An improved exact ε-constraint and cut-and-solve combined method for biobjective robust lane reservation

Peng Wu, Ada Che, Feng Chu, Mengchu Zhou

Research output: Contribution to journalArticlepeer-review

42 Scopus citations

Abstract

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 \varepsilon-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.

Original languageEnglish (US)
Article number7008511
Pages (from-to)1479-1492
Number of pages14
JournalIEEE Transactions on Intelligent Transportation Systems
Volume16
Issue number3
DOIs
StatePublished - Jun 1 2015

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

Keywords

  • Biobjective mixed-integer linear program (BMILP)
  • cut-and-solve algorithm
  • exact \varepsilon-constraint method
  • lane reservation
  • optimization
  • robustness

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