Parameter-Free Deterministic Global Search with Simplified Central Force Optimization

  • Richard A. Formato
Conference paper

DOI: 10.1007/978-3-642-14922-1_39

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6215)
Cite this paper as:
Formato R.A. (2010) Parameter-Free Deterministic Global Search with Simplified Central Force Optimization. In: Huang DS., Zhao Z., Bevilacqua V., Figueroa J.C. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Lecture Notes in Computer Science, vol 6215. Springer, Berlin, Heidelberg

Abstract

This note describes a simplified parameter-free implementation of Central Force Optimization for use in deterministic multidimensional search and optimization. The user supplies only the objective function to be maximized, nothing more. The algorithm’s performance is tested against a widely used suite of twenty three benchmark functions and compared to other state-of-the-art algorithms. CFO performs very well.

Keywords

Central Force Optimization CFO Deterministic Algorithm Multidimensional Search and Optimization Parameter-Free Optimization Gravitational Kinematics Metaphor Metaheuristic 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Richard A. Formato
    • 1
  1. 1.Registered Patent Attorney & Consulting EngineerHarwichUSA

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