Commuting with delay prone buses
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Neuro-Dynamic Programming
Path planning under time-dependent uncertainty
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Proceedings of the twenty-first annual symposium on Principles of distributed computing
Stochastic shortest paths via Quasi-convex maximization
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Probabilistic Analysis of Online Bin Coloring Algorithms Via Stochastic Comparison
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
ACE-INPUTS: A Cost-Effective Intelligent Public Transportation System
IEICE - Transactions on Information and Systems
Route planning under uncertainty: the Canadian traveller problem
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Reliability theory model and expected life shortest path in stochastic and time-dependent networks
ICCS'03 Proceedings of the 2003 international conference on Computational science
Ant colony optimization for stochastic shortest path problems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
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In the bus network problem, the goal is to generate a plan for getting from point X to point Y within a city using buses in the smallest expected time. Because bus arrival times are not determined by a fixed schedule but instead may be random, the problem requires more than standard shortest path techniques. In recent work, Datar and Ranade provide algorithms in the case where bus arrivals are assumed to be independent and exponentially distributed.We offer solutions to two important generalizations of the problem, answering open questions posed by Datar and Ranade. First, we provide a polynomial time algorithm for a much wider class of arrival distributions, namely those with increasing failure rate. This class includes not only exponential distributions but also uniform, normal, and gamma distributions. Second, in the case where bus arrival times are independent and geometric discrete random variables, we provide an algorithm for transportation networks of buses and trains, where trains run according to a fixed schedule.