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Iterative Optimization RCO: A “Ruler & Compass” Deterministic Method

Author

Listed:
  • Maurice Clerc

    (Independent Consultant, 74570 Groisy, France
    Laboratory of Images Signals and Intelligent Systems (LiSSi), University of Paris-Est Créteil (UPEC), 94000 Créteil, France)

Abstract

We present a basic version of a deterministic iterative optimization algorithm that requires only one parameter and is often capable of finding a good solution after very few evaluations of the fitness function. We demonstrate its principles using a multimodal one-dimensional problem. For such problems, the algorithm could be applied with just a ruler and a compass, which is how it got its name. We also provide classical examples and compare its performance with six well-known stochastic optimizers. These comparisons highlight the strengths and weaknesses of RCO. Since this version does not address potential stagnation, it is best suited for low-dimensional problems (typically no more than ten), where each evaluation of a position in the search space is computationally expensive.

Suggested Citation

  • Maurice Clerc, 2024. "Iterative Optimization RCO: A “Ruler & Compass” Deterministic Method," Mathematics, MDPI, vol. 12(23), pages 1-19, November.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:23:p:3755-:d:1532114
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