A hybrid algorithm combining heuristics with Monte Carlo simulation for solving the Stochastic Flow Shop Problem

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dc.contributor	Universitat Politècnica de Catalunya. Departament de Matemàtica Aplicada I
dc.contributor.author	Juan Pérez, Angel Alejandro
dc.contributor.author	Peruyero, Esteban
dc.contributor.author	Riera Terrén, Daniel
dc.date	2011
dc.identifier.citation	Juan, A.; Peruyero, E.; Riera, D. A hybrid algorithm combining heuristics with Monte Carlo simulation for solving the Stochastic Flow Shop Problem. A: ALIO/EURO Workshop on Applied Combinatorial Optimization. "Proceedings of the VII ALIO/EURO Workshop on Applied Combinatorial Optimization". Porto: 2011, p. 129-132.
dc.identifier.uri	http://hdl.handle.net/2117/17571
dc.language.iso	eng
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa
dc.subject	Heuristic
dc.subject	Monte Carlo method
dc.subject	Heurística
dc.subject	Montecarlo, Mètode de
dc.title	A hybrid algorithm combining heuristics with Monte Carlo simulation for solving the Stochastic Flow Shop Problem
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	In this paper a hybrid simulation-based algorithm is proposed for the Stochastic Flow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation. To achieve this goal we use Monte Carlo simulation and a modified version of the well-known NEH heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

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