International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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On the Global Convergence of Univariate Dynamic Encoding Algorithm for Searches (uDEAS)

  • Kim, Jong-Wook (Department of Electronics Engineering, Dang-A University) ;
  • Kim, Tae-Gyu (Department of Electronics Engineering, Dang-A University) ;
  • Choi, Joon-Young (Department of Electronic Engineering, Pusan National University) ;
  • Kim, Sang-Woo (Electrical and Computer Engineering Division, Pohang University of Science and Technology)
  • Published : 2008.08.31
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Abstract

This paper analyzes global convergence of the univariate dynamic encoding algorithm for searches (uDEAS) and provides an application result to function optimization. uDEAS is a more advanced optimization method than its predecessor in terms of the number of neighborhood points. This improvement should be validated through mathematical analysis for further research and application. Since uDEAS can be categorized into the generating set search method also established recently, the global convergence property of uDEAS is proved in the context of the direct search method. To show the strong performance of uDEAS, the global minima of four 30 dimensional benchmark functions are attempted to be located by uDEAS and the other direct search methods. The proof of global convergence and the successful optimization result guarantee that uDEAS is a reliable and effective global optimization method.

Keywords

References

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