A Robust-Solution-Based Methodology to Solve Multiple-Objective Problems with Uncertainty

Daniel Salazar (), Xavier Gandibleux (), Julien Jorge () and Marc Sevaux ()
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Daniel Salazar: University of Las Palmas de Gran Canaria Edif. Polivalente
Xavier Gandibleux: FRE CNRS 2729—Université de Nantes. 2, rue de la Houssiniére
Julien Jorge: FRE CNRS 2729—Université de Nantes. 2, rue de la Houssiniére
Marc Sevaux: University of South Brittany Center de recherche

A chapter in Multiobjective Programming and Goal Programming, 2009, pp 197-207 from Springer

Abstract: Abstract This paper presents the formulation and evaluation of a methodology to solve multiple-objective problems in the presence of uncertainty based on robustness. The methods were developed regarding a Particular real “Released when Completing blocking (RCb)” scheduling flowshop problem characterized by several equivalent solutions, but they can be extended to another robustness problems.

Keywords: Flowshop scheduling problem; Genetic algorithm; Multiobjective evolutionary algorithm; Multiobjective simulated annealing; Robustness; Robust schedule; Release when completing blocking (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-540-85646-7_19

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DOI: 10.1007/978-3-540-85646-7_19

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