, 1998.
Message Passing Interface Forum. MPI: A Message-Passing Interface standard (version 1.1), Technical Report, 1995. http://www.mpi-forum.org.
Rayward-Smith, V. J., Rush, S. A. and McKeown, G. P.: Efficiency considerations in the implementation of parallel branch-and-bound, Ann. Oper. Res. 43 (1993), 123–145.
Madsen, K. and Žilinskas, J.: Testing of branch-and-bound methods for global optimization, IMM-REP-2000-05, Department of Mathematical Modelling, Technical University of Denmark, DK-2800 Lyngby, Denmark, 2000.
Madsen, K.: Test problems for global optimization, http://www.imm.dtu.dk/~km/GlobOpt/testex/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Kluwer Academic Publishers
About this chapter
Cite this chapter
Madsen, K., Žilinskas, J. (2002). Parallel Branch-and-bound Attraction Based Methods for Global Optimzation. In: Dzemyda, G., Šaltenis, V., Žilinskas, A. (eds) Stochastic and Global Optimization. Nonconvex Optimization and Its Applications, vol 59. Springer, Boston, MA. https://doi.org/10.1007/0-306-47648-7_10
Download citation
DOI: https://doi.org/10.1007/0-306-47648-7_10
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4020-0484-1
Online ISBN: 978-0-306-47648-8
eBook Packages: Springer Book Archive