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
This paper presents and evaluates an order release decision rule in a job-shop, based on the input-output control concept. The order release mechanism is part of a global decision-making scheme that includes four main decisions: accept/reject orders, define the order's due date, release the accepted jobs and dispatch it on the shop floor. This paper also presents an evaluation of two acceptance rules, four release mechanisms, and two dispatching rules, using four levels of due date tightness. Extensive simulation experiments were performed to compare the different decision rules, using several criteria: mean tardiness, percent tardy, mean absolute deviation, mean queue time in the shop floor and in the system, and machine usage. We conclude that considering the four decisions simultaneously improve the job-shop performance, and planning both the input and the output when deciding to release a job, leads to an improvement of the operational performance measures. Copyright © 2012 Inderscience Enterprises Ltd.

Abstract
In this paper, we consider the single machine scheduling problem with quadratic earliness and tardiness costs, and no machine idle time. We propose a genetic approach based on a random key alphabet and present several algorithms based on this approach. These versions differ on the generation of both the initial population and the individuals added in the migration step, as well as on the use of local search. The proposed procedures are compared with the best existing heuristics, as well as with optimal solutions for the smaller instance sizes. The computational results show that the proposed algorithms clearly outperform the existing procedures and are quite close to the optimum. The improvement over the existing heuristics increases with both the difficulty and the size of the instances. The performance of the proposed genetic approach is improved by the initialization of the initial population, the generation of greedy randomized solutions, and the addition of the local search procedure. Indeed, the more sophisticated versions can obtain similar or better solutions and are much faster. The genetic version that incorporates all the considered features is the new heuristic of choice for small and medium size instances.

Abstract
Serious Games are in increasing use for serious purposes, such as health. Particularly in the field of cognitive rehabilitation, they can offer new solutions that are fun, user-friendly and goal-directed. In this study, a prototype rehabilitation platform is presented, aimed at intervening in executive functioning and other related cognitive functions in patients with Acquired Brain Injury. It was tested in three studies investigating patients' satisfaction and performance in a virtual environment using 2D computer-screen or 3D projection-screen approaches, and patients' satisfaction with the virtual reality (VR) program regarding its usability and role in motivation to participate in the rehabilitation process. Contributing to the final version of the program, results in our pilot-studies are promising, supporting the usability of the VR program and showing its relevance in subjects' motivation to participate in the rehabilitation process.

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
With advancement in computer science and information technology, computing systems are becoming increasingly more complex with an increasing number of heterogeneous components. They are thus becoming more difficult to monitor, manage, and maintain. This process has been well known as labor intensive and error prone. In addition, traditional approaches for system management are difficult to keep up with the rapidly changing environments. There is a need for automatic and efficient approaches to monitor and manage complex computing systems. In this paper, we propose an innovative framework for scheduling system management by combining Autonomic Computing (AC) paradigm, Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems.