Programmed Search in a Timetabling Problem over Finite Domains

González-del-Campo, Ramón; Sáenz-Pérez, Fernando

doi:10.1016/j.entcs.2007.01.013

Cited by 6 publications

(2 citation statements)

References 23 publications

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“…Carter et al [1], Deris et al [2], and Asratian and de Werra [3] proved that the timetabling problem is a NP-complete problem and an optimum solution cannot be obtained. Gonzalez del Campo and Saenz Perez [4] showed that there were four techniques to solve the problem, namely 1) evolutionary computing, 2) integer programming, 3) constraint programming, and 4) constraint logic programming. Daskalaki et al [5] developed an integer programming formulation for university timetabling to minimize a linear cost function.…”

Section: Introductionmentioning

confidence: 99%

Improving Energy Efficiency by Classroom Scheduling: A Case Study in a Thai University

Sethanan

Theerakulpisut

Benjapiyaporn

2014

AMR

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In an attempt to improve energy efficiency in classrooms by classroom scheduling, an algorithm was developed to solve the timetabling problem in a Thai university. The algorithm using Tabu Search, unlike all other algorithms for time tabling, aims at reducing classroom energy consumption. The algorithm took into account the number of students in each class, class time, class size, time available for both students enrolling in each class and faculty members in charge of the classes, and energy consumption in each time period of the classroom. The algorithm was used to solve the past timetabling problem of a Thai university over the academic year 2006 to 2012 and the results were compared with those of the trial-and-error traditional timetabling. It was found that the algorithm can be used to significantly lower energy consumption of the classrooms.

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Section: Introductionmentioning

confidence: 99%

Improving Energy Efficiency by Classroom Scheduling: A Case Study in a Thai University

Sethanan

Theerakulpisut

Benjapiyaporn

2014

AMR

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“…Many efficient algorithms, such as traditional Integer Programming [2], [3], [4] Constraint Logic Programming [5], [6] and meta-heuristic algorithms [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23], have been designed to solve the educational timetabling problem. It should be noted that the University Course Timetabling Problem (UCTP) competition, organized by Metaheuristics Network and sponsored by PATAT in 2002 [7], has greatly promoted the application of meta-heuristic algorithms.…”

Section: Introductionmentioning

confidence: 99%

A clique-based algorithm for constructing feasible timetables

Liu

Zhang

Chin

2011

Optimization Methods and Software

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Constructing a feasible solution, where the focus is on "hard" constraints only, is an important part of solving timetabling problems. For the University Course Timetabling Problem (UCTP), we propose a heuristic algorithm to schedule events to timeslots based on cliques, each representing a set of events that could be scheduled in the same timeslot, which the algorithm constructs. Our algorithm has been tested on a set of well-known instances, and the experimental results show that our algorithm compares favorably with other effective algorithms.

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Integrating ILOG CP Technology into $\mathcal{TOY}$

Castiñeiras¹,

Sáenz-Pérez

2010

Functional and Constraint Logic Programming

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Programmed Search in a Timetabling Problem over Finite Domains

Cited by 6 publications

References 23 publications

Improving Energy Efficiency by Classroom Scheduling: A Case Study in a Thai University

Improving Energy Efficiency by Classroom Scheduling: A Case Study in a Thai University

A clique-based algorithm for constructing feasible timetables

Integrating ILOG CP Technology into $\mathcal{TOY}$

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