Optimization of university course scheduling problem with a hybrid artificial bee colony algorithm

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Date

2011

Authors

Adalet Oner
Sel Ozcan
Derya Dengi

Journal Title

Journal ISSN

Volume Title

Publisher

IEEE

Open Access Color

Green Open Access

Yes

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Publicly Funded

No
Impulse
Top 10%
Influence
Top 10%
Popularity
Average

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Journal Issue

Abstract

Course scheduling problem (CSP) is concerned with developing a timetable that illustrates a number of courses assigned to the classrooms. In this study a hybrid algorithm composed of a heuristic graph node coloring (GNC) algorithm and artificial bee colony (ABC) algorithm is proposed to solve CSP. The study is one of the few applications of ABC on discrete optimization problems and to our best knowledge it is the first application on CSP. A basic heuristic algorithm of node coloring problem takes part initially to develop some feasible solutions of CSP. Those feasible solutions correspond to the food sources in ABC algorithm. The ABC is then is used to improve the feasible solutions. The employed and onlooker bees are directed or controlled in a specific manner in order to avoid the conflicts in the course timetable. Proposed solution procedure is tested using real data from a university in Turkey. The experimental results demonstrate that the proposed hybrid algorithm yields efficient solutions. © 2011 IEEE. © 2011 Elsevier B.V. All rights reserved.

Description

Keywords

Artificial Bee Colony Algorithm, Course Scheduling Problem, Node Coloring, Artificial Bee Colonies, Course Scheduling, Discrete Optimization Problems, Feasible Solution, Food Sources, Hybrid Algorithms, Knowledge It, Node Coloring, Solution Procedure, University Course, Curricula, Heuristic Algorithms, Optimization, Scheduling Algorithms, Teaching, Evolutionary Algorithms, Artificial bee colonies, Course scheduling, Discrete optimization problems, Feasible solution, Food sources, Hybrid algorithms, Knowledge IT, Node coloring, Solution procedure, University course, Curricula, Heuristic algorithms, Optimization, Scheduling algorithms, Teaching, Evolutionary algorithms, Course Scheduling Problem, Node Coloring, Artificial Bee Colony Algorithm

Fields of Science

0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Citation

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OpenCitations Citation Count
11

Source

2011 IEEE Congress of Evolutionary Computation CEC 2011

Volume

Issue

Start Page

339

End Page

346
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Citations

CrossRef : 2

Scopus : 17

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Mendeley Readers : 45

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