A Sparse Optimization Approach for Energy-Efficient Timetabling in Metro Railway Systems

In this paper, the authors propose a sparse optimization approach to maximize the utilization of regenerative energy produced by braking trains for energy-efficient timetabling in metro railway systems. By introducing the cardinality function and the square of the Euclidean norm function as the objective function, the resulting sparse optimization model can characterize the utilization of the regenerative energy appropriately. A two-stage alternating direction method of multipliers is designed to efficiently solve the convex relaxation counterpart of the original NP-hard problem and then to produce an energy-efficient timetable of trains. The resulting approach is applied to Beijing Metro Yizhuang Line with different instances of service for case study. Comparison with the existing two-step linear program approach is also conducted which illustrates the effectiveness of the proposed sparse optimization model in terms of the energy saving rate and the efficiency of the numerical optimization algorithm in terms of computational time.

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  • English

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  • Accession Number: 01687293
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Nov 7 2018 2:43PM