Dynamic Fuzzy Logic-Ant Colony System-Based Route Selection System
Route selection in metropolises based on specific desires is a major problem for city travelers as well as a challenging demand of car navigation systems. This paper introduces a multiparameter route selection system which employs fuzzy logic (FL) for local pheromone updating of an ant colony system...
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Series: | Applied Computational Intelligence and Soft Computing |
Online Access: | http://dx.doi.org/10.1155/2010/428270 |
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doaj-cbb37e1d82ef430dbf30942df8f5ec412020-11-24T22:55:18ZengHindawi LimitedApplied Computational Intelligence and Soft Computing1687-97241687-97322010-01-01201010.1155/2010/428270428270Dynamic Fuzzy Logic-Ant Colony System-Based Route Selection SystemHojjat Salehinejad0Siamak Talebi1Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman 76169-133, IranDepartment of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman 76169-133, IranRoute selection in metropolises based on specific desires is a major problem for city travelers as well as a challenging demand of car navigation systems. This paper introduces a multiparameter route selection system which employs fuzzy logic (FL) for local pheromone updating of an ant colony system (ACS) in detection of optimum multiparameter direction between two desired points, origin and destination (O/D). The importance rates of parameters such as path length and traffic are adjustable by the user. In this system, online traffic data are supplied directly by a traffic control center (TCC) and further minutes traffic data are predicted by employing artificial neural networks (ANNs). The proposed system is simulated on a region of London, United Kingdom, and the results are evaluated.http://dx.doi.org/10.1155/2010/428270 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hojjat Salehinejad Siamak Talebi |
spellingShingle |
Hojjat Salehinejad Siamak Talebi Dynamic Fuzzy Logic-Ant Colony System-Based Route Selection System Applied Computational Intelligence and Soft Computing |
author_facet |
Hojjat Salehinejad Siamak Talebi |
author_sort |
Hojjat Salehinejad |
title |
Dynamic Fuzzy Logic-Ant Colony System-Based Route Selection System |
title_short |
Dynamic Fuzzy Logic-Ant Colony System-Based Route Selection System |
title_full |
Dynamic Fuzzy Logic-Ant Colony System-Based Route Selection System |
title_fullStr |
Dynamic Fuzzy Logic-Ant Colony System-Based Route Selection System |
title_full_unstemmed |
Dynamic Fuzzy Logic-Ant Colony System-Based Route Selection System |
title_sort |
dynamic fuzzy logic-ant colony system-based route selection system |
publisher |
Hindawi Limited |
series |
Applied Computational Intelligence and Soft Computing |
issn |
1687-9724 1687-9732 |
publishDate |
2010-01-01 |
description |
Route selection in metropolises based on specific desires is a major problem for city travelers as well as a challenging demand of car navigation systems. This paper introduces a multiparameter route selection system which employs fuzzy logic (FL) for local pheromone updating of an ant colony system (ACS) in detection of optimum multiparameter direction between two desired points, origin and destination (O/D). The importance rates of parameters such as path length and traffic are adjustable by the user. In this system, online traffic data are supplied directly by a traffic control center (TCC) and further minutes traffic data are predicted by employing artificial neural networks (ANNs). The proposed system is simulated on a region of London, United Kingdom, and the results are evaluated. |
url |
http://dx.doi.org/10.1155/2010/428270 |
work_keys_str_mv |
AT hojjatsalehinejad dynamicfuzzylogicantcolonysystembasedrouteselectionsystem AT siamaktalebi dynamicfuzzylogicantcolonysystembasedrouteselectionsystem |
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1725657081858490368 |