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A Multiobjective Optimization Method for Integrated Road Asset Management Considering Traffic Dynamics

delete2026-01-01
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PRE
AI
S
Siyuan Meng
柏
柏强 (Qiang Bai) *
DOI:10.1177/03611981261441294delete
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Abstract

Abstract

En 中文
Traditional road asset management often operates in isolation, leading to suboptimal coordination. While integrated asset management enables multiasset maintenance and rehabilitation (M&R) decisions on a unified platform, existing approaches typically do not systematically account for traffic redistribution effects. This study proposes a road M&R planning method based on bilevel multiobjective optimization (MOO) that explicitly integrates user and environmental considerations with economic and performance objectives. The upper level optimizes network-level multiyear agency cost, network condition, user cost, and greenhouse gas (GHG) emissions. The lower level employs a traffic assignment model to address traffic dynamics caused by reduced link capacity during M&R operations. The bilevel MOO model is solved using the Nondominated Sorting Genetic Algorithm III and Self-Regulated Method of Successful Averages to generate Pareto solutions, with an analytic hierarchy process-based weighted-sum method determining the final solution. A five-year case study on a road network in Liaoning Province, China, demonstrates the method's effectiveness for pavement and bridge M&R planning: 19.11% improvement in network condition, 9.07% reduction in GHG emissions, and 4.64% reduction in user costs, proving the method's effectiveness for achieving cost-effective and sustainable M&R decisions. Comparative analysis against a static traffic baseline reveals that explicitly modeling traffic redistribution reduces user costs by 99.39% and GHG emissions by 61.17%, demonstrating traffic dynamics alter optimal M&R decisions. The methodology is validated for a regional network with asphalt pavements, reinforced concrete T-beam bridges, and passenger vehicle traffic under deterministic demand; extensions to heterogeneous vehicle types, elastic demand, and other infrastructures represent directions for future studies.
Keywords:
maintenance and rehabilitation
integrated asset management
multiobjective optimization
traffic dynamics
sustainability

Journal

T
Transportation Research Record
IF:
1.8
Papers:
876
Citations:
3.4W

Organization

C
Chang'an University
Scholars:
4.1K
Papers: 1.5K
Citations: 1.3W
U
university of massachusetts amherst
Scholars:
838
Papers: 448
Citations: 0
Cited Papers

Cited Papers

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Pavement asset management systems and technologies: A review
err2020-11-01
err106
PREAI
errPeraka, Naga Siva Pavani; Biligiri, Krishna Prapoorna
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