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A Survey of Automated Timetabling
, 1999
"... The timetabling problem consists in scheduling a sequence of lectures between teachers and students in a prefixed period of time (typically a week), satisfying a set of constraints of various types. A large number of variants of the timetabling problem have been proposed in the literature, which d ..."
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Cited by 185 (15 self)
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The timetabling problem consists in scheduling a sequence of lectures between teachers and students in a prefixed period of time (typically a week), satisfying a set of constraints of various types. A large number of variants of the timetabling problem have been proposed in the literature, which differ from each other based on the type of institution involved (university or school) and the type of constraints. This problem, that has been traditionally considered in the operational research field, has recently been tackled with techniques belonging also to Artificial Intelligence (e.g., genetic algorithms, tabu search, and constraint satisfaction). In this paper, we survey the various formulations of the problem, and the techniques and algorithms used for its solution.
Tabu Search Techniques for Large HighSchool Timetabling Problems
 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS
, 1996
"... The highschool timetabling problem regards the weekly scheduling for all the lectures of a high school. The problem consists in assigning lectures to periods in such a way that no teacher (or class) is involved in more than one lecture at a time, and other side constraints are satisfied. The pro ..."
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Cited by 60 (8 self)
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The highschool timetabling problem regards the weekly scheduling for all the lectures of a high school. The problem consists in assigning lectures to periods in such a way that no teacher (or class) is involved in more than one lecture at a time, and other side constraints are satisfied. The problem is NPcomplete and is usually tackled using heuristic methods. This paper describes a solution algorithm (and its implementation) based on tabu search. The algorithm interleaves different types of moves and makes use of an adaptive relaxation of the hard constraints. The implementation of the algorithm has been successfully experimented in some large high schools with various kinds of side constraints.
UTSE: Construction of Optimum Timetables for University Courses  A CLP Based Approach
 CONFERENCE ON THE PRACTICAL APPLICATIONS OF PROLOG
, 1995
"... The construction of timetables for universities or schools is an extremely complex problem, whose manual solution requires much effort. The set of all possible solutions, that is the search space of the problem, is very large, at least in the realworld examples. An acceptable solution is one that sa ..."
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Cited by 24 (3 self)
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The construction of timetables for universities or schools is an extremely complex problem, whose manual solution requires much effort. The set of all possible solutions, that is the search space of the problem, is very large, at least in the realworld examples. An acceptable solution is one that satisfies all the problem constraints. The problem becomes even more difficult if someone wants to generate an optimum timetable according to some heuristic criteria. Various attempts have been made so far on the automatic solving of the timetabling problem by a computer. In this paper, a method is proposed for the construction of optimum timetables for university courses. A specific system is presented which has been used for the timetabling procedure of the Department of Informatics of the University of Athens. The software platform of the implementation is an instance of the Constraint Logic Programming class of languages, the ECL i PS e system. ECL i PS e is proved to be an appropriate vehicle for managing the complexity of the timetabling problem.
Metaheuristics For HighSchool Timetabling
, 1997
"... In this paper we present the results of an investigation of the possibilities offered by three wellknown metaheuristic algorithms to solve the timetable problem, a multiconstrained, NPhard, combinatorial optimization problem with realworld applications. First, we present our model of the problem, ..."
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Cited by 19 (0 self)
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In this paper we present the results of an investigation of the possibilities offered by three wellknown metaheuristic algorithms to solve the timetable problem, a multiconstrained, NPhard, combinatorial optimization problem with realworld applications. First, we present our model of the problem, including the definition of a hierarchical structure for the objective function, and of the neighborhood search operators which we apply to matrices representing timetables. Then we report about the outcomes of the utilization of the implemented systems to the specific case of the generation of a school timetable. We compare the results obtained by simulated annealing, tabu search and two versions, with and without local search, of the genetic algorithm. Our results show that GA with local search and tabu search based on temporary problem relaxations both outperform simulated annealing and handmade timetables. 1. Introduction Metaheuristic algorithms [23] constitute a class of computation...
A Genetic Algorithm To Solve The Timetable Problem
, 1993
"... In this paper we present the results of an investigation of the possibilities offered by genetic algorithms to solve the timetable problem. This problem has been chosen since it is representative of the class of multiconstrained, NPhard, combinatorial optimization problems with realworld applicat ..."
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Cited by 16 (0 self)
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In this paper we present the results of an investigation of the possibilities offered by genetic algorithms to solve the timetable problem. This problem has been chosen since it is representative of the class of multiconstrained, NPhard, combinatorial optimization problems with realworld application. First we present our model, including the definition of a hierarchical structure for the objective function and the generalized genetic operators which can be applied to matrices representing timetables. Then we report about the outcomes of the utilization of the implemented system to the specific case of the generation of a school timetable. We compare two versions of the genetic algorithm (GA), with and without local search, both to a handmade timetable and to two other approaches based on simulated annealing and tabu search. Our results show that GA with local search and tabu search with relaxation both outperform simulated annealing and handmade timetables. (Introduction) Evolutio...
A Generic ObjectOriented Constraint Based Model for University Course Timetabling
, 2000
"... . The construction of course timetables for academic institutions is a very difficult problem with a lot of constraints that have to be respected and a huge search space to be explored, even if the size of the problem input is not significantly large, due to the exponential number of the possibl ..."
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Cited by 2 (1 self)
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. The construction of course timetables for academic institutions is a very difficult problem with a lot of constraints that have to be respected and a huge search space to be explored, even if the size of the problem input is not significantly large, due to the exponential number of the possible feasible timetables. On the other hand, the problem itself does not have a widely approved definition, since different variations of it are faced by different departments. However, there exists a set of entities and constraints among them which are common to every possible instantiation of the timetabling problem. In this paper, we present a model of this common core in terms of a constraint programming objectoriented C++ library, namely the Ilog Solver, and we show the way this model may be extended to cover the needs of a specific academic unit, the Department of Informatics of the University of Athens. The exploration of the relevant search space, in order to find solutions of ...
Programming Approach
, 2004
"... Constraint programming is a relatively new approach for solving combinatorial optimization problems. This approach is especially effective for large scale scheduling problems with side conditions. University course scheduling problem is one of the hard problems in combinatorial optimization. Furthe ..."
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Constraint programming is a relatively new approach for solving combinatorial optimization problems. This approach is especially effective for large scale scheduling problems with side conditions. University course scheduling problem is one of the hard problems in combinatorial optimization. Furthermore, the specific requirements of each institution make it very difficult to suggest a generalized model and a solution algorithm for this problem. The purpose of this study was to design a decision support system for scheduling courses at a university. This system utilizes both constraint programming and mathematical programming techniques. The problem is solved in three stages. The first two stages, in tandem, generate a course schedule using constraint programming; in the last stage, classrooms are assigned to courses based on solution of a binary integer programming model. The proposed system is validated by experimental runs using actual course offerings and classroom data from past semesters.