Journal
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Volume 16, Issue 3, Pages 1479-1492Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2014.2368594
Keywords
Biobjective mixed-integer linear program (BMILP); cut-and-solve algorithm; exact epsilon-constraint method; lane reservation; optimization; robustness
Categories
Funding
- French Ministries of Foreign and European Affairs [27927VE]
- Higher Education and Research [27927VE]
- Chinese Ministry of Education [27927VE]
- program of 100 Foreign Experts in Anhui Province
- program of Chair professor of Huangshan Scholars at Hefei University of Technology
- National Science Foundation [CMMI-1162482]
- National Natural Science Foundation of China [71071129, 71471145]
- Humanities, Social Sciences and Management Innovation Foundation of Northwestern Polytechnical University [RW201301]
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This study investigates a new biobjective lane-reservation problem, which is to exclusively reserve lanes from an existing transportation network for special transport tasks with given deadlines. The objectives are to minimize the total negative impact on normal traffic due to the reduction of available lanes for general-purpose vehicles and to maximize the robustness of the lane-reservation solution against the uncertainty in link travel times. We first define the robustness for the lane-reservation problem and formulate a biobjective mixed-integer linear program. Then, we develop an improved exact epsilon-constraint and a cut-and-solve combined method to generate its Pareto front. Computational results for an instance based on a real network topology and 220 randomly generated instances with up to 150 nodes, 600 arcs, and 50 tasks demonstrate that the proposed method is able to find the Pareto front and that the proposed cut-and-solve method is more efficient than the direct use of optimization software CPLEX.
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