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Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/7924

Title: Combining neighbourhoods in fuzzy job shop problems
Author(s): Puente Peinador, Jorge
Rodríguez Vela, María del Camino
González Rodríguez, Inés
Issue date: 2011
Publisher: Springer
Publisher version: http://dx.doi.org/10.1007/978-3-642-25274-7_35
Citation: Advances in Artificial Intelligence, p. 343-352 (2011); doi:10.1007/978-3-642-25274-7_35
Series/Report no.: Lecture Notes in Computer Science;7023
Format extent: p. 343-352
Abstract: In the sequel, we propose a new neighbourhood structure for local search for the fuzzy job shop scheduling problem, which is a variant of the well-known job shop problem, where uncertain durations are modelled as fuzzy numbers and the objective is to minimise the expected makespan of the resulting schedule. The new neighbourhood structure is based on changing the position of a task in a critical block. We provide feasibility conditions and a makespan estimate which allows to select only feasible and promising neighbours. The experimental results illustrate the success of our proposal in reducing expected makespan within a memetic algorithm. The experiments also show that combining the new structure with an existing neighbourhood from the literature considering both neighborhoods at the same time, provides the best results
Description: Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2011(14th. 2011. La Laguna, Spain)
URI: http://hdl.handle.net/10651/7924
ISBN: 978-3-642-25273-0
ISSN: 0302-9743
Local identifier: 20111662
Sponsored: All authors are supported by MEC-FEDER Grant TIN2010-20976-C02-02
Project id.: MEC-FEDER/TIN2010-20976-C02-02
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