Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/8386
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dc.contributor.authorGrosan, C-
dc.contributor.authorAbraham, A-
dc.date.accessioned2014-05-06T15:37:14Z-
dc.date.available2014-05-06T15:37:14Z-
dc.date.issued2010-
dc.identifier.citationInformation Sciences, 180(14), 2674 - 2695, 2010en_US
dc.identifier.issn0020-0255-
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0020025509005489en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/8386-
dc.descriptionThis is the post-print version of the final paper published in Information Sciences. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.en_US
dc.description.abstractThe aggregation of objectives in multiple criteria programming is one of the simplest and widely used approach. But it is well known that this technique sometimes fail in different aspects for determining the Pareto frontier. This paper proposes a new approach for multicriteria optimization, which aggregates the objective functions and uses a line search method in order to locate an approximate efficient point. Once the first Pareto solution is obtained, a simplified version of the former one is used in the context of Pareto dominance to obtain a set of efficient points, which will assure a thorough distribution of solutions on the Pareto frontier. In the current form, the proposed technique is well suitable for problems having multiple objectives (it is not limited to bi-objective problems) and require the functions to be continuous twice differentiable. In order to assess the effectiveness of this approach, some experiments were performed and compared with two recent well known population-based metaheuristics namely ParEGO and NSGA II. When compared to ParEGO and NSGA II, the proposed approach not only assures a better convergence to the Pareto frontier but also illustrates a good distribution of solutions. From a computational point of view, both stages of the line search converge within a short time (average about 150 ms for the first stage and about 20 ms for the second stage). Apart from this, the proposed technique is very simple, easy to implement and use to solve multiobjective problems.en_US
dc.description.sponsorshipCNCSIS IDEI 2412, Romaniaen_US
dc.languageEnglish-
dc.language.isoenen_US
dc.publisherElsevier Science Inc.en_US
dc.subjectPareto frontieren_US
dc.subjectGlobal optimizationen_US
dc.subjectLine searchen_US
dc.subjectMetaheuristicsen_US
dc.subjectMultiobjective optimizationen_US
dc.titleApproximating Pareto frontier using a hybrid line search approachen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.ins.2009.12.018-
pubs.organisational-data/Brunel-
pubs.organisational-data/Brunel/Brunel Active Staff-
pubs.organisational-data/Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths-
pubs.organisational-data/Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths/Computer Science-
pubs.organisational-data/Brunel/University Research Centres and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/Brunel Business School - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/Brunel Business School - URCs and Groups/Centre for Research into Entrepreneurship, International Business and Innovation in Emerging Markets-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Arts - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Arts - URCs and Groups/Brunel Centre for Contemporary Writing-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute for Ageing Studies-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute of Cancer Genetics and Pharmacogenomics-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Centre for Systems and Synthetic Biology-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/Multidisclipary Assessment of Technology Centre for Healthcare (MATCH)-
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Computer Science
Dept of Computer Science Research Papers

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