On the reduced-set pareto-lipschitzian optimization

<p>A well-known example of global optimization that provides solutions within fixed error limits is optimization of functions with a known Lipschitz constant. In many real-life problems this constant is unknown.</p> <p>To address that a method called Pareto-Lipschitzian Optimizatio...

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Main Authors: Jonas Mockus, Remigijus Paulavičius
Format: Article
Language:English
Published: Klaipėda University 2013-09-01
Series:Computational Science and Techniques
Online Access:http://journals.ku.lt/index.php/CST/article/view/84
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author Jonas Mockus
Remigijus Paulavičius
author_facet Jonas Mockus
Remigijus Paulavičius
author_sort Jonas Mockus
collection DOAJ
description <p>A well-known example of global optimization that provides solutions within fixed error limits is optimization of functions with a known Lipschitz constant. In many real-life problems this constant is unknown.</p> <p>To address that a method called Pareto-Lipschitzian Optimization (PLO) was described that provides solutions within fixed error limits for functions with unknown Lipschitz constants. In this approach, a set of all unknown Lipschitz constants is regarded as multiple criteria using the concept of Pareto Optimality (PO).</p> <p>In this paper, a new version of the Pareto-Lipschitzian Optimization method (PLOR) is proposed where a set of unknown Lipschitzian constants is reduced just to the minimal and maximal ones. In the both methods, partition patterns are similar to those of DIRECT. The difference is in the rules of sequential partitions defining non-dominated sets. In PLO, it includes all Pareto-Optimal sets defined by all Lipschitz constants. In PLOR, it considers just two elements corresponding to the maximal and minimal Lipschitz constant. in DIRECT, it selects a part of the Pareto-Optimal set which is determined by some heuristic parameter .</p>
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spelling doaj.art-7b2af3fe090b4addaa6761a480fc11132022-12-21T18:21:45ZengKlaipėda UniversityComputational Science and Techniques2029-99662013-09-011218419210.15181/csat.v1i2.8493On the reduced-set pareto-lipschitzian optimizationJonas Mockus0Remigijus Paulavičius1VU MIILithuanian University of Educational Sciences<p>A well-known example of global optimization that provides solutions within fixed error limits is optimization of functions with a known Lipschitz constant. In many real-life problems this constant is unknown.</p> <p>To address that a method called Pareto-Lipschitzian Optimization (PLO) was described that provides solutions within fixed error limits for functions with unknown Lipschitz constants. In this approach, a set of all unknown Lipschitz constants is regarded as multiple criteria using the concept of Pareto Optimality (PO).</p> <p>In this paper, a new version of the Pareto-Lipschitzian Optimization method (PLOR) is proposed where a set of unknown Lipschitzian constants is reduced just to the minimal and maximal ones. In the both methods, partition patterns are similar to those of DIRECT. The difference is in the rules of sequential partitions defining non-dominated sets. In PLO, it includes all Pareto-Optimal sets defined by all Lipschitz constants. In PLOR, it considers just two elements corresponding to the maximal and minimal Lipschitz constant. in DIRECT, it selects a part of the Pareto-Optimal set which is determined by some heuristic parameter .</p>http://journals.ku.lt/index.php/CST/article/view/84
spellingShingle Jonas Mockus
Remigijus Paulavičius
On the reduced-set pareto-lipschitzian optimization
Computational Science and Techniques
title On the reduced-set pareto-lipschitzian optimization
title_full On the reduced-set pareto-lipschitzian optimization
title_fullStr On the reduced-set pareto-lipschitzian optimization
title_full_unstemmed On the reduced-set pareto-lipschitzian optimization
title_short On the reduced-set pareto-lipschitzian optimization
title_sort on the reduced set pareto lipschitzian optimization
url http://journals.ku.lt/index.php/CST/article/view/84
work_keys_str_mv AT jonasmockus onthereducedsetparetolipschitzianoptimization
AT remigijuspaulavicius onthereducedsetparetolipschitzianoptimization