Feature-based tuning of simulated annealing applied to the curriculum-based course timetabling problem

We consider the university course timetabling problem, which is one of the most studied problems in educational timetabling. In particular, we focus our attention on the formulation known as the curriculum-based course timetabling problem, which has been tackled by many researchers and for which there are many available benchmarks. The contribution of this paper is twofold. First, we propose an effective and robust single-stage simulated annealing method for solving the problem. Secondly, we design and apply an extensive and statistically-principled methodology for the parameter tuning procedure. The outcome of this analysis is a methodology for modeling the relationship between search method parameters and instance features that allows us to set the parameters for unseen instances on the basis of a simple inspection of the instance itself. Using this methodology, our algorithm, despite its apparent simplicity, has been able to achieve high quality results on a set of popular benchmarks. A final contribution of the paper is a novel set of real-world instances, which could be used as a benchmark for future comparison

Comments on: An overview of curriculum-based course timetabling

1noopenopenSchaerf, AndreaSchaerf, Andre

Educational timetabling: Problems, benchmarks, and state-of-the-art results

We propose a survey of the research contributions on the field of Educational Timetabling with a specific focus on “standard” formulations and the corresponding benchmark instances. We identify six of such formulations and we discuss their features, pointing out their relevance and usability. Other available formulations and datasets are also reviewed and briefly discussed. Subsequently, we report the main state-of-the-art results on the selected benchmarks, in terms of solution quality (upper and lower bounds), search techniques, running times, and other side settings

Hybrid meta-heuristics for combinatorial optimization

Combinatorial optimization problems arise, in many forms, in vari- ous aspects of everyday life. Nowadays, a lot of services are driven by optimization algorithms, enabling us to make the best use of the available resources while guaranteeing a level of service. Ex- amples of such services are public transportation, goods delivery, university time-tabling, and patient scheduling. Thanks also to the open data movement, a lot of usage data about public and private services is accessible today, sometimes in aggregate form, to everyone. Examples of such data are traffic information (Google), bike sharing systems usage (CitiBike NYC), location services, etc. The availability of all this body of data allows us to better understand how people interacts with these services. However, in order for this information to be useful, it is necessary to develop tools to extract knowledge from it and to drive better decisions. In this context, optimization is a powerful tool, which can be used to improve the way the available resources are used, avoid squandering, and improve the sustainability of services. The fields of meta-heuristics, artificial intelligence, and oper- ations research, have been tackling many of these problems for years, without much interaction. However, in the last few years, such communities have started looking at each other’s advance- ments, in order to develop optimization techniques that are faster, more robust, and easier to maintain. This effort gave birth to the fertile field of hybrid meta-heuristics.openDottorato di ricerca in Ingegneria industriale e dell'informazioneopenUrli, Tommas

Um estudo de estruturas de vizinhanças no GRASP aplicado ao Problema de Tabela-Horário para Universidades

Tabela-horário educacional é um dos problemas mais pesquisados na classe de problemas de tabela-horário. Este problema consiste em alocar uma sequência de aulas nas salas disponíveis para um período de tempo predeterminado considerando necessidades de alunos, professores e satisfazendo algumas restrições. Existem três classes de problema de tabela-horário educacional: tabela-horário de exames, de escolas e de universidades. Várias formulações para o problema de tabela-horário para universidades podem ser encontradas na literatura porque as necessidades que devem ser atendidas na construção da tabela-horário variam para cada instituição de ensino. Neste trabalho foi abordado o problema de tabela-horário de universidades baseada em cursos em acordo com o segundo campeonato internacional de tabela-horário ITC-2007. Para solucionar o problema utilizamos a meta-heurística GRASP com os algoritmos Steepest Descent, Hill Climbing e Simulated Annealing como busca local utilizando várias vizinhanças conhecidas na literatura. Além de propor uma solução com o algoritmo GRASP, que é comparado com outras propostas na literatura, também é realizada uma análise detalhada das vizinhanças para este problema

Operational research:methods and applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order