dc.contributor.advisor |
Henning, T |
en |
dc.contributor.advisor |
Raith, A |
en |
dc.contributor.advisor |
Shamseldin, A |
en |
dc.contributor.author |
Chen, Lin |
en |
dc.date.accessioned |
2016-04-27T21:06:28Z |
en |
dc.date.issued |
2016 |
en |
dc.identifier.citation |
2016 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/28674 |
en |
dc.description.abstract |
This thesis attempts to improve decision making in Infrastructure Asset Management (IAM) by introducing Multi-Objective Optimisation (MOO) and developing a robust MOO technique for long-term and network-level decision making in IAM. IAM is the backbone of modern societies and has a great impact on the economy, society, environment and culture. Decision making as an essential part of IAM helps to achieve the goals and requirements of IAM by providing appropriate management strategies. Complex in its nature, decision making has a wide range of difficulties. Hence, MOO, as a type of decision making methods, is increasingly applied to assist decision making in IAM. This research aims at a robust MOO technique that can be easily applied to different decision making problems, achieve good optimisation results, and therefore help decision makers to easily and accurately select appropriate management strategies for their long-term and network-level decision making in IAM. This research is conducted based on a comprehensive review of the applications of optimisation in decision making in IAM. Then it further discusses a variety of MOO techniques and their performance when dealing with practical decision making in IAM. Finally, based on the discussion of the existing MOO techniques, a new MOO technique is developed for long-term and network-level decision making; and a communication tool is also proposed to present the optimisation result. According to this research, it finds that MOO can deal with the difficulties of practical decision making in IAM and provide objective optimisation results that greatly help to trade off decision making outcomes, clarify decision making problems and simplify decision making process. However, this research points out that a robust MOO technique that can satisfy all the requirements of practical long-term and network-level decision making in IAM was not found. Therefore, a robust MOO technique named Dynamic Epsilon Constraint Method (DECM) is developed in this regard, which performs better than the other studied techniques, satisfies all the decision making requirements and can be applied to answer different questions of IAM. Also, a communication tool is proposed, which interprets optimisation results and enables exploring the management preferences and refining the results. |
en |
dc.publisher |
ResearchSpace@Auckland |
en |
dc.relation.ispartof |
PhD Thesis - University of Auckland |
en |
dc.relation.isreferencedby |
UoA99264849304002091 |
en |
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.rights.uri |
http://creativecommons.org/licenses/by-nc-sa/3.0/nz/ |
en |
dc.title |
Development of a Multi-Objective Optimisation Technique for Long-Term and Network-Level Decision Making in Infrastructure Asset Management |
en |
dc.type |
Thesis |
en |
thesis.degree.discipline |
Civil and Environmental Engineering |
en |
thesis.degree.grantor |
The University of Auckland |
en |
thesis.degree.level |
Doctoral |
en |
thesis.degree.name |
PhD |
en |
dc.rights.holder |
Copyright: The Author |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.elements-id |
526905 |
en |
pubs.record-created-at-source-date |
2016-04-28 |
en |
dc.identifier.wikidata |
Q112930827 |
|