A Multi­ Objective Optimization via Simulation framework for restructuring traffic networks subject to increases in population

Abstract

Traffic network design is a complex problem due to its nonlinear and stochastic nature. The Origin-Destiny Traffic Assignment Problem is particular case of this problem. In it, we are faced with an increase in the system vehicle population; and, we want to determine where to set the generating nodes and the traffic consumers, minimizing the current system and trying to reduce necessary investment. Performing optimizations in an analytical way in this kind of problems tends to be really complicated and a bit impractical, since it is difficult to estimate vehicle flows. In this chapter, we propose the use of a Multi-Objective Particle Swamp Optimization together with Traffic Simulations in order to generate restructuring alternatives that optimize both, traffic flow and cost associated to this restructure. This approach allows to obtain a very good approximation of the Pareto Frontier of the problem, with a fast convergence to the low infrastructure cost solutions and a total coverage of the frontier when the number of iterations is high.