Improved Lagrangian relaxation based optimization procedure for scheduling with storage

Gu, H; Memar, J; Zinder, Y

Improved Lagrangian relaxation based optimization procedure for scheduling with storage

Gu, H

Memar, J

Zinder, Y

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Publication Type:: Conference Proceeding
Citation:: IFAC-PapersOnLine, 2019, 52 (13), pp. 100 - 105
Issue Date:: 2019-09-01

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Field	Value	Language
dc.contributor.author	Gu, H https://orcid.org/0000-0003-2035-2583	en_US
dc.contributor.author	Memar, J https://orcid.org/0000-0003-2395-1450	en_US
dc.contributor.author	Zinder, Y https://orcid.org/0000-0003-2024-8129	en_US
dc.date.accessioned	2020-04-07T07:24:09Z
dc.date.available	2020-04-07T07:24:09Z
dc.date.issued	2019-09-01	en_US
dc.identifier.citation	IFAC-PapersOnLine, 2019, 52 (13), pp. 100 - 105	en_US
dc.identifier.uri	http://hdl.handle.net/10453/139869
dc.description.abstract	© 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. The paper considers the two-stage hybrid flow shop scheduling problem, where the second-stage machines process jobs in predefined batches and the processing of each batch requires a batch-dependent portion of limited storage space. This portion of the storage is seized by a batch from the start of the processing of the jobs, constituting the batch, on the first stage, till the batch has been completed on the second stage. The objective is the total weighted tardiness of the batches with respect to the given due dates. This scheduling problem arises in manufacturing, supply chains of mineral resources and computer systems. One of the approaches to this NP-hard in the strong sense problem is Lagrangian relaxation. The paper presents modifications that allow to significantly improve the performance in comparison with a straightforward Lagrangian relaxation. The effectiveness of the proposed modifications is justified by the results of computational experiments.	en_US
dc.relation.ispartof	IFAC-PapersOnLine	en_US
dc.relation.isbasedon	10.1016/j.ifacol.2019.11.159	en_US
dc.title	Improved Lagrangian relaxation based optimization procedure for scheduling with storage	en_US
dc.type	Conference Proceeding
utslib.citation.volume	13	en_US
utslib.citation.volume	52	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.issue	13	en_US
pubs.publication-status	Published	en_US
pubs.volume	52	en_US

Abstract:

© 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. The paper considers the two-stage hybrid flow shop scheduling problem, where the second-stage machines process jobs in predefined batches and the processing of each batch requires a batch-dependent portion of limited storage space. This portion of the storage is seized by a batch from the start of the processing of the jobs, constituting the batch, on the first stage, till the batch has been completed on the second stage. The objective is the total weighted tardiness of the batches with respect to the given due dates. This scheduling problem arises in manufacturing, supply chains of mineral resources and computer systems. One of the approaches to this NP-hard in the strong sense problem is Lagrangian relaxation. The paper presents modifications that allow to significantly improve the performance in comparison with a straightforward Lagrangian relaxation. The effectiveness of the proposed modifications is justified by the results of computational experiments.

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http://hdl.handle.net/10453/139869