Meta-heuristics for optimizing bi-objective heterogeneous urban traffic network

Meta heuristic algorithms are often used to solve scheduling problems. In this project we will use the meta heuristic algorithm to solve the scheduling problem of urban traffic signals. The project uses a macro model of the two mixed flow of pedestrian and vehicle to analyze the delay of pedestrians...

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Bibliographic Details
Main Author: Tang, Zhe
Other Authors: Su Rong
Format: Thesis
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10356/78666
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author Tang, Zhe
author2 Su Rong
author_facet Su Rong
Tang, Zhe
author_sort Tang, Zhe
collection NTU
description Meta heuristic algorithms are often used to solve scheduling problems. In this project we will use the meta heuristic algorithm to solve the scheduling problem of urban traffic signals. The project uses a macro model of the two mixed flow of pedestrian and vehicle to analyze the delay of pedestrians and vehicles in the traffic network. The objective is to reduce the overall waiting time for vehicles and pedestrians. And a search operator is used to improve the performance of the meta-heuristics. Performance evaluation includes waiting time and computing time. The parameters involved in the related algorithms will be enumerated. A detailed comparison process will also be given.
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spelling ntu-10356/786662023-07-04T16:22:55Z Meta-heuristics for optimizing bi-objective heterogeneous urban traffic network Tang, Zhe Su Rong School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Meta heuristic algorithms are often used to solve scheduling problems. In this project we will use the meta heuristic algorithm to solve the scheduling problem of urban traffic signals. The project uses a macro model of the two mixed flow of pedestrian and vehicle to analyze the delay of pedestrians and vehicles in the traffic network. The objective is to reduce the overall waiting time for vehicles and pedestrians. And a search operator is used to improve the performance of the meta-heuristics. Performance evaluation includes waiting time and computing time. The parameters involved in the related algorithms will be enumerated. A detailed comparison process will also be given. Master of Science (Computer Control and Automation) 2019-06-25T06:19:24Z 2019-06-25T06:19:24Z 2019 Thesis http://hdl.handle.net/10356/78666 en 67 p. application/pdf
spellingShingle Engineering::Electrical and electronic engineering
Tang, Zhe
Meta-heuristics for optimizing bi-objective heterogeneous urban traffic network
title Meta-heuristics for optimizing bi-objective heterogeneous urban traffic network
title_full Meta-heuristics for optimizing bi-objective heterogeneous urban traffic network
title_fullStr Meta-heuristics for optimizing bi-objective heterogeneous urban traffic network
title_full_unstemmed Meta-heuristics for optimizing bi-objective heterogeneous urban traffic network
title_short Meta-heuristics for optimizing bi-objective heterogeneous urban traffic network
title_sort meta heuristics for optimizing bi objective heterogeneous urban traffic network
topic Engineering::Electrical and electronic engineering
url http://hdl.handle.net/10356/78666
work_keys_str_mv AT tangzhe metaheuristicsforoptimizingbiobjectiveheterogeneousurbantrafficnetwork