GENETIC ALGORITHMS IN BUS NETWORK OPTIMIZATION
planning - methods, land use - planning, ridership - commuting, economics - appraisal/evaluation, mode - bus
Optimization, Optimisation, Network analysis (Planning), Multiple criteria decision making, Multicriteria evaluation, Iterative methods, Iterations, Intracity bus transportation, Heuristic methods, Genetic algorithms, Bus transit
A heuristic approach can be used to solve transportation bus network optimization problems. This paper proposes a new method to compute fitness function (ff) values in genetic algorithms. In this method, a genetic algorithm is used to generate iteratively new populations. New bus networks are generated from an initial set of bus networks in order to improve the performance of the old ones and reduce the number of vehicles employed in the network without increasing the average traveling time. Each member of the population is evaluated by computing a number of performance indicators obtained by the analysis of the assignment of the O/D demand associated to the considered networks. In this method, ff values are computed by means of a multicriteria analysis executed on the found performance indicators. This heuristic aims to achieve the best bus network that will satisfy both the demand and offer of transport.
BIELLI, M, Caramia, M, Carotenuto, P, (2002). GENETIC ALGORITHMS IN BUS NETWORK OPTIMIZATION. Transportation Research Part C: Emerging Technologies, Volume 10, Issue 1, p. 19-34.
Transportation Research Part C Home Page: http://www.sciencedirect.com/science/journal/0968090X