Ο κύριος σκοπός της παρούσας εργασίας είναι να διερευνηθεί η χρήση ενός εναλλακτικού νέου γενετικού αλγορίθμου, που εφαρμόζεται στο ωράριο εργασίας και στον χρονοπρογραμματισμό των αστικών και υπεραστικών λεωφορείων στην Ελλάδα. Φαίνεται ότι η απόδοση επηρεάζεται από διάφορες παραμέτρους, όπως ισχυρούς ή ελαστικούς περιορισμούς, δεδομένου ενός συνόλου των οδηγών λεωφορείων, και ενός συνόλου δρομολογιών προς εκτέλεση. Πιο συγκεκριμένα, η μέθοδος που επιλέχθηκε για τη διεξαγωγή της παρούσας εργασίας είναι μια προσομοίωση των υπεραστικών λεωφορείων της πόλης της Πρέβεζας. Τέλος, τα αποτελέσματα της μελέτης δείχνουν ότι ο συνδυασμός των τεχνικών που παρουσιάστηκαν λειτουργεί αποτελεσματικά και να ξεπερνά όλα τα προηγούμενα μοντέλα σε μια απλή προσομοίωση. / The main target is to expand the usage of an alternative new generic algorithm, that is used in the timetable scheduling of urban and intercity buses in Greece. The performance is influenced by several factors. The method used is a simulation of the intercity buses of the city of Preveza. Finally, the results of the study shows that the combination of the techniques implemented works efficiently and overcomes the previous methods in a simple simulation.

Este trabalho tem como objetivo solucionar problemas complexos em diferentes segmentos da Engenharia de Produção e Transporte a partir da utilização de técnicas de otimização. São consideradas as áreas de sistemas de saúde, transportes e análise sensorial, envolvendo problemas de formação de grade de horários e análise de clusters. De forma específica, as abordagens objetivam: (i) em relação ao setor hospitalar, alocar especialidades cirúrgicas em uma grade de horários de um hospital de modo a minimizar a variância do tempo pós-operatório; (ii) quanto à análise sensorial, desenvolver um índice capaz de identificar painelistas que necessitam de treinamento utilizando conceitos de análise de clusters; (iii) no setor aeroportuário, identificar aeroportos com baixa capacidade preditiva de demanda e relacioná-los com suas características físicas, a partir da análise de clusters. Em todos os problemas abordados, as soluções envolvendo métodos de otimização se mostraram adequadas, com resultados satisfatórios. / This study aims to solve complex problems in different segments of Production Engineering and Transportation using optimization techniques. Different areas are considered, such as the areas of health systems, transport and sensory analysis, involving the timetable scheduling problem and cluster analysis. Specifically, this works aims to: (i) in relation to the hospital sector, allocate surgical specialties in a timetable in order to minimize the variance of postoperative time; (ii) for the sensory analysis, develop an index able to identify panelists who require training, using concepts of cluster analysis; (iii) in the airport sector, identify airports with low predictive capacity of demand and relate them to their physical characteristics, using cluster analysis. In all addressed problems, solutions involving optimization methods were adequate, with satisfactory results.

Este trabalho tem como objetivo solucionar problemas complexos em diferentes segmentos da Engenharia de Produção e Transporte a partir da utilização de técnicas de otimização. São consideradas as áreas de sistemas de saúde, transportes e análise sensorial, envolvendo problemas de formação de grade de horários e análise de clusters. De forma específica, as abordagens objetivam: (i) em relação ao setor hospitalar, alocar especialidades cirúrgicas em uma grade de horários de um hospital de modo a minimizar a variância do tempo pós-operatório; (ii) quanto à análise sensorial, desenvolver um índice capaz de identificar painelistas que necessitam de treinamento utilizando conceitos de análise de clusters; (iii) no setor aeroportuário, identificar aeroportos com baixa capacidade preditiva de demanda e relacioná-los com suas características físicas, a partir da análise de clusters. Em todos os problemas abordados, as soluções envolvendo métodos de otimização se mostraram adequadas, com resultados satisfatórios. / This study aims to solve complex problems in different segments of Production Engineering and Transportation using optimization techniques. Different areas are considered, such as the areas of health systems, transport and sensory analysis, involving the timetable scheduling problem and cluster analysis. Specifically, this works aims to: (i) in relation to the hospital sector, allocate surgical specialties in a timetable in order to minimize the variance of postoperative time; (ii) for the sensory analysis, develop an index able to identify panelists who require training, using concepts of cluster analysis; (iii) in the airport sector, identify airports with low predictive capacity of demand and relate them to their physical characteristics, using cluster analysis. In all addressed problems, solutions involving optimization methods were adequate, with satisfactory results.

Este trabalho tem como objetivo solucionar problemas complexos em diferentes segmentos da Engenharia de Produção e Transporte a partir da utilização de técnicas de otimização. São consideradas as áreas de sistemas de saúde, transportes e análise sensorial, envolvendo problemas de formação de grade de horários e análise de clusters. De forma específica, as abordagens objetivam: (i) em relação ao setor hospitalar, alocar especialidades cirúrgicas em uma grade de horários de um hospital de modo a minimizar a variância do tempo pós-operatório; (ii) quanto à análise sensorial, desenvolver um índice capaz de identificar painelistas que necessitam de treinamento utilizando conceitos de análise de clusters; (iii) no setor aeroportuário, identificar aeroportos com baixa capacidade preditiva de demanda e relacioná-los com suas características físicas, a partir da análise de clusters. Em todos os problemas abordados, as soluções envolvendo métodos de otimização se mostraram adequadas, com resultados satisfatórios. / This study aims to solve complex problems in different segments of Production Engineering and Transportation using optimization techniques. Different areas are considered, such as the areas of health systems, transport and sensory analysis, involving the timetable scheduling problem and cluster analysis. Specifically, this works aims to: (i) in relation to the hospital sector, allocate surgical specialties in a timetable in order to minimize the variance of postoperative time; (ii) for the sensory analysis, develop an index able to identify panelists who require training, using concepts of cluster analysis; (iii) in the airport sector, identify airports with low predictive capacity of demand and relate them to their physical characteristics, using cluster analysis. In all addressed problems, solutions involving optimization methods were adequate, with satisfactory results.

This master thesis deals with the automatic design of examinations and courses scheduling. The design is adapted to the specific requirements of the Faculty of Information Technology of Brno University of Technology. A genetic algorithm and a heuristic algorithm are employed to solve this task. The genetic algorithm is used to specify the sequence of the examinations (or the courses) and then the heuristic algorithm spread them out into a timetable. An implementation (written in Python 3) provides a fast parallel processing calculation which can generate satisfactory schedules in tens of minutes. Performed experiments show approximately 13% better results in all considered criteria in comparison with utilized examination schedules in the past. The development was periodically consulted with persons responsible for the schedule processing at the faculty. The program will be used while designing of examination schedules for the academic year 2015/2016.