Tri-level multi-follower decision-making in a partial-cooperative situation

Han, J; Wan, S; Lu, J; Zhang, G

Tri-level multi-follower decision-making in a partial-cooperative situation

Han, J Wan, S Lu, J

Zhang, G

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2017 12th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2017, 2017, 2018-January pp. 1 - 6
Issue Date:: 2017-07-01

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Field	Value	Language
dc.contributor.author	Han, J	en_US
dc.contributor.author	Wan, S	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.date.issued	2017-07-01	en_US
dc.identifier.citation	Proceedings of the 2017 12th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2017, 2017, 2018-January pp. 1 - 6	en_US
dc.identifier.isbn	9781538618295	en_US
dc.identifier.uri	http://hdl.handle.net/10453/125768
dc.description.abstract	© 2017 IEEE. Tri-level decision-making addresses compromises between interactive decision entities that are distributed throughout a three-level hierarchy. These decision entities are respectively termed as the top-level leader, the middle-level follower and the bottom-level follower. This paper considers a tri-level multi-follower (TLMF) decision problem where both cooperative and uncooperative relationships coexist between multiple followers at the same level. In this situation, followers share some decision variables with their counterparts and also control individual decision variables to achieve their respective goals; this is also known as partial-cooperative TLMF decision-making. To support this category of decision-making, this paper first presents a linear model to characterize the partial-cooperative TLMF decision-making process. It then develops a vertex enumeration algorithm to obtain a solution to the resulting model. Lastly, we apply the proposed TLMF decision techniques to handle an inventory management problem in applications.	en_US
dc.relation.ispartof	Proceedings of the 2017 12th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2017	en_US
dc.relation.isbasedon	10.1109/ISKE.2017.8258802	en_US
dc.title	Tri-level multi-follower decision-making in a partial-cooperative situation	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2018-January	en_US
utslib.for	080105 Expert 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	2018-January	en_US

Abstract:

© 2017 IEEE. Tri-level decision-making addresses compromises between interactive decision entities that are distributed throughout a three-level hierarchy. These decision entities are respectively termed as the top-level leader, the middle-level follower and the bottom-level follower. This paper considers a tri-level multi-follower (TLMF) decision problem where both cooperative and uncooperative relationships coexist between multiple followers at the same level. In this situation, followers share some decision variables with their counterparts and also control individual decision variables to achieve their respective goals; this is also known as partial-cooperative TLMF decision-making. To support this category of decision-making, this paper first presents a linear model to characterize the partial-cooperative TLMF decision-making process. It then develops a vertex enumeration algorithm to obtain a solution to the resulting model. Lastly, we apply the proposed TLMF decision techniques to handle an inventory management problem in applications.

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http://hdl.handle.net/10453/125768