creator Al Hassan, Reida advisor Shahidehpour, Mohammad This thesis proposes three different approaches for optimizing the travel time of cars in large networks. Genetic Algorithm with the integration of microscopic traffic simulation is employed to search for global solution for traffic signals settings. Shortest path algorithms are utilized to regulate the congestion level of the network. Large networks are partitioned into subnetworks to enable the optimization and simulation procedure. Several case studies are analyzed in this thesis to examine the efficiency of each approach and to observe the influence of different factors in the solution quality and computation time of the optimization process. Submitted by Erma Thomas (thomase@iit.edu) on 2016-03-31T20:21:25Z No. of bitstreams: 1 etdadmin_upload_395789.zip: 1332299 bytes, checksum: 4e75d671ba38e131d1cccb78309b0e73 (MD5) Made available in DSpace on 2016-03-31T20:21:25Z (GMT). No. of bitstreams: 1 etdadmin_upload_395789.zip: 1332299 bytes, checksum: 4e75d671ba38e131d1cccb78309b0e73 (MD5) Previous issue date: 2015-12 M.S. in Electrical Engineering, December 2015 2015 2015-12 http://hdl.handle.net/10560/3781 en microscopic traffic simulator Optimizing Traffic Shortest path Travel Time for Cars Thesis born digital application/pdf In Copyright http://rightsstatements.org/page/InC/1.0/ Restricted Access ECE / Electrical and Computer Engineering Illinois Institute of Technology Affiliated department