Travel times in urban transport are often subject to stochastic variations due to random fluctuations in travel demands, frequent interruptions of traffic controls, and unpredictable occurrences of traffic incidents. A chance constrained model with capacity and time window was provided, and a heuristic-based genetic algorithm to solve the problem was introduced. The experiments demonstrated that performance of the algorithm was efficient, especially in clustered data sets.
展开▼
