Pavement maintenance and rehabilitation planning optimisation under budget and pavement deterioration uncertainty

Fani, A; Golroo, A; Ali Mirhassani, S; Gandomi, AH

Pavement maintenance and rehabilitation planning optimisation under budget and pavement deterioration uncertainty

Fani, A Golroo, A Ali Mirhassani, S Gandomi, AH

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Publisher:: Routledge
Publication Type:: Journal Article
Citation:: The International Journal of Pavement Engineering, 2022, 23, (2), pp. 414-424
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Fani, A
dc.contributor.author	Golroo, A
dc.contributor.author	Ali Mirhassani, S
dc.contributor.author	Gandomi, AH
dc.date.accessioned	2023-03-27T04:51:26Z
dc.date.available	2023-03-27T04:51:26Z
dc.date.issued	2022-01-01
dc.identifier.citation	The International Journal of Pavement Engineering, 2022, 23, (2), pp. 414-424
dc.identifier.issn	1029-8436
dc.identifier.issn	1477-268X
dc.identifier.uri	http://hdl.handle.net/10453/168583
dc.description.abstract	© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. One of the key parts of a pavement management system is the maintenance and rehabilitation planning. The planning is usually developed under the assumption that all parameters are known with certainty. In practice, there are various parameters afflicted with large uncertainty. Ignoring the uncertainty may lead to a suboptimal plan adversely affecting the network conditions. The objective of this study is to develop an optimisation framework for network-level pavement maintenance and rehabilitation planning considering the uncertain nature of pavement deterioration and the budget with an applicable approach. A multistage stochastic mixed-integer programming model is proposed to find the optimal plan that is feasible for all possible scenarios of uncertainty and optimise the expectation of objective function. Two case studies of 4 and 21 pavement sections are presented to show the applicability of the proposed method. The value of stochastic solution and the expected value of perfect information which are the indices for evaluating the benefits of using the stochastic model are, respectively, 30% and 85% of the objective function of here and now model for the first case study and 26% and 42% of it regarding the second one. The indices are high indicating the effectiveness of the stochastic solution.
dc.language	English
dc.publisher	Routledge
dc.relation.ispartof	The International Journal of Pavement Engineering
dc.relation.isbasedon	10.1080/10298436.2020.1748628
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Pavement Engineering on 2022-01-28, available online: https://www.tandfonline.com/10.1080/10298436.2020.1748628.
dc.subject	0905 Civil Engineering
dc.subject.classification	Logistics & Transportation
dc.title	Pavement maintenance and rehabilitation planning optimisation under budget and pavement deterioration uncertainty
dc.type	Journal Article
utslib.citation.volume	23
utslib.for	0905 Civil Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2023-03-27T04:51:25Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	23
utslib.citation.issue	2

Abstract:

© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. One of the key parts of a pavement management system is the maintenance and rehabilitation planning. The planning is usually developed under the assumption that all parameters are known with certainty. In practice, there are various parameters afflicted with large uncertainty. Ignoring the uncertainty may lead to a suboptimal plan adversely affecting the network conditions. The objective of this study is to develop an optimisation framework for network-level pavement maintenance and rehabilitation planning considering the uncertain nature of pavement deterioration and the budget with an applicable approach. A multistage stochastic mixed-integer programming model is proposed to find the optimal plan that is feasible for all possible scenarios of uncertainty and optimise the expectation of objective function. Two case studies of 4 and 21 pavement sections are presented to show the applicability of the proposed method. The value of stochastic solution and the expected value of perfect information which are the indices for evaluating the benefits of using the stochastic model are, respectively, 30% and 85% of the objective function of here and now model for the first case study and 26% and 42% of it regarding the second one. The indices are high indicating the effectiveness of the stochastic solution.

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http://hdl.handle.net/10453/168583