Abstract
The author describes a man-computer interactive mass transit crew scheduling module which was developed as a component of a Decision Support System (DSS) implemented in a personal computer at the Oporto Urban Transport Authority (STCP). The problem of crew scheduling is briefly discussed and set in the context of the broader process of the planning and control of urban transport services. The general philosophy and the structure of the module are analysed. A crew scheduling heuristic based method is presented. Particular attention is paid to the interactive nature of the approach adopted. Results of the actual implementation process at STCP are given.

Abstract
The territory alignment problem is part of a bigger procedure, the territory design, which consists of assigning small geographic regions to larger areas following the most relevant criteria for planning. This chapter aims to briefly update the review of the existing literature on the territory alignment problem, its applications and solution approaches, and to illustrate the most recent tendencies by means of a hybrid meta-heuristic developed by the authors. The approach is based in GRASP and Tabu Search meta-heuristics. The algorithm was integrated in an interactive and user-friendly Geographic Information System application, named MultiACE, also developed in the context of this study. This application was embedded in the ArcGIS software. This chapter also illustrates the potential of the proposed approach as a practical and readily implementable management decision aid in the context of a current case that involved the maintenance team of a Portuguese regional office of a worldwide equipment company. © 2012, IGI Global.

Abstract
In some formulations of the vehicle replacement problem, in particular those leading to repair limit type models, the alternative policies are evaluated and compared over a fixed planning horizon. Although it has been widely recognised that the optimal policies derived under these formulations depend critically on the length of the horizon, no method has been presented so far to set appropriately this parameter. In this paper. the authors describe a method which overcomes this shortcoming. Once the best policy has been derived from a given finite horizon with length H, such a policy is repeated indefinitely over time and an equivalent annual rent is computed. The parametrisation of H leads to the definition of an annual rent function with a sequence of nearly equidistant local minima. It is suggested that in practice the second local minimum of this function leads to an adequate choice of the parameter H. The method can be applied both to stochastic and deterministic cost modelling situations. The method was tested using both real data from large samples of different types of passenger vehicles and artificially generated data. (C) 1997 Elsevier Science B.V.

Abstract
Mining public transportation networks is a growing and explosive challenge due to the increasing number of information available. In highly populated urban zones, the vehicles can often fail the schedule. Such fails cause headway deviations (HD) between high-frequency bus pairs. In this paper, we propose to identify systematic HD which usually provokes the phenomenon known as Bus Bunching (BB). We use the PrefixSpan algorithm to accurately mine sequences of bus stops where multiple HD frequently emerges, forcing two or more buses to clump. Our results are promising: 1) we demonstrated that the BB origin can be modeled like a sequence mining problem where 2) the discovered patterns can easily identify the route schedule points to adjust in order to mitigate such events.

Abstract
It is well known that the definition of bus schedules is critical for the service reliability of public transports. Several proposals have been suggested, using data from Automatic Vehicle Location (AVL) systems, in order to enhance the reliability of public transports. In this paper we study the optimum number of schedules and the days covered by each one of them, in order to increase reliability. We use the Dynamic Time Warping distance in order to calculate the similarities between two different dimensioned irregularly spaced data sequences before the use of data clustering techniques. The application of this methodology with the K-Means for a specific bus route demonstrated that a new schedule for the weekends in non-scholar periods could be considered due to its distinct profile from the remaining days. For future work, we propose to apply this methodology to larger data sets in time and in number, corresponding to different bus routes, in order to find a consensual cluster between all the routes. ©2010 IEEE.

Abstract
In highly populated urban zones, it is common to notice headway deviations (HD) between pairs of buses. When these events occur in a bus stop, they often cause bus bunching (BB) in the following bus stops. Several proposals have been suggested to mitigate this problem. In this paper, we propose to find BBS (Bunching Black Spots) - sequences of bus stops where systematic HD events cause the formation of BB. We run a sequence mining algorithm, named PrefixSpan, to find interesting events available in time series. We prove that we can accurately model the BB trip usual pattern like a frequent sequence mining problem. The subsequences proved to be a promising way of identify the route' schedule points to adjust in order to mitigate such events. © 2012 Springer-Verlag.