A Multi-objective Evolutionary scheme for Control Points deployment in Intelligent Transportation Systems

Martin Luther Mfenjou, Ado Adamou Abba Ari, Arouna Ndam Njoya, Kolyang Dina Taiwe, Wahabou Abdou, Abdelhak Mourad Gueroui


One of the problems that hinder emergency in developing countries is the problem of monitoring activities through inter-urban roadway networks. In the literature, the use of control points is proposed in the context of these countries in order to ensure efficient monitoring, by ensuring a good coverage while minimizing the installation costs as well as the number of accidents across these road networks. In this work, we propose an optimal deployment of these control points from several optimization methods based on some evolutionary multi-objective algorithms including the Non dominated Sorting Genetic Algorithm-II (NSGA-II), the Multi-Objective Particle Swarm Optimization (MOPSO), the Strength Pareto Evolutionary Algorithm -II (SPEA-II), and the Pareto Envelope based Selection Algorithm-II (PESA-II). We performed the tests and compared these deployments using Pareto front and performance indicators like the Inverted Generational Distance (IGD), Spread and Hypervolume. The results obtained show that the NSGA-II method is the most suitable for the deployment of these control points.


Intelligent Transportation System; Multi-objective; Evolutionary Algorithms; Roadway Network; Deployment; Performance Evaluation; Control Points


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