期刊
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
卷 30, 期 3, 页码 -出版社
ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)CP.1943-5487.0000503
关键词
Transportation network reconstruction; Post-disaster recovery; Multi-objective optimization; Mixed-integer linear programming; Computational cost; Traffic analysis; Contractors assignment; Search space
资金
- Royalty Research Fund Award of the University of Washington
Catastrophes, such as hurricanes, earthquakes, and tsunamis often cause large-scale damage to transportation systems. In the aftermath of these disasters, there is a present challenge to quickly analyze various reconstruction plans and assess their impacts on restoring transportation services. This paper presents a new methodology for optimizing post-disaster reconstruction plans for transportation networks with superior computational efficiency employing mixed-integer linear programming (MILP). The model is capable of optimizing transportation recovery projects prioritization and contractors assignment in order to simultaneously: (1)accelerate networks recovery; and (2)minimize public expenditures. The full methodology is presented in two companion publications, where the focus of this paper is to propose new methods for (1)decomposing traffic analysis; (2)assessing the traffic and cost performance of reconstruction plans; (3)reducing the massive solution search space; and (4)phasing the use of mixed-integer linear programming to optimize the problem. An illustrative example is presented throughout the paper to demonstrate the implementation phases. (C) 2015 American Society of Civil Engineers.
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