We present a new multi-path routing methodology, MLBrouting, that is based on the multinomial logit model, which is well known in the random utility field. The key concept of the study is to set multiple paths from the origin to the destination, and distribute packets in accordance with multinomial logit type probability. Since MLB-routing is pure multi-path routing, it reduces the convergence ...

Recently, the Markov chain choice model has been introduced by Blanchet et al. to overcome the computational intractability for learning and revenue management for several modern choice models, including the mixed multinomial logit models. However, the known methods for learning the Markov models require almost all items to be offered in the learning stage, which is impractical. To address this...

In statistics, a multinomial logit (MNL) model, also known as multinomial logistic regression, is a regression model which generalizes logistic regression by allowing more than two discrete outcomes.[1] That is, it is a model that is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable, given a set of independent variables (which...