A Routing Strategy with Multi-Attributes in Stochastic and Time-Dependent Transportation Networks

A stochastic, time-dependent (STD) network is the network in which the arc weights are random variables with the probability distribution function changing over time. If there is more than one attribute of concern in selecting an optimal path, then the networks are called multi-attribute stochastic, time-dependent (MSTD) networks. Based on the multi-attribute decision making about information entropy, an exact algorithm is proposed for obtaining synthetic optimal hyperpaths from all nodes to a specified destination in MSTD networks. Synthetic optimal hyperpaths consist of a set of path strategies that enable the traveler to select a direction to his destination at each node in response to knowledge of the arrival time. In the end, an illustrative example is given to clarify the algorithm.