Application of a Metamodel-Based Optimization Approach for Toll Optimization and its comparison with Metaheuristics-based Model Optimization via a Case Study.

Abstract

First, a concept of metamodel-based optimization, in which a transport economics inspired model acts as a metamodel over an underlying set-up of directly interfaced transport models, is discussed. Then, a toll optimization scenario including a city and its neighboring rural municipalities is developed and a case study concerning its cooperative version is presented. The metamodel for this case study involves the player(s) optimizing their objective based on a schematic network, and simplified cost and demand functions, whereas the underlying set-up is a Static Traffic Assignment over the physical network with physical origin-destination elastic demand. This new metamodel-based optimization is then compared with traditional metaheuristics-based optimization. Results show that the new approach not only leads to lower computational expense but even outperforms metaheuristics-based optimization in terms of optimality.