Benchmarking curriculum-based course timetabling: Formulations, data formats, instances, validation, visualization, and results

Annals of Operations Research (Impact Factor: 1.22). 04/2012; 194(1):59-70. DOI: 10.1007/s10479-010-0707-0
Source: DBLP


We propose a set of formulations for the Curriculum-Based Course Timetabling problem, with the aim of “capturing” many real-world
formulations, and thus encouraging researchers to “reduce” their specific problems to one of them, gaining the opportunity
to compare and assess their results. This work is accompanied by a web application that maintains all the necessary infrastructures for benchmarking: validators, data formats, instances, reference scores, lower bounds, solutions, and visualizers. All instances
proposed here are based on real data from various universities and they represent a variety of possible situations.

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Available from: Luca Di Gaspero,
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    • "ple enough, a strong selection of features had to be done in the definition of the " standard " problems (McCollum et al. 2010; Bonutti et al. 2012). In some cases, the selection has been done at the expenses of the faithfulness to the real-world model. "
    Top 07/2015; 23(2):362-365. DOI:10.1007/s11750-015-0365-0 · 0.83 Impact Factor
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    • "We have implemented two MiniZinc models for the Curriculum-based Course Timetabling problem. For the sake of brevity we refer to [3] for the definition of the problem. The first model considers only the hard constraints and uses two arrays of variables, which assign each lecture to a period and to a room, respectively. "
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    ABSTRACT: MiniZinc is a high-level declarative modeling language that has become quite popular in the last few years. One of the main features of MiniZinc is the underlying middle-level constraint language FlatZinc, into which a MiniZinc model, along with a given instance, is translated. In this work, we describe an on-going project consisting in the implementation of a FlatZinc solver based on local search. The solver makes use of the framework EASYLOCAL++, which provides an abstract implementation of local search techniques.
    Metaheuristics International Conference, Agadir, Morocco; 06/2015
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    • "The curriculum-based course timetabling problem has been selected as one of the competition tracks of the International Timetabling Competition 2007 (ITC2007). This study used problem definition presented in Bonutti, De Cesco, Di Gaspero, & Schaerf [25] which extended from technical description in the ITC2007 web site and the corresponding technical report from Di Gaspero et al. [26]. The CB-CTT problem definition consists of the following basic entities: "
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    ABSTRACT: In this paper, harmony search algorithm is applied to curriculum-based course timetabling. The implementation, specifically the process of improvisation consists of memory consideration, random consideration and pitch adjustment. In memory consideration, the value of the course number for new solution was selected from all other course number located in the same column of the Harmony Memory. This research used the highest occurrence of the course number to be scheduled in a new harmony. The remaining courses that have not been scheduled by memory consideration will go through random consideration, i.e. will select any feasible location available to be scheduled in the new harmony solution. Each course scheduled out of memory consideration is examined as to whether it should be pitch adjusted with probability of eight procedures. However, the algorithm produced results that were not comparatively better than those previously known as best solution. With proper modification in terms of the approach in this algorithm would make the algorithm perform better on curriculum-based course timetabling.
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