Optimal feeder bus routes on irregular street networks

Steven Chien, Zhaowei Yang

Journal of Advanced Transportation · 2000 · 70 citations · 16 references

Concepts

TL;DR

Irregular, discrete demand distributions that reflect geographic variations are incorporated into the model. The study aims to optimize bus routes feeding a major intermodal transfer station while accounting for intersection delays and realistic street networks. A cost‑minimizing model locates optimal bus routes and headways in a heterogeneous service area, and computer programs analyze numerical examples to achieve global optimization. Analytical optimal headways for irregular, non‑uniform demand areas are validated by computer programs, and a near‑optimal algorithm attains comparable solutions to exhaustive search with markedly lower CPU time.

Abstract

Abstract The methodology presented here seeks to optimize bus routes feeding a major intermodal transit transfer station while considering intersection delays and realistic street networks. A model is developed for finding the optimal bus route location and its operating headway in a heterogeneous service area. The criterion for optimality is the minimum total cost, including supplier and user costs. Irregular and discrete demand distributions, which realistically represent geographic variations in demand, are considered in the proposed model. The optimal headway is derived analytically for an irregularly shaped service area without demand elasticity, with non‐uniformly distributed demand density, and with a many‐to‐one travel pattern. Computer programs are designed to analyze numerical examples, which show that the combinatory type routing problem can be globally optimized. The improved computational efficiency of the near‐optimal algorithm is demonstrated through numerical comparisons to an optimal solution obtained by the exhaustive search (ES) algorithm. The CPU time spent by each algorithm is also compared to demonstrate that the near‐optimal algorithm converges to an acceptable solution significantly faster than the ES algorithm.

References

16