Add to ORKGAbstract. This paper presents an attempt to find a statistical model that predicts the hardness of the University Course Timetabling Problem by analyzing instance properties. The model may later be used for better understanding what makes a particular instance hard. It may also be used for tuning the algorithm actually solving that problem instance. The paper introduces the definition of hardness, explains the statistical approach used for modeling instance hardness, as well as presents results obtained and possible ways of exploiting them.
In this article, two solution approaches are compared for a real-world, moderate-size but a highly c...
[[abstract]]The hardness of an instance of the Post’s correspondences problem (abbreviated to PCP) w...
The empirical study of algorithms is a crucial topic in the design of new algorithms because the con...
Most performance metrics for learning algorithms do not provide information about the misclassified ...
We investigate the applicability of an existing framework for algorithm runtime prediction to the fi...
The timetabling problem has traditionally been treated as a mathematical optimization, heuristic, or...
We investigate the applicability of an existing framework for algorithm runtime prediction to the fi...
Abstract Most data complexity studies have focused on characterizing the complexity of the entire da...
We consider the university course timetabling problem, which is one of the most studied problems in ...
Abstract. Empirical hardness models predict a solver’s runtime for a given instance of an N P-hard p...
We propose an algorithm selection approach and an instance space analysis for the well-known curricu...
In the process of developing a university’s weekly course timetable, changes in the data, such as th...
In this thesis, we present a way to model uncertainty when optimizing the UniversityTimetabling Prob...
In the process of developing a university’s weekly course timetable, changes in the data, such as th...
Abstract. Combinations of population-based approaches with local search have provided very good resu...
In this article, two solution approaches are compared for a real-world, moderate-size but a highly c...
[[abstract]]The hardness of an instance of the Post’s correspondences problem (abbreviated to PCP) w...
The empirical study of algorithms is a crucial topic in the design of new algorithms because the con...
Most performance metrics for learning algorithms do not provide information about the misclassified ...
We investigate the applicability of an existing framework for algorithm runtime prediction to the fi...
The timetabling problem has traditionally been treated as a mathematical optimization, heuristic, or...
We investigate the applicability of an existing framework for algorithm runtime prediction to the fi...
Abstract Most data complexity studies have focused on characterizing the complexity of the entire da...
We consider the university course timetabling problem, which is one of the most studied problems in ...
Abstract. Empirical hardness models predict a solver’s runtime for a given instance of an N P-hard p...
We propose an algorithm selection approach and an instance space analysis for the well-known curricu...
In the process of developing a university’s weekly course timetable, changes in the data, such as th...
In this thesis, we present a way to model uncertainty when optimizing the UniversityTimetabling Prob...
In the process of developing a university’s weekly course timetable, changes in the data, such as th...
Abstract. Combinations of population-based approaches with local search have provided very good resu...
In this article, two solution approaches are compared for a real-world, moderate-size but a highly c...
[[abstract]]The hardness of an instance of the Post’s correspondences problem (abbreviated to PCP) w...
The empirical study of algorithms is a crucial topic in the design of new algorithms because the con...