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

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 probl...

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Main Author: Maurice Clerc
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Mathematics
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Online Access:https://www.mdpi.com/2227-7390/12/23/3755
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author Maurice Clerc
author_facet Maurice Clerc
author_sort Maurice Clerc
collection DOAJ
description 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.
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spelling doaj-art-9cbb7c29f02849b99866411fb65622a62024-12-13T16:27:38ZengMDPI AGMathematics2227-73902024-11-011223375510.3390/math12233755Iterative Optimization RCO: A “Ruler & Compass” Deterministic MethodMaurice Clerc0Independent Consultant, 74570 Groisy, FranceWe 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.https://www.mdpi.com/2227-7390/12/23/3755optimizationiterativedeterministic
spellingShingle Maurice Clerc
Iterative Optimization RCO: A “Ruler & Compass” Deterministic Method
Mathematics
optimization
iterative
deterministic
title Iterative Optimization RCO: A “Ruler & Compass” Deterministic Method
title_full Iterative Optimization RCO: A “Ruler & Compass” Deterministic Method
title_fullStr Iterative Optimization RCO: A “Ruler & Compass” Deterministic Method
title_full_unstemmed Iterative Optimization RCO: A “Ruler & Compass” Deterministic Method
title_short Iterative Optimization RCO: A “Ruler & Compass” Deterministic Method
title_sort iterative optimization rco a ruler compass deterministic method
topic optimization
iterative
deterministic
url https://www.mdpi.com/2227-7390/12/23/3755
work_keys_str_mv AT mauriceclerc iterativeoptimizationrcoarulercompassdeterministicmethod