A hybrid discrete teaching-learning based meta-heuristic for solving no-idle flow shop scheduling problem with total tardiness criterion

A hybrid discrete teaching-learning based meta-heuristic for solving no-idle flow shop scheduling... •A discrete teaching phase based on probabilistic model is presented.•A discrete learning phase based on hierarchical structure is presented.•A reinforcement learning phase is added to improve the knowledge of teacher.•The parameters of the HDTLM are calibrated by a design of experiments.•The computational results on Taillard and Ruiz's benchmark set are carried out. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computers & Operations Research Elsevier

A hybrid discrete teaching-learning based meta-heuristic for solving no-idle flow shop scheduling problem with total tardiness criterion

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier Ltd
ISSN
0305-0548
eISSN
1873-765X
D.O.I.
10.1016/j.cor.2018.02.003
Publisher site
See Article on Publisher Site

Abstract

•A discrete teaching phase based on probabilistic model is presented.•A discrete learning phase based on hierarchical structure is presented.•A reinforcement learning phase is added to improve the knowledge of teacher.•The parameters of the HDTLM are calibrated by a design of experiments.•The computational results on Taillard and Ruiz's benchmark set are carried out.

Journal

Computers & Operations ResearchElsevier

Published: Jun 1, 2018

References

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