A graph edge colouring approach for school timetabling problems

Badoni, Rakesh P.; Gupta, Dharmendra K.

doi:10.1504/ijmor.2014.057853

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…However, the solution to this algorithm was not on par with other algorithms. Aside from Evolution algorithms and Swamp algo-rithms, a graph edge coloring algorithm to search for the timetable had been implemented by Rakesh [19]. The algorithm is split into 2 parts, the first use a bipartite to get a daily schedule in the matrix, then the second phrase assign lectures into the timeslot.…”

Section: Related Researchesmentioning

confidence: 99%

Genetic Algorithm for Solving Multi-Objective Optimization in Examination Timetabling Problem

Son

Jaafar

Aziz

et al. 2021

Int. J. Emerg. Technol. Learn.

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Examination timetabling is one of 3 critical timetabling jobs besides enrollment timetabling and teaching assignment. After a semester, scheduling examinations is not always an easy job in education management, especially for many data. The timetabling problem is an optimization and Np-hard problem. In this study, we build a multi-objective optimizer to create exam schedules for more than 2500 students. Our model aims to optimize the material costs while ensuring the dignity of the exam and students' convenience while considering the rooms' design, the time requirement of each exam, which involves rules and policy constraints. We propose a programmatic compromise to approach the maximum tar-get optimization model and solve it using the Genetic Algorithm. The results show the effectiveness of the introduced algorithm.

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Section: Related Researchesmentioning

confidence: 99%

Genetic Algorithm for Solving Multi-Objective Optimization in Examination Timetabling Problem

Son

Jaafar

Aziz

et al. 2021

Int. J. Emerg. Technol. Learn.

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“…Formalizing time scheduling process is a complex task that involves different reasoning strategies, structures and elements from multiple languages. Several attempts of formalizing time schedules using classical techniques exist in the literature (simulated annealing [6], genetic algorithm [7], Tabu search [8,9], case-based reasoning [10], and graph coloring approach [11,12,13,14]. However, these approaches lack formalization and are not simple to implement needed semantics during problem solving.…”

Section: Introductionmentioning

confidence: 99%

A Formal Ontology-based Framework Towards an Intelligent Temporal Scheduler

Usip¹,

Inyang²,

Asuquo³

et al. 2019

Adv. sci. technol. eng. syst. j.

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Time scheduling as seen in timetabling processes with few and/or competing resources has exposed complex interoperable time scheduling. Attempts to resolving these time scheduling processes has been undertaken, using several classical methods, with difficulty due to inherent complexities, constraints and conflicting issues. The use of ontology-based approaches to resolve time complexity is recently adopted due to its ease in interoperability and reuse of data. The probability weighted ontology provides the various types of complexity as a requirement for the complexity reduction. To determine the optimality of the resulting timetable required the evaluation of its criteria using the analytical hierarchy process. The need for a formal representation to explicate the intelligent behaviour of the ontology-based framework of the temporal scheduler arises. Hence, this work is aimed at providing that formal representation of the logical part of the ontology. The basic rules handling the constraints in the timetabling process are outlined with the corresponding formal representations of the interval-based logic using first-order logic. The semantic model of the temporal scheduler is further described following Guarino's formal ontology model. The unified modeling language (UML) design of a system framework prototype that adopts the formal model is also given. Through the formal ontology-based framework, all constraints that will give optimality are explicated and incorporated into the allocation reasoned, which results in an optimal formal ontology-based model. This will ensure reliability, ease of use and the likelihood of re-usability of the resulting timetable.

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