Feasibility study of optimization of a genetic algorithm for traffic network division for distributed road traffic simulation

Abstract

This paper deals with optimization of a genetic algorithm for road traffic network division for distributed road traffic simulation, which we developed. Two approaches for finding of optimal setting of the genetic algorithm are considered -an optimizing genetic algorithm and a systematic testing of possible settings. Since both approaches are expected to be extremely computation-consuming, their distributed versions are proposed and a feasibility study is evaluated.

Harnessing Mother Nature: Optimizing Genetic Algorithms for Adaptive Systems

“…The authors in [2] investigate a genetic algorithm optimization system similar to ours, with a focus on road traffic optimization. Although their system encodes similar parameters, their method of optimization differs greatly, as it is optimizing the final fitness of the genetic algorithm, not the efficiency and time of the genetic algorithm.…”

Urban travel demand estimation using genetic algorithm

“…He discussed an attribute reduction algorithm based on RS theory combined with a genetic algorithm to optimize a decision table relating reasons and type of road congestion. Interestingly, Tomas Potuzak [13] described a feasibility study of a genetic algorithm for optimization of parameters of another genetic algorithm for road traffic network division. He used the distributed computing approach for the optimization of the genetic algorithm parameters.…”