Reliability-Based Route Optimization of a Transportation Network with Random Arc Capacities and Time Threshold

摘要

The classical route optimization problem of a network focuses on the shortest or fastest route mainly under the assumption that all roads will not fail. In fact, the capacities of roads in a transportation network are not determinate but random because of the traffic accidents, maintenance or other activities. So a most reliable route from source to sink under the time threshold may be more important than the shortest or fastest route sometimes. This paper describes a stochastic Petri net-based simulation approach for reliability-based route optimization of a transportation network. The capacities of arcs may be in a stochastic state following any discrete or continuous distribution. The transmission time of each arc is also not a fixed number but stochastic according to its current capacity and demand. To solve this problem, a capacitated stochastic colored Petri net is used for modeling the system behavior. By the simulation, the optimal route with highest reliability can be obtained. Finally, an example of a transportation network with random arc capacities is given.