The best route in a given situation can vary when traffic conditions vary and updates should be notified to the user in real-time. Even though adapted to the real-time case, Dijkstra-like algorithms consider only one solution at a time and do not deal with the entire route until the end. In consequence, route evaluation is slow; furthermore, the same alternative to many users. These considerations suggest that the parallel analysis of many solutions could improve the overall performance of the system. Bibliography and experimental results suggest that routing systyems could benefit from the use of genetic algorithms instead of traditional search methods.

Genetic Algorithms in Real-Time Route Planning

C De Castro
2010

Abstract

The best route in a given situation can vary when traffic conditions vary and updates should be notified to the user in real-time. Even though adapted to the real-time case, Dijkstra-like algorithms consider only one solution at a time and do not deal with the entire route until the end. In consequence, route evaluation is slow; furthermore, the same alternative to many users. These considerations suggest that the parallel analysis of many solutions could improve the overall performance of the system. Bibliography and experimental results suggest that routing systyems could benefit from the use of genetic algorithms instead of traditional search methods.
2010
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
real-time
best route
genetic algorithms
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/231193
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact