On the Efficiency and Effectiveness of Controlled Random Search

  • Eligius M. T. Hendrix
  • Pilar M. Ortigosa
  • Inmaculada Garcia
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 59)


Applying evolutionary algorithms based on populations of trial points is attractive in many fields nowadays. Apart from the evolutionary analogy, profound analysis on their performance is lacking. In this paper, within a framework to study the behaviour of algorithms, an analysis is given on the performance of Controlled Random Search (CRS), a simple population based Global Optimization algorithm. The question is for which functions (cases) and which parameter settings the algorithm is effective and how the efficiency can be influenced. For this, several performance indicators are described. Analytical and experimental results on effectiveness and speed of convergence (Success Rate) of CRS are presented.


Controlled Random Search speed of convergence smooth optimization stochastic algorithms evolutionary algorithms effectiveness 


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Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Eligius M. T. Hendrix
    • 1
  • Pilar M. Ortigosa
    • 2
  • Inmaculada Garcia
    • 2
  1. 1.Group Operations Research and LogisticsWageningen UniversityWageningenThe Netherlands
  2. 2.Computer Architecture & Electronics Dpt.University of AlmeríaAlmeríaSpain

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