Implementing graph coloring heuristic in construction phase of curriculum-based course timetabling problem

Azlan, Ammar; Hussin, Naimah Mohd

doi:10.1109/isci.2013.6612369

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…These heuristics include largest enrolment, largest degree [50], largest weighted degree [51], largest colour degree, and saturation degree [52][53][54][55]. Various studies have also explored combinations of these heuristics [56][57][58][59][60]. Additionally, these heuristics have been integrated into various metaheuristic algorithms [61][62][63][64] and hyper-heuristic frameworks [65][66][67].…”

Section: Related Workmentioning

confidence: 99%

An Improved Saturation Degree-Based Constructive Heuristic for Master Surgery Scheduling Problem: Case Study

Razali,

Rahman,

Ayob

et al. 2024

IEEE Access

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The Master Surgery Scheduling Problem (MSSP) can be described as a timetabling problem involving assigning surgery groups to operating theatre (OT) time slots. Previous MSSP optimization models considered throughput, waiting measures, resource utilization, costs, and schedule assignment objectives, neglecting consecutive days assignment preferences and surgical equipment-sharing limitations. Furthermore, previous works utilize greedy constructive heuristics to produce solutions, which increases quality but decreases feasibility. Our prior study demonstrated that the saturation degree heuristic enhances feasibility by considering assignment difficulty during event selection. However, its impact on solution quality remained unexplored. Therefore, this study proposes an improved saturation degree-based constructive heuristic that integrates objective function value for event selection to increase both quality and feasibility. The algorithm sorts surgery groups based on unit scores, prioritizing lower assignment difficulty and higher objective value. The highest-scoring group is assigned to its feasible slot with the highest slot score, following similar goals. In case of no feasible slots, the repair mechanism vacates the highest swap score slot, assessing the impact on quality and feasibility. A new mathematical model is also formulated, incorporating novel objectives regarding consecutive days assignment preference and surgical equipmentsharing limitations. Validated using real-world data from Hospital Canselor Tuanku Muhriz, the proposed algorithm is evaluated considering repair mechanism usage for feasibility and objective function value for quality. The algorithm is benchmarked against greedy, random, regret-based, and saturation degree-based constructive heuristics. Our algorithm achieved a 14.63% improvement in feasibility compared to the original variant. Its objective function value is over two times better than the closest competitor and 2.6 times superior to the original variant. Comparison with the hospital's actual plan demonstrates competitive objective function value and a more balanced waiting time distribution among surgical groups. Our study showcases that a saturation degree-based constructive heuristic considering objective function value has increased solution quality while maintaining feasibility.

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Section: Related Workmentioning

confidence: 99%

An Improved Saturation Degree-Based Constructive Heuristic for Master Surgery Scheduling Problem: Case Study

Razali,

Rahman,

Ayob

et al. 2024

IEEE Access

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“…In the first stage, the assignment is performed without considering rooms, minimum working days, curriculum compactness, or minimizing penalties for room capacity. The representation of CB-CTPs as graphs is demonstrated in [36], where vertices and connections correspond to the lectures of courses and the constraints between them. Subsequently, graph coloring algorithms are employed to solve these CB-CTPs.…”

Section: Related Work On Cb-ctpmentioning

confidence: 99%

An Exploration and Exploitation-Based Metaheuristic Approach for University Course Timetabling Problems

Badoni

Sahoo

Srivastava

et al. 2023

Axioms

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The university course timetable problem (UCTP) is known to be NP-hard, with solution complexity growing exponentially with the problem size. This paper introduces an algorithm that effectively tackles UCTPs by employing a combination of exploration and exploitation strategies. The algorithm comprises two main components. Firstly, it utilizes a genetic algorithm (GA) to explore the search space and discover a solution within the global optimum region. Secondly, it enhances the solution by exploiting the region using an iterated local search (ILS) algorithm. The algorithm is tested on two common variants of UCTP: the post-enrollment-based course timetable problem (PE-CTP) and the curriculum-based course timetable problem (CB-CTP). The computational results demonstrate that the proposed algorithm yields competitive outcomes when compared empirically against other existing algorithms. Furthermore, a t-test comparison with state-of-the-art algorithms is conducted. The experimental findings also highlight that the hybrid approach effectively overcomes the limitation of local optima, which is encountered when solely employing GA in conjunction with local search.

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“…2) N. M. Hussin and A. Azlan (2013), have put into practise the graph colouring heuristic method for building process scheduling difficulty stages. Schedule challenge is addressed as a graphical representation issue.…”

Section: Literature Surveymentioning

confidence: 99%

Automatic Timetable Generator

Patil¹

2023

IJRASET

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The goal of this project is to create a time table generator for colleges. The creation of schedules is a very common issue that affects all educational institutions. The conflict between staff members' preferences is precisely where the issue arises. Every semester, colleges are required to create time tables, which used to be an extremely time-consuming task. Once the timetables are set for a given semester, the student is allowed to access them. Once the timetables are established for a particular semester, employees are also permitted to check the class allotment schedule.

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Implementing graph coloring heuristic in construction phase of curriculum-based course timetabling problem

Cited by 4 publications

References 11 publications

An Improved Saturation Degree-Based Constructive Heuristic for Master Surgery Scheduling Problem: Case Study

An Improved Saturation Degree-Based Constructive Heuristic for Master Surgery Scheduling Problem: Case Study

An Exploration and Exploitation-Based Metaheuristic Approach for University Course Timetabling Problems

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