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Schedule optimization under fuzzy constraints of vehicle capacity

Author

Listed:
  • Yanan Zhang

    (Tianjin University)

  • Zhaopeng Meng

    (Tianjin University)

  • Yan Zheng

    (Tianjin University)

  • Anca Ralescu

    (University of Cincinnati)

Abstract

The objective of designing timetables for public transportation is twofold: to ensure an efficient use of limited resources and to provide a comfortable ride for passengers. Two models for timetable optimization are investigated in this study. Model 1 uses a crisp constraint on the rate of vehicle capacity usage. Model 2 improves on model 1 by translating the crisp constraint into a fuzzy goal representing passenger satisfaction, and a fuzzy constraint, representing the extent of vehicle usage. Both, the fuzzy goal and the fuzzy constraint, are fuzzy sets on the number of on-board passengers. Heuristic methods together with linear programming are proposed for finding the optimal headway. Model 1 selects the largest time interval under the bound on vehicle size. The set of optimal time intervals in model 2 is decided by the simultaneous level cuts of the fuzzy goal and constraint. Experimental results show that fuzzy-set based model 2 is the most flexible and effective way to generate an optimal timetable.

Suggested Citation

  • Yanan Zhang & Zhaopeng Meng & Yan Zheng & Anca Ralescu, 2019. "Schedule optimization under fuzzy constraints of vehicle capacity," Fuzzy Optimization and Decision Making, Springer, vol. 18(2), pages 131-150, June.
    • Handle: RePEc:spr:fuzodm:v:18:y:2019:i:2:d:10.1007_s10700-018-9289-0
    DOI: 10.1007/s10700-018-9289-0
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    References listed on IDEAS

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