Real-time information plays an important role in travelers’ routing choices in an uncertain network by enabling online adaptation to revealed traffic conditions. The quality of the information affects its effectiveness. Usually there are some limitations in the information provided to the travelers, spatially, temporally or both. In this thesis, three variants of an optimal adaptive routing problem with partial online information problem are introduced: global information with time lag, global pre-trip information and radio information on a subset of links without time lag. A generic description of online information is provided. An algorithm is designed for the optimal routing problem in stochastic time-dependent networks with partial online information and specializations required for each of the three variants are given. A test example is conducted and computationally verifies the non-negative value of information. The work in this thesis is potentially of interest to traveler information systems evaluation and design.