Optimizing road networks in underdeveloped regions for improving comprehensive efficiency integrated by accessibility, vulnerability and socioeconomic interaction
Huiying Wen,
Yichen Ye and
Lin Zhang
Reliability Engineering and System Safety, 2024, vol. 243, issue C
Abstract:
Previous studies on performance assessment and optimization of road networks (RNs) have focused on either normal performance related to accessibility or extreme performance related to vulnerability. However, these two aspects are rarely considered together, and the impact of socioeconomic interaction has not been addressed. Therefore, the RN may be unable to adapt to the construction of future resilient infrastructure, leading to unstable and inefficient operations. Besides, the neglect of the role and development of RNs in underdeveloped regions can lead to unbalanced regional development. This study develops an optimization model of RNs in underdeveloped regions for comprehensive efficiency to solve the regional coordinated development problem. Specifically, a quantitative assessment method of the comprehensive efficiency integrating accessibility, vulnerability, and socioeconomic interaction is proposed to measure the performance. Then, a two-stage bi-level programming model for underdeveloped regions focusing on optimizing comprehensive efficiency is proposed. Finally, a case is studied to verify the model's effectiveness and enlighten the assessment and planning of RNs. Results show that compared with the original RN regarding invulnerability, reachable time, and socioeconomic interaction, optimization results of Stage 1 are optimized by 14.81Â %, 31.62Â %, and 0.03Â %, respectively, and Stage 2 are optimized by 44.64Â %, 42.87Â %, and 57.71Â %, respectively.
Keywords: Comprehensive efficiency; Vulnerability; Bi-level programming model; Road network; Regional coordinated development (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:243:y:2024:i:c:s0951832023007627
DOI: 10.1016/j.ress.2023.109848
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