A Simulated Annealing Based Approach to the High School Timetabling Problem

Fonseca, George H. G.; Brito, Samuel Souza; Santos, Haroldo Gambini

doi:10.1007/978-3-642-32639-4_66

Cited by 8 publications

(5 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Five competitors were submitted solutions to the ITC2011. HySST [11] applies a multi-stage hyper-heuristic on a set of mutational heuristics and hill climbers, GOAL [8] combines the iterated local search with simulated annealing, HFT [6] uses the evolutionary algorithms as a meta-heuristic to solve the problem, Lectio [20] applies an algorithm based on adaptive large neighbourhood search, and VAGOS [17].…”

Section: Resultsmentioning

confidence: 99%

“…Due to the NP nature of high school timetabling problems, meta-heuristics are preferred in most of the previous studies. Approaches used in HSTP include simulated annealing [8], evolutionary algorithms [6], tabu search [15], adaptive large neighborhood search [20], hyper-heuristic [11], particle swarm optimisation [21], bee algorithms [14], integer programming [5], tiling algorithms [13], walk down jump up algorithm [24] and constraint programming approach [22]. [16] provided a recent survey on HSTP.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Two Stage Approach for High School Timetabling

Shambour

Khader

Kheiri

et al. 2013

Neural Information Processing

View full text Add to dashboard Cite

There are different types of educational timetabling problems which are computationally difficult to solve. In this study, we deal with the High School Timetabling Problem which requires assignment of events, such as courses, and resources, such as classrooms, to time-slots under a set of different types of constraints. We describe an approach that hybridises an Evolutionary Algorithm variant and Simulated Annealing methods to solve this problem. This approach is tested over a set of real world instances obtained across different countries. The empirical results demonstrate the viability of the hybrid approach when compared to the previously proposed techniques.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Two Stage Approach for High School Timetabling

Shambour

Khader

Kheiri

et al. 2013

Neural Information Processing

View full text Add to dashboard Cite

show abstract

“…Furthermore, at ITC 2007, still in the same field, a combination of hill climbing algorithm with great deluge and simulated annealing was used [18]. At ITC 2011 a combination of iterated local search and simulated annealing algorithms was used to solve the problem of scheduling high school course [19].…”

Section: A International Timetabling Competition 2021mentioning

confidence: 99%

Adaptive Learning Modified Great Deluge Hyper-Heuristics

Hutama,

Muklason

2024

IJC

View full text Add to dashboard Cite

The International Timetabling Competition (ITC) 2021 focuses on sports scheduling, a domain intricately connected to optimizing combinatorics problems. Within the framework of the ITC 2021 challenge, a crucial task is to precisely allocate matches to their designated time slots. Addressing this challenge involves the utilization of the Adaptive Learning Modified Great Deluge (ALMGD) algorithm, which belongs to the realm of hyper-heuristics. This algorithm represents an evolutionary step from the foundational great deluge algorithm, incorporating an acceptance mechanism intricately woven with self-adaptive learning. To assess its efficacy, the performance of the ALMGD algorithm is scrutinized through a comparative analysis with the hill climbing and great deluge algorithms. As a result, the proposed algorithm can produce a solution that is superior to the comparison algorithm. The modified great deluge algorithm can reduce the penalty by 36%, while the hill climbing algorithm can only reduce the penalty by 29% and the great deluge algorithm reaches 34%.

show abstract

“…Their algorithm outperformed all other algorithms on this data set and yielded the best solution for 38 out of 41 instances. The subsequent study by Saviniec et al [25] proposed an algorithm based on parallelism that outperformed several stand-alone algorithms, such as iterated local search, tabu search, and simulated annealing, including two state-of-the-art algorithms by Dorneles et al [19] and Fonseca et al [26].…”

Section: Some Previous Research On Hstpmentioning

confidence: 99%

An Effective Local Particle Swarm Optimization-Based Algorithm for Solving the School Timetabling Problem

et al. 2023

View full text Add to dashboard Cite

This paper deals with the school timetabling problem. The problem was formulated as encountered in a typical Greek high school. A local version of the particle swarm optimization algorithm was developed and applied to the problem at hand. Results on well-established benchmark instances showed that the proposed algorithm achieved the proven optima provided from an integer programming method presented in earlier research. In almost all cases, the current algorithm beat the integer programming method, either concerning the lower bound yielded or the execution time needed.

show abstract

A Simulated Annealing Based Approach to the High School Timetabling Problem

Cited by 8 publications

References 11 publications

A Two Stage Approach for High School Timetabling

A Two Stage Approach for High School Timetabling

Adaptive Learning Modified Great Deluge Hyper-Heuristics

An Effective Local Particle Swarm Optimization-Based Algorithm for Solving the School Timetabling Problem

Contact Info

Product

Resources

About