Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/19423
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: On the automatic discovery of variants of the NEH procedure for flow shop scheduling using genetic programming
Authors: Vazquez-Rodriguez, Jose Antonio
Ochoa, Gabriela
Contact Email: gabriela.ochoa@stir.ac.uk
Keywords: heuristics
production
genetic programming
genetic algorithms
hyper-heuristics
Issue Date: Feb-2011
Publisher: Palgrave Macmillan
Citation: Vazquez-Rodriguez JA & Ochoa G (2011) On the automatic discovery of variants of the NEH procedure for flow shop scheduling using genetic programming, Journal of the Operational Research Society, 62 (2), pp. 381-396.
Abstract: We use genetic programming to find variants of the well-known Nawaz, En-score and Ham (NEH) heuristic for the permutation flow shop problem. Each variant uses a different ranking function to prioritize operations during schedule construction. We have tested our ideas on problems where jobs have release times, due dates, and weights and have considered five objective functions: makespan, sum of tardiness, sum of weighted tardiness, sum of completion times and sum of weighted completion times. The implemented genetic programming system has been carefully tuned and used to generate one variant of NEH for each objective function. The new NEHs, obtained with genetic programming, have been compared with the original NEH and randomized NEH versions on a large set of benchmark problems. Our results indicate that the NEH variants discovered by genetic programming are superior to the original NEH and its stochastic version on most of the problems investigated.
Type: Journal Article
URI: http://hdl.handle.net/1893/19423
DOI Link: http://dx.doi.org/10.1057/jors.2010.132
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Affiliation: University of Nottingham
Computing Science - CSM Dept

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