Latest revision as of 02:26, 23 March 2021

Abstract

Pavement maintenance is essential to prevent the deterioration of asset value and to satisfy the expectations of all stakeholders (objectives). However, the budgets are often insufficient to keep the road pavement at optimum levels. Therefore, a decision making process ought to be used for prioritizing different maintenance activities in order to achieve pre-defined goals by optimizing the use of the available budget. One of the biggest difficulties in multiobjective optimization method is the large number of the feasible solutions (Pareto optimal set or its approximation), which makes it hard for the Decision Maker to select the best solution.

To support interaction with the decision maker for identifying the best combination of maintenance actions, this paper proposes a new methodology named “Interactive Multiobjective Optimization-Dominance Rough Set Approach” (IMO-DRSA), using a decision-rule preference model.

The preference information, obtained by the Decision Maker (DM) during the course of the interaction, is processed using the Dominance-based Rough Set Approach in order to achieve a decision model expressed in terms of easily understandable “if ….then …” decision rules. This approach makes possible an interaction between the analyst and the decision maker and helps the decision maker to classify maintenance options and allocate limited funds according to predefined objectives (quantitative or qualitative). An application of the proposed methodology to road pavements of an Italian urban sub-network is presented.

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The different versions of the original document can be found in:

• http://dx.doi.org/10.1186/s12544-019-0353-9 under the license https://creativecommons.org/licenses/by/4.0

• http://hdl.handle.net/20.500.11769/361567 under the license https://creativecommons.org/licenses/by/4.0

• https://etrr.springeropen.com/track/pdf/10.1186/s12544-019-0353-9

• http://link.springer.com/article/10.1186/s12544-019-0353-9,

https://doaj.org/toc/1867-0717,

https://doaj.org/toc/1866-8887 under the license cc-by

• http://link.springer.com/content/pdf/10.1186/s12544-019-0353-9.pdf,

http://link.springer.com/article/10.1186/s12544-019-0353-9/fulltext.html,

http://dx.doi.org/10.1186/s12544-019-0353-9

• https://etrr.springeropen.com/track/pdf/10.1186/s12544-019-0353-9,

https://link.springer.com/content/pdf/10.1186/s12544-019-0353-9.pdf,

https://link.springer.com/article/10.1186/s12544-019-0353-9,

https://etrr.springeropen.com/articles/10.1186/s12544-019-0353-9,

https://researchportal.port.ac.uk/portal/files/13402319/Augeri2019_Article_PlanningUrbanPavementMaintenan.pdf,

https://researchportal.port.ac.uk/portal/en/publications/planning-urban-pavement-maintenance-by-a-new-interactive-multiobjective-optimization-approach(c9a8ca66-b9c5-48f2-ab71-acce84aa9d2b).html,

https://academic.microsoft.com/#/detail/2922673383 under the license https://creativecommons.org/licenses/by/4.0

• https://researchportal.port.ac.uk/portal/en/publications/planning-urban-pavement-maintenance-by-a-new-interactive-multiobjective-optimization-approach(c9a8ca66-b9c5-48f2-ab71-acce84aa9d2b).html,

https://doi.org/10.1186/s12544-019-0353-9,

https://researchportal.port.ac.uk/ws/files/13402319/Augeri2019_Article_PlanningUrbanPavementMaintenan.pdf,

https://etrr.springeropen.com/articles/10.1186/s12544-019-0353-9