Study of Bus Stop Skipping Scheme Based on Modified Cellular Genetic Algorithm

Abstract

A bus may skip one or more stops to reduce its travel time with a proper stop-skipping scheme when it is behind schedule. A nonlinear 0-1 stochastic programming model was developed with the objective of minimizing additional passenger delay incurred by buses running late. The delay includes the additional time spent in two successive buses as well as additional waiting time at bus stops. In order to solve this nonlinear problem, a modified cellular genetic algorithm (CGA) method was proposed. A numerical case study was conducted to examine the performance of the proposed methodology. By skipping at some stops, the additional passenger delay decreases 10.23%, with a 21.98% reduction for the first bus. In addition, the first bus arrives at the terminal 4.1 minutes earlier than without skipping. Also, it was found that the proposed algorithm had fast searching speed and good global search ability.

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