## A Hybrid Evolutionary Approach to the University Course Timetabling Problem

Citations: | 8 - 1 self |

### BibTeX

@MISC{Abdullah_ahybrid,

author = {Salwani Abdullah and Edmund K. Burke and Barry Mccollum},

title = {A Hybrid Evolutionary Approach to the University Course Timetabling Problem},

year = {}

}

### OpenURL

### Abstract

Abstract—Combinations of evolutionary based approaches with local search have provided very good results for a variety of scheduling problems. This paper describes the development of such an algorithm for university course timetabling. This problem is concerned with the assignment of lectures to specific timeslots and rooms. For a solution to be feasible, a number of hard constraints must be satisfied. The quality of the solution is measured in terms of a penalty value which represents the degree to which various soft constraints are satisfied. This hybrid evolutionary approach is tested over established datasets and compared against state-of-the-art techniques from the literature. The results obtained confirm that the approach is able to produce solutions to the course timetabling problem which exhibit some of the lowest penalty values in the literature on these benchmark problems. It is therefore concluded that the hybrid evolutionary approach represents a particularly effective methodology for producing high quality solutions to the university course timetabling problem.

### Citations

121 | A tabu search hyperheuristic for timetabling and rostering
- Burke, Kendall, et al.
- 2003
(Show Context)
Citation Context ...en a lot of attention paid to the problem of automating the construction of university timetables. Various techniques have been applied including simulated annealing (e.g. [1,2,3]), tabu search (e.g. =-=[4]-=-) and genetic algorithms (e.g. [5]). A successful approach to many scheduling and timetabling problems (e.g. [6,7]) is represented by the combination of evolutionary based approaches with local search... |

85 | A Memetic Algorithm for University Exam Timetabling
- Burke, Newall, et al.
- 1996
(Show Context)
Citation Context ...iques have been applied including simulated annealing (e.g. [1,2,3]), tabu search (e.g. [4]) and genetic algorithms (e.g. [5]). A successful approach to many scheduling and timetabling problems (e.g. =-=[6,7]-=-) is represented by the combination of evolutionary based approaches with local search (sometimes called a memetic algorithm). The paper is organised as follows: The next section describes the course ... |

80 | A Multi-Stage Evolutionary Algorithm for the Timetabling Problem
- Burke, Newall
- 1999
(Show Context)
Citation Context ...ames in the literature such as memetic algorithms, hybrid genetic algorithms and genetic local search algorithms [18]. Examples of similar approaches applied to university timetabling can be found in =-=[6,7,19]-=-. The method described in [6] employed a memetic algorithm for university examination timetabling where two evolutionary operators are used (light and heavy mutation) in the initial phase followed by ... |

76 | A tutorial for competent memetic algorithms: Model, taxonomy, and design issues
- Krasnogor, Smith
- 2005
(Show Context)
Citation Context ...s show that this methodology was able to improve the solution quality and reduce the time taken to find that solution. Interested readers can find more details about hybrid evolutionary approaches in =-=[18,20]-=-. An overview of memetic algorithms for scheduling and timetabling problems can be seen in [21]. IV. A HYBRID EVOLUTIONARY ALGORITHM FOR THE UNIVERSITY COURSE TIMETABLING PROBLEM The main technique us... |

66 | A Time-Predefined Local Search Approach to Exam Timetabling Problems
- Burke, Bykov, et al.
- 2004
(Show Context)
Citation Context ...ing literature, there has been a lot of attention paid to the problem of automating the construction of university timetables. Various techniques have been applied including simulated annealing (e.g. =-=[1,2,3]-=-), tabu search (e.g. [4]) and genetic algorithms (e.g. [5]). A successful approach to many scheduling and timetabling problems (e.g. [6,7]) is represented by the combination of evolutionary based appr... |

46 | A graph-based hyperheuristic for educational timetabling problems
- Burke, Mccollum, et al.
(Show Context)
Citation Context ...nd applied it to university course timetabling in addition to nurse rostering. The focus of the paper was on robustness across different problems rather than specifically on timetabling. Burke et al. =-=[16]-=- also employed tabu search within a graph based hyper-heuristic and applied it to both examination and course timetabling benchmark datasets. Again, the aim was to raise the level of generality by ope... |

42 | A Hybrid Genetic Algorithm for Highly Constrained Timetabling
- Burke, Elliman, et al.
- 1995
(Show Context)
Citation Context ...e presented in Figs. 4 and 5. Recall that our evolutionary method does not use a crossover operator. Such operators can create extra difficulties (such as having to “repair” offspring) in timetabling =-=[6,24,25]-=-. Combined, these figures represent the approach used in our experiments. The algorithm begins by creating an initial population of size 100. The process creates subsequent generations by firstly sele... |

40 |
A robust simulated annealing based examination timetabling system
- Thompson, Dowsland
- 1998
(Show Context)
Citation Context ...ing literature, there has been a lot of attention paid to the problem of automating the construction of university timetables. Various techniques have been applied including simulated annealing (e.g. =-=[1,2,3]-=-), tabu search (e.g. [4]) and genetic algorithms (e.g. [5]). A successful approach to many scheduling and timetabling problems (e.g. [6,7]) is represented by the combination of evolutionary based appr... |

36 | A monte carlo hyper-heuristic to optimise component placement sequencing for multi head placement machine
- Ayob, Kendall
(Show Context)
Citation Context ...ution in hand, Solbest. If there is an improvement in the quality of the solution, then the new solution, Sol* is updated. Otherwise, the exponential monte carlo acceptance criterion is employed (see =-=[23]-=-) where a new solution, Sol* is accepted if a generated random number, RandNum inbetween [0,1] is less than e -δ where δ is the difference between the quality of the new and old solutions (i.e. δ = f(... |

34 | A Max-Min Ant System for the University Course Timetabling Problem
- Socha, Knowles, et al.
- 2002
(Show Context)
Citation Context ...ts represent an absolute requirement. A timetable which satisfies the hard constraints is known as a feasible solution. In this paper, we will test our approach on the problem instances introduced by =-=[8]-=- who present the following hard constraints: • No student can be assigned to more than one course at the same time. • The room should satisfy the features required by the course. • The number of stude... |

27 | T.: A comparison of the performance of different metaheuristics on the timetabling problem
- Rossi-Doria, Sampels, et al.
- 2003
(Show Context)
Citation Context ...et al., 2005 [13]. In [14], Socha et al. build on the ant algorithm methodologies that they first investigated in [8] and apply the results to the datasets discussed in this paper. Rossi-Doria et al. =-=[15]-=- consider the same datasets and present a comparison of a number of metaheuristic methods. Burke et al. [4] introduced a tabusearch hyperheuristic and applied it to university course timetabling in ad... |

25 |
A grouping genetic algorithm for graph colouring and exam timetabling
- Erben
- 2001
(Show Context)
Citation Context ...problem of automating the construction of university timetables. Various techniques have been applied including simulated annealing (e.g. [1,2,3]), tabu search (e.g. [4]) and genetic algorithms (e.g. =-=[5]-=-). A successful approach to many scheduling and timetabling problems (e.g. [6,7]) is represented by the combination of evolutionary based approaches with local search (sometimes called a memetic algor... |

21 | Ant algorithms for the university course timetabling problem with regard to the state-of-the-art
- Socha, Sampels, et al.
- 2003
(Show Context)
Citation Context ...d a variable neighbourhood search approach which used a fixed tabu list to penalise particular neighbourhood structures. A fuzzy approach to the problem was introduced by Asmuni et al., 2005 [13]. In =-=[14]-=-, Socha et al. build on the ant algorithm methodologies that they first investigated in [8] and apply the results to the datasets discussed in this paper. Rossi-Doria et al. [15] consider the same dat... |

19 | University Timetabling: Bridging the Gap between Research and Practice - McCollum - 2006 |

19 | The design of memetic algorithms for scheduling and timetabling problems
- Burke, Silva
- 2004
(Show Context)
Citation Context ... find that solution. Interested readers can find more details about hybrid evolutionary approaches in [18,20]. An overview of memetic algorithms for scheduling and timetabling problems can be seen in =-=[21]-=-. IV. A HYBRID EVOLUTIONARY ALGORITHM FOR THE UNIVERSITY COURSE TIMETABLING PROBLEM The main technique used in our evolutionary algorithm is a light mutation operator followed by a randomised iterativ... |

18 | Specialised recombinative operators for timetabling problems
- Burke, Elliman, et al.
- 1995
(Show Context)
Citation Context ...e presented in Figs. 4 and 5. Recall that our evolutionary method does not use a crossover operator. Such operators can create extra difficulties (such as having to “repair” offspring) in timetabling =-=[6,24,25]-=-. Combined, these figures represent the approach used in our experiments. The algorithm begins by creating an initial population of size 100. The process creates subsequent generations by firstly sele... |

13 | B.: An investigation of variable neighbourhoodsearch foruniversitycoursetimetabling
- Abdullah, Burke, et al.
- 2005
(Show Context)
Citation Context ...perheuristic [16], a fuzzy approach [13], a variable neighbourhood search with a tabu list [12] and which employed a randomised iterative improvement algorithm with composite neighbourhood structures =-=[26]-=-. The term “x%Inf.” in Table 2 indicates a percentage of runs that failed to obtain feasible solutions. Also, note that the term “Ave.” represents the average result out of a number of runs and the te... |

10 | Using a Randomised Iterative Improvement Algorithm with Composite Neighbourhood Structures for University Course Timetabling
- Abdullah, Burke, et al.
(Show Context)
Citation Context ...nstances of the problem were originally produced by Paechter’s course timetabling test instance generator [10] which was developed within the International Meteheuristic Network [11]. Abdullah et al.s=-=[12]-=- developed a variable neighbourhood search approach which used a fixed tabu list to penalise particular neighbourhood structures. A fuzzy approach to the problem was introduced by Asmuni et al., 2005 ... |

9 | Fuzzy Multiple Heuristic Ordering for Course Timetabling
- Asmuni, Burke, et al.
(Show Context)
Citation Context ...hm by Socha et al., 2002 [8] M6: The Tabu search hyper-heuristic by Burke et al., 2003 [4] M7: The Graph based hyper-heuristic by Burke et al., 2006 [16] M8: The Fuzzy approach by Asmuni et al., 2005 =-=[13]-=- VII. DISCUSSION AND CONCLUSIONS Our approach is better than the local search method on ten of the problems and is better than the ant approach of [8] on seven of the problems (with one tie on the sma... |

6 |
Extensions to a Memetic Timetabling System”, The Practice and Theory of Automated Timetabling I
- Cumming, Norman, et al.
- 1996
(Show Context)
Citation Context ...iques have been applied including simulated annealing (e.g. [1,2,3]), tabu search (e.g. [4]) and genetic algorithms (e.g. [5]). A successful approach to many scheduling and timetabling problems (e.g. =-=[6,7]-=-) is represented by the combination of evolutionary based approaches with local search (sometimes called a memetic algorithm). The paper is organised as follows: The next section describes the course ... |

5 |
Memetic evolutionary algorithms
- Hart, Krasnogor, et al.
- 2005
(Show Context)
Citation Context ...e (an evolutionary algorithm together with local search) has been given various other names in the literature such as memetic algorithms, hybrid genetic algorithms and genetic local search algorithms =-=[18]-=-. Examples of similar approaches applied to university timetabling can be found in [6,7,19]. The method described in [6] employed a memetic algorithm for university examination timetabling where two e... |

1 |
Analysing Similarity in Exam Timetabling
- Burke, Eckersley, et al.
(Show Context)
Citation Context ...ing literature, there has been a lot of attention paid to the problem of automating the construction of university timetables. Various techniques have been applied including simulated annealing (e.g. =-=[1,2,3]-=-), tabu search (e.g. [4]) and genetic algorithms (e.g. [5]). A successful approach to many scheduling and timetabling problems (e.g. [6,7]) is represented by the combination of evolutionary based appr... |

1 |
Applications to Timetabling” Section 5.6 of the Handbook of Graph Theory (edited by Jonathan Gross and Jay Yellen
- Burke, Kingston, et al.
- 2004
(Show Context)
Citation Context ...on A construction algorithm is used to generate large populations of random feasible timetables. The approach, which starts with an empty timetable, is similar to a random graph colouring method (see =-=[22]-=-). A feasible solution is obtained by adding or removing appropriate courses from the schedule until the hard constraints are met. A roulette wheel selection is employed to select individuals for the ... |