Model and algorithm for multi-follower tri-level hierarchical decision-making

Han, J; Zhang, G; Lu, J; Hu, Y; Ma, S

Model and algorithm for multi-follower tri-level hierarchical decision-making

Han, J Zhang, G

Lu, J

Hu, Y Ma, S

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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), 2014, 8836 pp. 398 - 406
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Han, J	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Hu, Y	en_US
dc.contributor.author	Ma, S	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, 8836 pp. 398 - 406	en_US
dc.identifier.isbn	9783319126425	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/35496
dc.identifier.uri	http://hdl.handle.net/10453/35486
dc.identifier.uri	http://hdl.handle.net/10453/35495
dc.description.abstract	© Springer International Publishing Switzerland 2014. Tri-level decision-making addresses compromises among interacting decision entities that are distributed throughout a three-level hierarchy. Decision entities at the three hierarchical levels are respectively termed as the toplevel leader, the middle-level follower and the bottom-level follower. When multiple followers are involved at the middle and bottom levels, the leader’s decision will be affected not only by reactions of the followers but also by various relationships among them. To support such a multi-follower tri-level (MFTL) decision-making process, this study first proposes a general MFTL decision model for the situation involving both cooperative and uncooperative relationships among multiple followers. It then develops a MFTL Kth-Best algorithm to find an optimal solution to the model. Lastly, we use the proposed MFTL decision techniques to deal with a supply chain management problem in applications.	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.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Model and algorithm for multi-follower tri-level hierarchical decision-making	en_US
dc.type	Conference Proceeding
utslib.citation.volume	8836	en_US
utslib.for	080105 Expert Systems	en_US
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
utslib.for	080605 Decision Support and Group Support Systems	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 Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	8836	en_US

Abstract:

© Springer International Publishing Switzerland 2014. Tri-level decision-making addresses compromises among interacting decision entities that are distributed throughout a three-level hierarchy. Decision entities at the three hierarchical levels are respectively termed as the toplevel leader, the middle-level follower and the bottom-level follower. When multiple followers are involved at the middle and bottom levels, the leader’s decision will be affected not only by reactions of the followers but also by various relationships among them. To support such a multi-follower tri-level (MFTL) decision-making process, this study first proposes a general MFTL decision model for the situation involving both cooperative and uncooperative relationships among multiple followers. It then develops a MFTL Kth-Best algorithm to find an optimal solution to the model. Lastly, we use the proposed MFTL decision techniques to deal with a supply chain management problem in applications.

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http://hdl.handle.net/10453/35486