An extended bilevel programming model and its kth-best algorithm for dynamic decision making in emergency situations

Zhou, H; Lu, J; Zhang, G

An extended bilevel programming model and its kth-best algorithm for dynamic decision making in emergency situations

Zhou, H Lu, J

Zhang, G

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Publication Type:: Conference Proceeding
Citation:: IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - MCDM 2014: 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, Proceedings, 2015, pp. 100 - 105
Issue Date:: 2015-01-12

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Field	Value	Language
dc.contributor.author	Zhou, H	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	2015-01-12	en_US
dc.identifier.citation	IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - MCDM 2014: 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, Proceedings, 2015, pp. 100 - 105	en_US
dc.identifier.isbn	9781479944682	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121392
dc.description.abstract	© 2014 IEEE. Linear bilevel programming has been studied for many years and applied in different domains such as transportation, economics, engineering, environment, and telecommunications. However, there is lack of attention of the impacts on dynamic decision making with abrupt or unusual events caused by unpredictable natural environment or human activities (e.g. Tsunami, earthquake, and malicious or terrorist attacks). In reality these events could happens more often and have more significant impacts on decision making in an increasingly complex and dynamic world. This paper addresses this unique problem by introducing a concept of Virtual Follower (VF). An extended model of bilevel multi-follower programming with a virtual follower (BLMFP-VF) is defined and the kth-best algorithm for solving this problem is proposed. An example is given to illustrate the working of the extended model and approach.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0557154
dc.relation.ispartof	IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - MCDM 2014: 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, Proceedings	en_US
dc.relation.isbasedon	10.1109/MCDM.2014.7007194	en_US
dc.title	An extended bilevel programming model and its kth-best algorithm for dynamic decision making in emergency situations	en_US
dc.type	Conference Proceeding
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

Abstract:

© 2014 IEEE. Linear bilevel programming has been studied for many years and applied in different domains such as transportation, economics, engineering, environment, and telecommunications. However, there is lack of attention of the impacts on dynamic decision making with abrupt or unusual events caused by unpredictable natural environment or human activities (e.g. Tsunami, earthquake, and malicious or terrorist attacks). In reality these events could happens more often and have more significant impacts on decision making in an increasingly complex and dynamic world. This paper addresses this unique problem by introducing a concept of Virtual Follower (VF). An extended model of bilevel multi-follower programming with a virtual follower (BLMFP-VF) is defined and the kth-best algorithm for solving this problem is proposed. An example is given to illustrate the working of the extended model and approach.

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http://hdl.handle.net/10453/121392