Article
Pavement Maintenance Decision Making Based on
Optimization Models
Shitai Bao
1
, Keying Han
1
, Lan Zhang
2
, Xudong Luo
3
and Shunqing Chen
3,
*
Citation: Bao, S.; Han, K.; Zhang, L.;
Luo, X.; Chen, S. Pavement
Maintenance Decision Making Based
on Optimization Models. Appl. Sci.
2021, 11, 9706. https://doi.org/
10.3390/app11209706
Received: 9 September 2021
Accepted: 15 October 2021
Published: 18 October 2021
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1
College of Natural Resources and Environment, South China Agricultural University, 483 Wushan Road,
Guangzhou 510642, China; bst100@scau.edu.cn (S.B.); hankeying@stu.scau.edu.cn (K.H.)
2
School of Foreign Studies, South China Agricultural University, 483 Wushan Road, Guangzhou 510642, China;
zhanglan9416@stu.scau.edu.cn
3
Center of R&D, Augur Intelligent Technology Co., Ltd., 1029 Gaopu Road, Tianhe Dist.,
Guangzhou 510663, China; luoxd@augurit.com
* Correspondence: chensq@augurit.com; Tel.: +86-020-37020096; Fax: +86-020-37020432
Abstract:
Pavement maintenance prioritization considering both quality and cost is an important
decision-making problem. In this paper, the actual pavement condition index of city roads was
calculated using municipal patrol data. A linear optimization model that maximized maintenance
quality with limited maintenance costs and a multi-objective optimization model that maximized
maintenance quality while minimizing maintenance costs were developed based on the pavement
condition index. These models were subsequently employed in making decisions for actual pavement
maintenance using sequential quadratic programming and a genetic algorithm. The results showed
that the proposed decision-making models could effectively address actual pavement maintenance
issues. Additionally, the results of the single-objective linear optimization model verified that the
multiobjective optimization model was accurate. Thus, they could provide optimal pavement
maintenance schemes for roads according to actual pavement conditions. The reliability of the
models was investigated by analyzing their assumptions and validating their optimization results.
Furthermore, their applicability in pavement operation-related decision making and preventive
maintenance for roads of different grades was confirmed.
Keywords:
pavement maintenance and rehabilitation; decision optimization; pavement condition
index; linear optimization; genetic algorithm
1. Introduction
Continuous urbanization in China has significantly increased the cumulative mileage
of roads, which are considered the arteries of economic and social activities at the national
and local levels. As an essential component of road infrastructure, a pavement is a type of
hard surface made from durable surface material, which is able to withstand traffic and
harmful environments. Because of increasing traffic volumes with heavy loads and the
impacts of adverse environments, regular pavement maintenance is necessary to repair
damage and mitigate degradation. A sufficient budget should be allocated to maintain
the pavement at an appropriate condition, but insufficient budget is the primary obstacle
of pavement maintenance [
1
]. When conducting large-scale pavement maintenance, it
is important to consider the maintenance costs while ensuring that maintenance quality
meets the requisite standards. The selection of a proper pavement maintenance scheme
is a multiobjective optimization task. Therefore, determining the optimal maintenance
scheme is crucial for decision making in pavement maintenance [
2
,
3
]. Decision making
in pavement maintenance is a complicated, nondeterministic polynomial time (NP)-hard
problem [4].
Maintenance personnel generally make judgments based on their personal experience
when facing pavement maintenance tasks. Typical considerations include determination
Appl. Sci. 2021, 11, 9706. https://doi.org/10.3390/app11209706 https://www.mdpi.com/journal/applsci
