Author/Authors :
Tavakkoli-Moghaddam Reza نويسنده , Asadi Hamed نويسنده Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. , Shahsavari Pour naja 1515@yahoo.com نويسنده Assistant Professor of Industrial Engineering at the University in Islamic Azad University
Abstract :
Trac jam is a daily problem in nearly all major cities in the world and
continues to increase with population and economic growth of urban areas. Trac lights,
as one of the key components at intersections, play an important role in control of trac
ow. Hence, study and research on phase synchronization and time optimization of the
trac lights could be an important step to avoid creating congestion and rejection queues
in a urban network. Here, we describe the application of NSGA-II, a multi-objective
evolutionary algorithm, to optimize both vehicle and pedestrian delays in an individual
intersection. In this paper, we improve NSGA-II algorithm based on the regression line
to nd a Pareto-optimal solution or a restrictive set of Pareto-optimal solutions based on
our solution approaches to the problem, named PDNSGA (Non-dominated Sorting Genetic
Algorithm based on Perpendicular Distance). The high speed of the proposed algorithm and
its quick convergence makes it desirable for large scheduling with a large number of phases.
It is demonstrated that our proposed algorithm (PDNSGA) gives better outputs than those
of MOGA, NSGA-II, and WBGA in trac signal optimization problem, statistically
