An investigation of multi-objective particle swarm optimization algorithm for better performance and its application to signalized traffic problem

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Record Details

Record ID: stcompfyp:13
Title: An investigation of multi-objective particle swarm optimization algorithm for better performance and its application to signalized traffic problem
Type of Work: Final Year Project/Work
Collection: S&T Best Computing Projects
Contributor: Yuen, Man Chung (creator)
Ng, Sin Chun Vanessa 吳倩珍 (supervisor)
School / Unit: School of Science and Technology (S&T)
Program: Bachelor of Computing with Honours in Internet Technology
Date: 2020
Abstract: In this project, we are going to study and improve the state-of-the-art MOPSO algorithms. The proposed algorithm was based on the competitive mechanism MOPSO that guides the particles by the current population. We aim to achieve better performance that balances between exploration and exploitation of the whole swarm, avoid premature convergence, and maintain a well-distributed Pareto front. The proposed algorithm was applied to the signalized traffic problem to optimize the effective green time of each phase in real-world problems.
Type of Resource: Mixed
Language: English
Physical Description: This work includes 1 PDF file and 1 video clip.
Keywords: traffic congestion; traffic signs and signals; swarm intelligence; computational intelligence; mathematical optimization; multiple criteria decision making
Access Eligibility: Public Access
Permanent Link: https://repository.lib.hkmu.edu.hk/sw/islandora/object/stcompfyp:13

Object Details

Record ID: stcompfyp:15
Title: An investigation of multi-objective particle swarm optimization algorithm for better performance and its application to signalized traffic problem - video
Collection: S&T Best Computing Projects
Type of Resource: Video
Physical Description: 3 minutes 54 seconds.
Access Eligibility: Public Access
Permanent Link: https://repository.lib.hkmu.edu.hk/sw/islandora/object/stcompfyp:15