Abstract
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.
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Zhang, T., Guo, B., Tan, Y. (2011). Reliability-Based Route Optimization of a Transportation Network with Random Arc Capacities and Time Threshold. In: Tang, Y., Huynh, VN., Lawry, J. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2011. Lecture Notes in Computer Science(), vol 7027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24918-1_17
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DOI: https://doi.org/10.1007/978-3-642-24918-1_17
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