A Course Scheduling Algorithm Based on Self-Adaptive Constrained Particle Swarm*

The automatic course scheduling in college is a complex constraint optimization problem. A kind of self-adaptive constraint particle swarm algorithm is proposed to avoid premature convergence of particle swarm optimization algorithm. A self-adaptive criterion is applied in different phases of algori...

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Main Authors: Cui Wei, Long Xiaohong
Format: Article
Language:English
Published: EDP Sciences 2016-01-01
Series:MATEC Web of Conferences
Online Access:http://dx.doi.org/10.1051/matecconf/20166102006
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author Cui Wei
Long Xiaohong
author_facet Cui Wei
Long Xiaohong
author_sort Cui Wei
collection DOAJ
description The automatic course scheduling in college is a complex constraint optimization problem. A kind of self-adaptive constraint particle swarm algorithm is proposed to avoid premature convergence of particle swarm optimization algorithm. A self-adaptive criterion is applied in different phases of algorithm execution to realize dynamic and adaptive switch between attractors and repellors during the algorithm’s running process, and inertia weight will change dynamically and adaptively with the number of iterations. The algorithm performance can be further improved with a higher convergence speed and stronger robustness.
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spelling doaj.art-7a63b56d11fc4690912fc90013af76df2022-12-21T22:21:29ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01610200610.1051/matecconf/20166102006matecconf_apop2016_02006A Course Scheduling Algorithm Based on Self-Adaptive Constrained Particle Swarm*Cui Wei0Long Xiaohong1Luzhou Vocational & Technical CollegeLuzhou Vocational & Technical CollegeThe automatic course scheduling in college is a complex constraint optimization problem. A kind of self-adaptive constraint particle swarm algorithm is proposed to avoid premature convergence of particle swarm optimization algorithm. A self-adaptive criterion is applied in different phases of algorithm execution to realize dynamic and adaptive switch between attractors and repellors during the algorithm’s running process, and inertia weight will change dynamically and adaptively with the number of iterations. The algorithm performance can be further improved with a higher convergence speed and stronger robustness.http://dx.doi.org/10.1051/matecconf/20166102006
spellingShingle Cui Wei
Long Xiaohong
A Course Scheduling Algorithm Based on Self-Adaptive Constrained Particle Swarm*
MATEC Web of Conferences
title A Course Scheduling Algorithm Based on Self-Adaptive Constrained Particle Swarm*
title_full A Course Scheduling Algorithm Based on Self-Adaptive Constrained Particle Swarm*
title_fullStr A Course Scheduling Algorithm Based on Self-Adaptive Constrained Particle Swarm*
title_full_unstemmed A Course Scheduling Algorithm Based on Self-Adaptive Constrained Particle Swarm*
title_short A Course Scheduling Algorithm Based on Self-Adaptive Constrained Particle Swarm*
title_sort course scheduling algorithm based on self adaptive constrained particle swarm
url http://dx.doi.org/10.1051/matecconf/20166102006
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