This paper focuses on a new method to compute fitness function (ff) values in genetic algorithms for bus network optimization. In the proposed methodology, a genetic algorithm is used to generate iteratively new populations (sets of bus networks). 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. Thus, ff values are computed by means of a multicriteria analysis executed on the performance indicators so found. The goal is to design a heuristic algorithm that allows to achieve the best bus network satisfying both the transport demand and supply.

An integrated software tool environment is presented, and a methodology is proposed for the operational support of the local authority, for analysis of the impact of transport measures in terms of network energy consumption and pollutant emissions. It is based on work done by the European Union within the save program (speci®c actions for vigorous energy eciency)ÐSlam project (supporting local authorities methodology). As background, the Slam project is described, with the principal aspects and needs of environmental and trac network management. The central section de®nes a methodology able to support technicians in recognizing the trac asset and decision makers in evaluating interventions on urban transport infrastructures or technological systems. The role of the di€erent models and their interactions with the transport telematics services currently active on the Florence (Italy) network is discussed. Finally, the procedure for calculating the trac impacts on energy consumption is described with the help of a test case, the evaluation of a dedicated bus corridor in Florence. # 1999 Published by Elsevier Science Ltd. All rights reserved.