Journal of Optimization Theory and Applications

, Volume 75, Issue 3, pp 635–638

Importance of search-domain reduction in random optimization

Authors

  • R. Spaans
    • Department of Chemical EngineeringUniversity of Toronto
  • R. Luus
    • Department of Chemical EngineeringUniversity of Toronto
Technical Note

DOI: 10.1007/BF00940497

Cite this article as:
Spaans, R. & Luus, R. J Optim Theory Appl (1992) 75: 635. doi:10.1007/BF00940497

Abstract

The importance of incorporating systematic search-domain reduction into random optimization is illustrated. In the absence of domain reduction, even an enormous number of function evaluations does not ensure convergence sufficiently close to the optimum as was recently reported by Sarma. However, when the search domain is reduced systematically after every iteration as recommended by Luus and Jaakola, convergence is obtained in a relatively small number of function evaluations, even when the initial search region is large and the starting point is far from the optimum.

Key Words

Random optimizationsearch-domain reductionnumerical convergence

Copyright information

© Plenum Publishing Corporation 1992