This paper presents a review of emerging techniques for enhancing the practical application of city logistics models.
A number of models have been applied to practical problems for evaluating policy measures of city logistics. These
models can be categorised into two types: optimisation models, and simulation models. Optimisation models
incorporate dynamic and stochastic elements, since the real urban freight transport faces varying demands and travel
times. Simulation models typically use multi-agent systems, as multiple stakeholders are involved in planning city
logistics schemes. Evaluation methodology is directly related to decision making of policy measures. Models for
supporting decision making have become more important for obtaining a social acceptance as well as governance
among private and public entities