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Signal Setting Design at a Single Junction Through the Application of Genetic Algorithms

  • Giulio Erberto Cantarella
  • Stefano de Luca
  • Roberta Di Pace
  • Silvio Memoli
Chapter
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 262)

Abstract

The purpose of this chapter is the application of Genetic Algorithms to solve the Signal Setting Design at a single junction. Two methods are compared: the monocriteria and the multicriteria optimisations. In the former case, three different objectives functions were considered: the capacity factor maximisation, the total delay minimisation and the total number of stops minimisation; in the latter case, two combinations of criteria were investigated: the total delay minimisation and the capacity factor maximisation, the total delay minimisation and the total number of stops minimisation. Furthermore, two multicriteria genetic algorithms were compared: the Goldberg’s Pareto Ranking (GPR) and the Non Dominated Sorting Genetic Algorithms (NSGA-II). Conclusions discuss the effectiveness of multicriteria optimisation with respect to monocriteria optimisation, and the effectiveness of NSGA-II with respect to the GPR.

Keywords

Signal setting Optimisation modelling Genetic algorithms Metaheuristics Single junction 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Giulio Erberto Cantarella
    • 1
  • Stefano de Luca
    • 1
  • Roberta Di Pace
    • 1
  • Silvio Memoli
    • 1
  1. 1.Department of Civil EngineeringUniversity of SalernoFiscianoItaly

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