A Parallel Genetic Algorithms Optimization Approach to Calibrate Microsimulation Networks

A. Rachdi and B. Abdulhai (Canada)


Parallel Genetic Algorithms, Calibration and Trafficmodeling.


This paper introduces GENOSIM-p: a Generic traffic microsimulation parameter optimization tool using Parallel Genetic Algorithms (PGA), and its implementation to the St. Clair network in Downtown Toronto, Canada. GENOSIM-p is the parallel version of previous optimization software GENOSIM [1]. GENOSIM-p employs PGA to calibrate traffic microsimulation models. In this research, we will use PARAMICS: a microscopic traffic simulation platform. PARAMICS consists of high performance cross-linked traffic models having multiple user-adjustable parameters. GENOSIM-p will use PGA to manipulate those control parameters and search for an optimal set of values that minimize the discrepancy between simulation output and real field data.

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