Solving Curriculum-Based Course Timetabling Problem with Artificial Bee Colony Algorithm

2011 ◽  
Author(s):  
Danang Junaedi ◽  
Nur Ulfa Maulidevi
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Course Timetabling ◽  
Timetabling Problem ◽  
Bee Colony ◽  
Course Timetabling Problem

A Modified Artificial Bee Colony Algorithm for Post-enrolment Course Timetabling

2013 ◽  
pp. 377-386 ◽  
Author(s):  
Asaju La’aro Bolaji ◽  
Ahamad Tajudin Khader ◽  
Mohammed Azmi Al-Betar ◽  
Mohammed A. Awadallah
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Course Timetabling ◽  
Bee Colony

scholarly journals School Timetabling Optimisation Using Artificial Bee Colony Algorithm Based on a Virtual Searching Space Method

Mathematics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 73
Author(s):  
Kaixiang Zhu ◽  
Lily D. Li ◽  
Michael Li
Keyword(s):  
Artificial Bee Colony ◽  
Search Space ◽  
Course Timetabling ◽  
Timetabling Problem ◽  
Bee Colony ◽  
Educational Timetabling ◽  
Proposed Model ◽  
School Timetabling ◽  
School Timetabling Problem ◽  
World School

Although educational timetabling problems have been studied for decades, one instance of this, the school timetabling problem (STP), has not developed as quickly as examination timetabling and course timetabling problems due to its diversity and complexity. In addition, most STP research has only focused on the educators’ availabilities when studying the educator aspect, and the educators’ preferences and expertise have not been taken into consideration. To fill in this gap, this paper proposes a conceptual model for the school timetabling problem considering educators’ availabilities, preferences and expertise as a whole. Based on a common real-world school timetabling scenario, the artificial bee colony (ABC) algorithm is adapted to this study, as research shows its applicability in solving examination and course timetabling problems. A virtual search space for dealing with the large search space is introduced to the proposed model. The proposed approach is simulated with a large, randomly generated dataset. The experimental results demonstrate that the proposed approach is able to solve the STP and handle a large dataset in an ordinary computing hardware environment, which significantly reduces computational costs. Compared to the traditional constraint programming method, the proposed approach is more effective and can provide more satisfactory solutions by considering educators’ availabilities, preferences, and expertise levels.

Artificial Bee Colony Algorithm for Solving Educational Timetabling Problems

2012 ◽  
Vol 3 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Asaju La’aro Bolaji ◽  
Ahamad Tajudin Khader ◽  
Mohammed Azmi Al-Betar ◽  
Mohammed A. Awadallah
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Solution Method ◽  
Search Space ◽  
Initial Population ◽  
Timetabling Problem ◽  
Bee Colony ◽  
Educational Timetabling ◽  
Problem Instances ◽  
Uncapacitated Examination Timetabling Problem

This paper presents an artificial bee colony algorithm (ABC) for Education Timetabling Problem (ETP). It is aimed at developing a good-quality solution for the problem. The initial population of solutions was generated using Saturation Degree (SD) and Backtracking Algorithm (BA) to ensure the feasibility of the solutions. At the improvement stage in the solution method, ABC uses neighbourhood structures iteratively within the employed and onlooker bee operators, in order to rigorously navigate the UTP search space. The technique was evaluated using curriculum-based course timetabling (CB-CTT) and Uncapacitated Examination Timetabling Problem (UETP) problem instances. The experimental results on UETP showed that the technique is comparable with other state-of-the-art techniques and provides encouraging results on CB-CTT.

Path Planning of Mobile Robot Using Improved Artificial Bee Colony Algorithm

2020 ◽  
Vol 38 (9A) ◽  
pp. 1384-1395
Author(s):  
Rakaa T. Kamil ◽  
Mohamed J. Mohamed ◽  
Bashra K. Oleiwi
Keyword(s):  
Mobile Robot ◽  
Comparative Research ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Dynamic Control ◽  
Computational Time ◽  
Bee Colony ◽  
Shortest Distance ◽  
Minimum Number ◽  
Cubic Polynomial

A modified version of the artificial Bee Colony Algorithm (ABC) was suggested namely Adaptive Dimension Limit- Artificial Bee Colony Algorithm (ADL-ABC). To determine the optimum global path for mobile robot that satisfies the chosen criteria for shortest distance and collision–free with circular shaped static obstacles on robot environment. The cubic polynomial connects the start point to the end point through three via points used, so the generated paths are smooth and achievable by the robot. Two case studies (or scenarios) are presented in this task and comparative research (or study) is adopted between two algorithm’s results in order to evaluate the performance of the suggested algorithm. The results of the simulation showed that modified parameter (dynamic control limit) is avoiding static number of limit which excludes unnecessary Iteration, so it can find solution with minimum number of iterations and less computational time. From tables of result if there is an equal distance along the path such as in case A (14.490, 14.459) unit, there will be a reduction in time approximately to halve at percentage 5%.

Artificial bee colony algorithm with modified search strategy

2013 ◽  
Vol 32 (12) ◽  
pp. 3326-3330
Author(s):  
Yin-xue ZHANG ◽  
Xue-min TIAN ◽  
Yu-ping CAO
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Search Strategy ◽  
Bee Colony
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