Schedule optimization under fuzzy constraints of vehicle capacity

Yanan Zhang (), Zhaopeng Meng (), Yan Zheng () and Anca Ralescu ()
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Yanan Zhang: Tianjin University
Zhaopeng Meng: Tianjin University
Yan Zheng: Tianjin University
Anca Ralescu: University of Cincinnati

Fuzzy Optimization and Decision Making, 2019, vol. 18, issue 2, No 1, 150 pages

Abstract: 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.

Keywords: Multi-criteria decision making; Fuzzy optimization; Integer programming; Timetable scheduling; Public transit optimization (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10700-018-9289-0

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