Mono-Objective Function Analysis Using an Optimization Approach

In this paper we propose an evolutionary technique based in a Lyapunov method for mono-objective optimization, that associate to every ergodic controllable finite Markov Chains a Lyapunov-like mono-objective function. For representing the trajectory dynamics properties local-optimal policies are def...

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Detalhes bibliográficos
Autor: Clepner Kerik, Julio Bernardo
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2014
País:México
Recursos:Instituto Politécnico Nacional
Repositório:Repositorio Digital del IPN
OAI Identifier:oai:www.repositoriodigital.ipn.mx:123456789/19796
Acesso em linha:http://www.repositoriodigital.ipn.mx/handle/123456789/19796
Access Level:Acceso aberto
Palavra-chave:Lyapunov
problem solving control methods
search heuristic methods
artificial intelligence
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spelling Mono-Objective Function Analysis Using an Optimization ApproachClepner Kerik, Julio BernardoLyapunovproblem solving control methodssearch heuristic methodsartificial intelligenceIn this paper we propose an evolutionary technique based in a Lyapunov method for mono-objective optimization, that associate to every ergodic controllable finite Markov Chains a Lyapunov-like mono-objective function. For representing the trajectory dynamics properties local-optimal policies are defined to minimize the one-step decrement of the cost-function. We propose a state-value function that increase and decrease between states of the Markov decision processes. Then, we show that a Lyapunov mono-objective function, which can only decrease over time, can be built for the system. For illustration purposes, we present a simulated experiment that shows the trueness of the suggested method.Instituto Politécnico Nacional. CIECASAnálisis de funcionespdfIEEE LATIN AMERICA TRANSACTIONS, VOL. 12, NO. 22014-08-21T14:11:16Z2014-08-21T14:11:16Z2014-03info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleIEEE South Brazil1548-0992http://www.repositoriodigital.ipn.mx/handle/123456789/19796reponame:Repositorio Digital del IPNinstname:Instituto Politécnico Nacionalinstacron:IPNesinfo:eu-repo/semantics/openAccessoai:www.repositoriodigital.ipn.mx:123456789/197962026-02-18T16:47:32Z
dc.title.none.fl_str_mv Mono-Objective Function Analysis Using an Optimization Approach
title Mono-Objective Function Analysis Using an Optimization Approach
spellingShingle Mono-Objective Function Analysis Using an Optimization Approach
Clepner Kerik, Julio Bernardo
Lyapunov
problem solving control methods
search heuristic methods
artificial intelligence
title_short Mono-Objective Function Analysis Using an Optimization Approach
title_full Mono-Objective Function Analysis Using an Optimization Approach
title_fullStr Mono-Objective Function Analysis Using an Optimization Approach
title_full_unstemmed Mono-Objective Function Analysis Using an Optimization Approach
title_sort Mono-Objective Function Analysis Using an Optimization Approach
dc.creator.none.fl_str_mv Clepner Kerik, Julio Bernardo
author Clepner Kerik, Julio Bernardo
author_facet Clepner Kerik, Julio Bernardo
author_role author
dc.subject.none.fl_str_mv Lyapunov
problem solving control methods
search heuristic methods
artificial intelligence
topic Lyapunov
problem solving control methods
search heuristic methods
artificial intelligence
description In this paper we propose an evolutionary technique based in a Lyapunov method for mono-objective optimization, that associate to every ergodic controllable finite Markov Chains a Lyapunov-like mono-objective function. For representing the trajectory dynamics properties local-optimal policies are defined to minimize the one-step decrement of the cost-function. We propose a state-value function that increase and decrease between states of the Markov decision processes. Then, we show that a Lyapunov mono-objective function, which can only decrease over time, can be built for the system. For illustration purposes, we present a simulated experiment that shows the trueness of the suggested method.
publishDate 2014
dc.date.none.fl_str_mv 2014-08-21T14:11:16Z
2014-08-21T14:11:16Z
2014-03
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv IEEE South Brazil
1548-0992
http://www.repositoriodigital.ipn.mx/handle/123456789/19796
identifier_str_mv IEEE South Brazil
1548-0992
url http://www.repositoriodigital.ipn.mx/handle/123456789/19796
dc.language.none.fl_str_mv es
language_invalid_str_mv es
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv IEEE LATIN AMERICA TRANSACTIONS, VOL. 12, NO. 2
publisher.none.fl_str_mv IEEE LATIN AMERICA TRANSACTIONS, VOL. 12, NO. 2
dc.source.none.fl_str_mv reponame:Repositorio Digital del IPN
instname:Instituto Politécnico Nacional
instacron:IPN
instname_str Instituto Politécnico Nacional
instacron_str IPN
institution IPN
reponame_str Repositorio Digital del IPN
collection Repositorio Digital del IPN
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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