Open AccessGenetic algorithms approach to the problem of the automated vehicle identification equipment locations
Author(s) -
Teodorovic Dusan,
van Aerde Michel,
Zhu Fulin,
Dion Francois
Publication year - 2002
Publication title -
journal of advanced transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.577
H-Index - 46
eISSN - 2042-3195
pISSN - 0197-6729
DOI - 10.1002/atr.5670360102
Subject(s) - simulated annealing , identification (biology) , metaheuristic , genetic algorithm , computer science , algorithm , mathematical optimization , data mining , machine learning , mathematics , botany , biology
The automated vehicle identification (AVI) equipment location problem entails determination of the best locations for the automated vehicle identification equipment. The paper attempts to solve the AVI equipment location problem as a multi‐objective optimization problem, thus determining the best locations on the basis of several criteria. The developed model is based on genetic algorithms. Testing of the model developed on the greater transportation networks is certainly one of the most important directions for the future research, as much as the development of models based on other metaheuristic approaches (Simulated Annealing, Taboo Search). The results obtained in this stage of the research are promising.