Μοντελοποίηση και επίλυση του προβλήματος κατάρτισης του ωρολόγιου προγράμματος του τμήματος Μ.Μ.Β. με μεθόδους ακέραιου προγραμματισμού σε διαδικτυακό γραφικό περιβάλλον

Η παρούσα διπλωματική εργασία αποτελεί επέκταση της δουλειάς που έγινε από τον Βασίλειο Κουτρουμπίνα για τη βελτιστοποίηση του ωρολογίου προγράμματος του Τμήματος Μηχανολόγων Μηχανικών Βιομηχανίας. Υιοθετήσαμε το αρχικό μοντέλο ακεραίου προγραμματισμού και το εξελίξαμε ώστε να μπορεί να έχει πρακτική εφαρμογή για την κάλυψη των αναγκών του τμήματος, δίνοντας τα επιθυμητά αποτελέσματα σε λογικούς χρόνους. Επιπλέον, δημιουργήθηκε ένα αρχικό γραφικό interface για την εισαγωγή και εξαγωγή δεδομένων, όπως επίσης και για την επικαιροποίηση των σχετικών βάσεων δεδομένων. Έτσι, καταλήξαμε σε ένα ουσιαστικά λειτουργικό λογισμικό που με τις απαραίτητες ανθρώπινες παρεμβάσεις μπορεί να καταστρώσει ταχύτατα το ωρολόγιο πρόγραμμα διδασκαλίας του Τμήματος Μηχανολόγων Μηχανικών Βιομηχανίας

An Analytics Based Architecture and Methodology for Collaborative Timetabling in Higher Education

Class scheduling in higher education, also known as “timetabling”, is a complex process that involves many people across an institution for several months every year, and literature on the topic has been rapidly evolving over the last 15 years. We propose architecture and methodology to enable the implementation of systems that can help users gain insight on non-trivial existing and emerging enrollment patterns that need to be considered for planning purposes, and to facilitate collaborative timetabling activities. University of Pittsburgh data on undergraduate enrollments during six recent fall terms is used to illustrate the proposed ideas. Core components are specified by: First, modeling the problem using Association Rule Analysis where the sets of courses that individual students take in an academic term are treated as transactions. This renders combinations of courses called itemsets. A new backtracking algorithm called MASAI is proposed to determine the maximum number of seats available per itemset. This corresponds to the identification of itemsets of interest as in the case at hand course itemsets with no seats available are primary targets. MASAI is a novel approach to the identification of itemsets of interest that uses information that is not available in transactional data to determine the maximum number of seats possible in each itemset. Second, in order to facilitate deeper analyses that consider the relationships between course itemsets, the problem is modeled as a multi-mode graph that incorporates information obtained with the Association Rule Analysis and MASAI. A Generalized Clique Percolation Method (GCPM) is proposed to enable the identification of overlapping and hierarchical communities in graphs/networks. GCPM is used to identify communities in the multi-mode graph, enabling the discovery of non-trivial enrollment patterns, and the identification of scheduling practices that limit the enrollment options for students. Third, the elements that would form the core of a socially translucent environment that is based on the previous components are discussed. This collaborative environment is intended to provide scheduling authorities with access to shared information on enrollment patterns and how decisions on scheduling of courses in their departments impact the overall institution’s schedule and the enrollment options for students

EDT 2004: an open interactive timetabling tool

Abstract. This article deals with the analysis and design of an interactive decision support system for timetable management. This tool will be able to take hierarchical data organization into account and to maintain coherence of the constraints on this data. Our research which has led to the creation of the EDT 2004 tool 1 has two aims. The first aim is to provide an open, generic tool which can be developed in many different ways. In order to achieve this aim, we have followed an object-oriented approach and we have defined object classes dedicated for the modeling of the timetabling problem. The second aim is to analyze the needs in timetable manipulation and to provide a generic organization so that the tool can be used in many situations. To achieve this aim, both user based and automated technics are used