A new method for decision making in multi-objective optimization problems

Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespre...

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Main Authors: Oscar Brito Augusto, Fouad Bennis, Stephane Caro
Format: Article
Language:English
Published: Sociedade Brasileira de Pesquisa Operacional 2012-08-01
Series:Pesquisa Operacional
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382012000200005&lng=en&tlng=en
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spelling doaj-4ab037b09fb2489eb64f8f833ab800812020-11-24T22:11:23ZengSociedade Brasileira de Pesquisa OperacionalPesquisa Operacional1678-51422012-08-01322331369S0101-74382012000200005A new method for decision making in multi-objective optimization problemsOscar Brito Augusto0Fouad Bennis1Stephane Caro2Universidade de São PauloInstitut de Recherche en Communications et Cybernétique de NantesInstitut de Recherche en Communications et Cybernétique de NantesMany engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-dominated solutions, a Pareto set. Although it is very interesting to know the non-dominated solutions, an additional criterion is needed to select one solution to be deployed. To better support the design process, this paper presents a new method of solving non-linear multi-objective optimization problems by adding a control function that will guide the optimization process over the Pareto set that does not need to be found explicitly. The proposed methodology differs from the classical methods that combine the objective functions in a single scale, and is based on a unique run of non-linear single-objective optimizers.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382012000200005&lng=en&tlng=enmulti-objective optimizationmulti-attribute decision makingengineering design optimization
collection DOAJ
language English
format Article
sources DOAJ
author Oscar Brito Augusto
Fouad Bennis
Stephane Caro
spellingShingle Oscar Brito Augusto
Fouad Bennis
Stephane Caro
A new method for decision making in multi-objective optimization problems
Pesquisa Operacional
multi-objective optimization
multi-attribute decision making
engineering design optimization
author_facet Oscar Brito Augusto
Fouad Bennis
Stephane Caro
author_sort Oscar Brito Augusto
title A new method for decision making in multi-objective optimization problems
title_short A new method for decision making in multi-objective optimization problems
title_full A new method for decision making in multi-objective optimization problems
title_fullStr A new method for decision making in multi-objective optimization problems
title_full_unstemmed A new method for decision making in multi-objective optimization problems
title_sort new method for decision making in multi-objective optimization problems
publisher Sociedade Brasileira de Pesquisa Operacional
series Pesquisa Operacional
issn 1678-5142
publishDate 2012-08-01
description Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-dominated solutions, a Pareto set. Although it is very interesting to know the non-dominated solutions, an additional criterion is needed to select one solution to be deployed. To better support the design process, this paper presents a new method of solving non-linear multi-objective optimization problems by adding a control function that will guide the optimization process over the Pareto set that does not need to be found explicitly. The proposed methodology differs from the classical methods that combine the objective functions in a single scale, and is based on a unique run of non-linear single-objective optimizers.
topic multi-objective optimization
multi-attribute decision making
engineering design optimization
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382012000200005&lng=en&tlng=en
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