Abstract
A city's transportation infrastructure deeply affects its citizens' quality of life-from the freshness of food to the amount of frustration felt while commuting to work. Providing an optimal infrastructure has the possibility of dramatically improving the population's well-being. Since the transportation infrastructure is a system-of-systems (SoS) [1], it may be modelled and optimized for a given set of objectives [2]. In this manner, the city resources can be optimized for multiple objectives such as commute time, overall throughput, and sustainability. This is made possible by using a fuzzy assessor to map the individual objectives into a single overall fitness value that is optimized by a genetic algorithm (GA). The value of the individual objectives is determined by the selected systems which are each characterized by a set of characteristics (cost, CO2 emissions, etc.), capabilities, and interfaces.
Recommended Citation
R. Alaguvelu et al., "Fuzzy-Genetic Algorithm Approach to Generate an Optimal Meta-Architecture for a Smart, Safe & Efficient City Transportation System of Systems," 2016 11th Systems of Systems Engineering Conference, SoSE 2016, article no. 7542935, Institute of Electrical and Electronics Engineers, Aug 2016.
The definitive version is available at https://doi.org/10.1109/SYSOSE.2016.7542935
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
FILA-SoS; fuzzy assessor; GA; genetic algorithm; SoS; system-of-systems
International Standard Book Number (ISBN)
978-146738727-9
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
12 Aug 2016
