Analysis of energy consumption reduction in metro systems using rollingstop-skipping patterns

S. Yang, Jianjun Wu (Corresponding author), Xin Yang, F. Liao, Daqing Li, Yun Wei

Research output: Contribution to journalArticleAcademicpeer-review

32 Citations (Scopus)
16 Downloads (Pure)


Energy-efficient operations optimization has attracted much attention recently to reduce the energy consumption and the associated costs of metro systems. Compared with all-stop patterns, stop-skipping patterns potentially lead to decreasing energy consumption and increasing train loading utilization. This paper develops an optimization-based approach to design energy-efficient metro timetables and speed profiles with a stop-skipping pattern based on passenger smart-card data. First, we develop an algorithm to generate: a set of likely to be skipped stations is identified according to historical travel records, and a heuristic rule is adopted to select the specific skipped station. Second, we reformulate the energy-efficient timetabling optimization problem as a convex quadratic programming problem and develop a solution algorithm to determine the optimized timetables and speed profiles. A numerical example is conducted using the real-world passenger data and the train operational data of a metro line in Beijing. The results show that the developed approach reduces energy consumption by 15.39% and increases the loading volume per train by 3.56 person/min in comparison with the current timetable.
Original languageEnglish
Pages (from-to)129-142
Number of pages14
JournalComputers & Industrial Engineering
Publication statusPublished - 1 Jan 2019


  • Energy consumption
  • Quadratic programming
  • Stop-skipping pattern
  • Timetable optimization


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