A lagrangian relaxation based forward-backward improvement heuristic for maximising the net present value of resource-constrained projects

Gu, H; Schutt, A; Stuckey, PJ

A lagrangian relaxation based forward-backward improvement heuristic for maximising the net present value of resource-constrained projects

Gu, H

Schutt, A Stuckey, PJ

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, 7874 LNCS pp. 340 - 346
Issue Date:: 2013-12-01

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Field	Value	Language
dc.contributor.author	Gu, H https://orcid.org/0000-0003-2035-2583	en_US
dc.contributor.author	Schutt, A	en_US
dc.contributor.author	Stuckey, PJ	en_US
dc.date.issued	2013-12-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, 7874 LNCS pp. 340 - 346	en_US
dc.identifier.isbn	9783642381706	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/31143
dc.description.abstract	In this paper we propose a forward-backward improvement heuristic for the variant of resource-constrained project scheduling problem aiming to maximise the net present value of a project. It relies on the Lagrangian relaxation method to generate an initial set of schedules which are then improved by the iterative forward/backward scheduling technique. It greatly improves the performance of the Lagrangian relaxation based heuristics in the literature and is a strong competitor to the best meta-heuristics. We also embed this heuristic into a state-of-the-art CP solver. Experimentation carried out on a comprehensive set of test data indicates we compare favorably with the state of the art. © Springer-Verlag 2013.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-642-38171-3_24	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A lagrangian relaxation based forward-backward improvement heuristic for maximising the net present value of resource-constrained projects	en_US
dc.type	Conference Proceeding
utslib.citation.volume	7874 LNCS	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
dc.location.activity	Yorktown Heights, NY
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.publication-status	Published	en_US
pubs.volume	7874 LNCS	en_US

Abstract:

In this paper we propose a forward-backward improvement heuristic for the variant of resource-constrained project scheduling problem aiming to maximise the net present value of a project. It relies on the Lagrangian relaxation method to generate an initial set of schedules which are then improved by the iterative forward/backward scheduling technique. It greatly improves the performance of the Lagrangian relaxation based heuristics in the literature and is a strong competitor to the best meta-heuristics. We also embed this heuristic into a state-of-the-art CP solver. Experimentation carried out on a comprehensive set of test data indicates we compare favorably with the state of the art. © Springer-Verlag 2013.

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http://hdl.handle.net/10453/31143