  The weighted sum method is a simple and widely used technique that scalarizes
multiple conflicting objectives into a single objective function. It suffers
from the problem of determining the appropriate weights corresponding to the
objectives. This paper proposes a novel Hierarchical Bayesian model based on
Multinomial distribution and Dirichlet prior to refine the weights for solving
such multi-objective route optimization problems. The model and methodologies
revolve around data obtained from a small scale pilot survey. The method aims
at improving the existing methods of weight determination in the field of
Intelligent Transport Systems as data driven choice of weights through
appropriate probabilistic modelling ensures, on an average, much reliable
results than non-probabilistic techniques. Application of this model and
methodologies to simulated as well as real data sets revealed quite encouraging
performances with respect to stabilizing the estimates of weights.
