Bus Scheduling with Trip Coordination and Complex Constraints

  • Raymond S. K. Kwan
  • Mohammad A. Rahin
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 430)


At the stage of compiling bus schedules, schedulers usually can still manoeuvre the trip timings to a certain extent. Sometimes, even options in the route structures might still be open. Most schedulers, especially in the highly competitive U.K. bus industry, would strive to explore many possibilities in order to derive the best schedules in terms of efficiency, competitiveness, quality of service to the public, and operational objectives. This paper reports on recent researches in producing complementary modules to the well-established bus scheduling system BUSPLAN to meet the schedulers / planners’ growing needs. These include interactive and semiautomatic tools for co-ordinating trip timings, and heuristics for handling multivehicle-type constraints.

Earlier work on the co-ordination of trip timings had already been reported in the Fourth Workshop in Hamburg. Recent research has extended this to cover full-day operations rather than just over periods of steady state operations. This encompasses smooth transitions between steady state periods and less regular services at the beginning and end of day. Dead running between terminals also becomes an important consideration.

Since deregulation in 1986, there is a resurgence in multi-vehicle-type constraints in the U.K. bus industry. These constraints are sometimes complicated by the use of more than one depot. VAMPIRES, which was developed in the 1970s and whose algorithm now forms the basis of BUSPLAN, included heuristics for these problems. This paper describes recent improvement updates to these heuristics. Research in improving the VAMPIRES algorithm through object-oriented modelling is also outlined.


Vehicle Type Target Number Joint Headway Schedule Linkage Interactive Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Raymond S. K. Kwan
    • 1
  • Mohammad A. Rahin
    • 1
  1. 1.School of Computer StudiesUniversity of LeedsLeedsUK

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