Title :
Sparsely synchronized parallel genetic algorithm for road traffic network division
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of West Bohemia, Plzen, Czech Republic
Abstract :
In this paper, we explore the features of the sparsely synchronized parallel genetic algorithm for the road traffic network division. The algorithm is an alternative to a commonly used island model for the parallelization of the genetic algorithms. The algorithm employs the parallelization of particular phases of the genetic algorithm (fitness values calculation, crossover, etc.). However, the threads of the genetic algorithm are not synchronized in every generation, but rather only once per several generations or even not at all. The lack of the synchronization leads to the inconsistencies in the shared memory, which does not have to be a problem considering the stochastic nature of the genetic algorithms. The investigation of the features and usability of the sparse synchronization of the parallel genetic algorithm (with application for the road traffic network division) is the main theme of this paper.
Keywords :
genetic algorithms; parallel algorithms; road traffic; shared memory systems; stochastic processes; island model; road traffic network division; shared memory; sparse synchronization; sparsely synchronized parallel genetic algorithm; stochastic nature; Computational modeling; Computers; Genetic algorithms; Instruction sets; Roads; Sociology; Synchronization; inconsistency; parallel genetic algorithm; sparse synchronization; traffic network division;
Conference_Titel :
Human System Interactions (HSI), 2015 8th International Conference on
Conference_Location :
Warsaw
DOI :
10.1109/HSI.2015.7170655