Shortest path problem in stochastic graphs has been recently studied in the literature and a number of algorithms has been provided to find it using varieties of learning automata models. However, all these algorithms suffer from two common drawbacks: low speed and lack of a clear termination condition. In this paper, we propose a novel learning automata-based algorithm for this problem which c...

The shortest path problem is one of the most fundamental problems in network optimization. This paper is concerned with shortest path problems in non-deterministic environment, in which the lengths of some arcs have stochastic characteristics and meanwhile some have uncertain characteristics. In order to investigate paths in these networks, this paper introduces the chance distribution of minim...

Stochastic shortest path (SSP) problems arise in a variety of discrete stochastic control contexts. An optimal solutions to such a problem is typically computed using the value function, which can be found by solving the corresponding dynamic programming equations. In the deterministic case, these equations can be often solved by the highly efficient label-setting methods (such as Dijkstra’s an...

Stochastic shortest path (SSP) problems arise in a variety of discrete stochastic control contexts. An optimal solution to such a problem is typically computed using the value function, which can be found by solving the corresponding dynamic programming equations. In the deterministic case, these equations can be often solved by highly efficient label-setting methods (such as Dijkstra’s and Dia...

Stochastic shortest path (SSP) problems arise in a variety of discrete stochastic control contexts. An optimal solution to such a problem is typically computed using the value function, which can be found by solving the corresponding dynamic programming equations. In the deterministic case, these equations can be often solved by the highly efficient label-setting methods (such as Dijkstra’s and...

Finding optimal path in a given network is an important content of intelligent transportation information service. Static shortest path has been studied widely and many efficient searching methods have been developed, for example Dijkstra’s algorithm, Floyd-Warshall, Bellman-Ford, A et al. However, practical travel time is not a constant value but a stochastic value. How to take full use of the...

Stochastic shortest path (SSP) computations are often performed under very strict time constraints, so computational efficiency is critical. A major determinant for the CPU number of scenarios used. We demonstrate that by carefully picking right scenario generation method finding scenarios, quality can be improved substantially over random sampling a given scenarios. study extensive SSP instanc...