A Review of Metaheuristic Techniques for Solving University Course Timetabling Problem

Kaur, Manpreet; Saini, Sanjay

doi:10.1007/978-981-15-5421-6_3

Cited by 8 publications

(8 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, the literature identifies many issues with timetabling in higher education structures, creating issues in managing the course. Kaur and Saini (2020) highlight that the prominent issues in timetable management are inadequate classroom facilities/management, and poor communication between academic institutions and students. Albalooshi and Shatnawi (2021) further highlight that digitisation and the integration of VLE platforms addresses these issues.…”

Section: Efficiency Of the Timetable On The Coursementioning

confidence: 99%

Enhancing the organisation and the management of built environment higher education courses

Gomis

Saini

Pathirage

et al. 2022

QAE

View full text Add to dashboard Cite

Purpose Persistent critical issues in built environment higher education (BEHE) curricula may need to be addressed by improving course organisation and management. In addition to the implications of the COVID pandemic, issues such as inadequate communication and lack of contemporary and innovative practices integrated with course delivery have resulted in a gap for Course organisation and management. The purpose of this study is to recommend a set of drivers that can assist academics and academic institutions in improving course development, organisation and management in the BEHE context. Thus, the study focused on three themes: course organisation and administration, timetabling and course communication. Design/methodology/approach A systematic approach was taken to obtain data, where a documental analysis and a close-ended questionnaire were adopted as data collection instruments. The documental analysis considered 334 mid module reviews (MMRs) generating data from architecture, construction management, civil engineering, surveying and real estate students. Content analysis was used to identify critical themes within the MMRs and develop a closed-ended questionnaire. Twenty academics from each discipline completed the questionnaire. Eight drivers were developed from the data obtained from both MMRs and questionnaires. Content analysis and interpretive structural modelling were applied to identify the relationship between the drivers. Finally, these drivers were categorised by their level of influence and reliance to highlight how they contributed to improving course organisation and management. Findings The study revealed eight drivers that can improve course organisation and management in the BEHE context. The study found that using virtual learning environments and communication are fundamental in course organisation and management. Practical implications This research paper suggests drivers to improve how academics and academic institutions organise and manage courses. The study recommends eight drivers that could be used as a guideline and a best practice as per the level partitioning diagram developed to enhance the course organisation and management in BEHE. Originality/value The study proposes a set of drivers to improve course organisation and management in BEHE curricula. Furthermore, insight into how these drivers influence and rely on each driver and their relation with the national student survey theme are novel contributions to the current body of knowledge. The paper further clarifies how they should be implemented for successful course organisation and management, thus, improving the quality of courses in higher education curricula.

show abstract

Section: Efficiency Of the Timetable On The Coursementioning

confidence: 99%

Enhancing the organisation and the management of built environment higher education courses

Gomis

Saini

Pathirage

et al. 2022

QAE

View full text Add to dashboard Cite

show abstract

“…Therefore, neighborhood production is one of the important issues in SA. To implement the thermal simulation algorithm, the basic factors including starting point, generator of motion, neighborhood generation, acceptance criterion and stop condition are needed [62,63].…”

Section: Simulated Annealing (Sa) Algorithmmentioning

confidence: 99%

A New Direct Coefficient-Based Heuristic Algorithm for Set Covering Problems

Hashemi¹,

Gholami²,

Venkatadri³

et al. 2021

Int. J. Fuzzy Syst.

View full text Add to dashboard Cite

The set covering problem is a fundamental model which comprises a wide range of important applications such as crew scheduling problems that need to cover a set of trips. It is one of the most common issues in the facility location problem, which requires further investigations, particularly in emergency and service facilities. As such, the objective of this study is to propose a new coefficient-based heuristic algorithm for the set covering problems. This paper has accordingly presented the algorithm that evaluates the qualification of subsets by directly applying a fitness function. This fitness function is formulated based on sets and subsets coefficients in a way that the subsets of selected sets have the lowest probability to be selected in the next iteration. The algorithm is not only capable of constructing an answer within polynomial time, but can solve complex set covering problems without conventional restrictions. The performance of this algorithm is evaluated on benchmark instances including a set of reproduced and selected OR-library problems within different sizes. Computational results indicate that the proposed heuristic algorithm produces better solutions, especially in large-scale problems comparing simulated annealing in terms of quality and time.

show abstract

“…To solve timetabling problems, different types of approaches have been used. Approximate approaches such as heuristics (Abdullah, 2006), metaheuristics (Kaur and Saini, 2020) and hyperheuristics (Pillay, 2016), among others, are widely used. They provide a good trade-off between the quality of the solution and the computation time.…”

Section: Literature Reviewmentioning

confidence: 99%