The non-emergency patient transport modelled as a team orienteering problem

This work presents an improved model to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving Orienteering Problems is presented, and this heuristic provides good results in terms of accuracy and computation time. Euclidean instances as well as asymmetric real data gathered from Google maps were used, and the model has a promising performance mainly with asymmetric cost matrices.

A multi-criteria decision support system for a routing problem in waste collection

Autor proof

A decision support system for a waste collection vehicle routing problem

The selective collection of municipal solid waste for recycling is a very complex and expensive process, where a major issue is to perform cost-efficient waste collection routes. Despite the abundance of commercially available software for fleet management, they often lack the capability to deal properly with sequencing problems and dynamic revision of plans and schedules during process execution. Our approach to achieve better solutions for the waste collection process is to model it as a vehicle routing problem, more specifically as a team orienteering problem where capacity constraints on the vehicles are considered, as well as time windows for the waste collection points and for the vehicles. The final model is called capacitated team orienteering problem with double time windows (CTOPdTW).We developed a genetic algorithm to solve routing problems in waste collection modelled as a CTOPdTW. The results achieved suggest possible reductions of logistic costs in selective waste collection.

The multiple team formation problem using sociometry

The Team Formation problem (TFP) has become a well-known problem in the OR literature over the last few years. In this problem, the allocation of multiple individuals that match a required set of skills as a group must be chosen to maximise one or several social positive attributes. Speci�cally, the aim of the current research is two-fold. First, two new dimensions of the TFP are added by considering multiple projects and fractions of people's dedication. This new problem is named the Multiple Team Formation Problem (MTFP). Second, an optimization model consisting in a quadratic objective function, linear constraints and integer variables is proposed for the problem. The optimization model is solved by three algorithms: a Constraint Programming approach provided by a commercial solver, a Local Search heuristic and a Variable Neighbourhood Search metaheuristic. These three algorithms constitute the first attempt to solve the MTFP, being a variable neighbourhood local search metaheuristic the most effi�cient in almost all cases. Applications of this problem commonly appear in real-life situations, particularly with the current and ongoing development of social network analysis. Therefore, this work opens multiple paths for future research.

Non emergency patients transport - a mixed integer linear programming

This work presents a model and a heuristic to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving problems with one vehicle was presented, and this heuristic provides good results in terms of accuracy and computation time.

Genetic algorithms for the non emergency patients transport service

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the paper. The authors would like to thank Dr. Elaine DeBock for reviewing the manuscript.

Optimização do processo de recolha de resíduos: desenvolvimento de ferramentas de investigação operacional para o problema de orientação de equipas com multi-restrições

Tese de Doutoramento em Engenharia Industrial e de Sistemas.

The Old Ball Game: Organization of Nineteenth Century Professional Base Ball Clubs

The first professional base ball clubs came in two varieties: stock clubs, which paid their players fixed wages, and player cooperatives, in which players shared the proceeds after expenses. We argue that stock clubs were formed with players of known ability, while co-ops were formed with players of unknown ability. Although residual claimancy served to screen out players of inferior ability in co-ops, the process was imperfect due to the team production problem. Based on this argument, we suggest that co-ops functioned as an early minor league system where untried players could seek to prove themselves and eventually move up to wage teams. Empirical analysis of data on player performance and experience in early professional base ball provides support for the theory.

Scheduling of track inspection and maintenance activities in railroad networks

The U.S. railroad companies spend billions of dollars every year on railroad track maintenance in order to ensure safety and operational efficiency of their railroad networks. Besides maintenance costs, other costs such as train accident costs, train and shipment delay costs and rolling stock maintenance costs are also closely related to track maintenance activities. Optimizing the track maintenance process on the extensive railroad networks is a very complex problem with major cost implications. Currently, the decision making process for track maintenance planning is largely manual and primarily relies on the knowledge and judgment of experts. There is considerable potential to improve the process by using operations research techniques to develop solutions to the optimization problems on track maintenance. In this dissertation study, we propose a range of mathematical models and solution algorithms for three network-level scheduling problems on track maintenance: track inspection scheduling problem (TISP), production team scheduling problem (PTSP) and job-to-project clustering problem (JTPCP). TISP involves a set of inspection teams which travel over the railroad network to identify track defects. It is a large-scale routing and scheduling problem where thousands of tasks are to be scheduled subject to many difficult side constraints such as periodicity constraints and discrete working time constraints. A vehicle routing problem formulation was proposed for TISP, and a customized heuristic algorithm was developed to solve the model. The algorithm iteratively applies a constructive heuristic and a local search algorithm in an incremental scheduling horizon framework. The proposed model and algorithm have been adopted by a Class I railroad in its decision making process. Real-world case studies show the proposed approach outperforms the manual approach in short-term scheduling and can be used to conduct long-term what-if analyses to yield managerial insights. PTSP schedules capital track maintenance projects, which are the largest track maintenance activities and account for the majority of railroad capital spending. A time-space network model was proposed to formulate PTSP. More than ten types of side constraints were considered in the model, including very complex constraints such as mutual exclusion constraints and consecution constraints. A multiple neighborhood search algorithm, including a decomposition and restriction search and a block-interchange search, was developed to solve the model. Various performance enhancement techniques, such as data reduction, augmented cost function and subproblem prioritization, were developed to improve the algorithm. The proposed approach has been adopted by a Class I railroad for two years. Our numerical results show the model solutions are able to satisfy all hard constraints and most soft constraints. Compared with the existing manual procedure, the proposed approach is able to bring significant cost savings and operational efficiency improvement. JTPCP is an intermediate problem between TISP and PTSP. It focuses on clustering thousands of capital track maintenance jobs (based on the defects identified in track inspection) into projects so that the projects can be scheduled in PTSP. A vehicle routing problem based model and a multiple-step heuristic algorithm were developed to solve this problem. Various side constraints such as mutual exclusion constraints and rounding constraints were considered. The proposed approach has been applied in practice and has shown good performance in both solution quality and efficiency.

Problema del agente viajero selectivo con restricciones adicionales

En esta tesis se introduce una variante del Problema del Agente Viajero Selectivo, también conocido en la literatura como Orienteering Problem (OP). En el OP se tiene un conjunto de clientes potenciales, a cada uno de los cuales se le asocia una puntuación o beneficio que recibe el agente al visitarlo, el objetivo es el de diseñar una ruta que comience y termine en el depósito y que maximice el puntaje colectado, tomando en cuenta que existe un límite máximo en la duración de la ruta. En este trabajo se consideran restricciones de conflictos entre clientes, es decir, si dos de ellos tienen conflicto, no pueden ser incluidos ambos en la ruta; por otra parte, existe un subconjunto de clientes que deben ser visitados de manera obligatoria. Se proponen dos modelos matemáticos del problema, cuya diferencia principal es la manera en que aborda la eliminación de ciclos. El primer modelo usa restricciones de tipo secuencial inspiradas en las propuestas por Miller et al. (1960) y el segundo utiliza restricciones basadas en flujo de múltiples productos y se basan en las restricciones propuestas por Wong (1980) y Claus (1984). Asimismo, se proponen dos algoritmos para la solución del problema planteado, el primero es de tipo heurístico y está basado en un esquema GRASP (Greedy Randomized Adaptive Search Procedure) reactivo, cuya fase de mejora es un método tipo VNS (Variable Neighborhood Search) general, el segundo es una estrategia de descomposición basada en generación de columnas. El desempeño de los algoritmos propuestos es evaluado a través de experimentos computacionales sobre un gran conjunto de instancias y los resultados obtenidos son comparados contra las soluciones ´optimas obtenidas al resolver los modelos matemáticos haciendo uso del solver Cplex 12.6.

Modified Team-based Learning (TBL) as a tool in Problem-based learning (PBL); Observations and Lessons from Year One

Both TBL and PBL attempt to maximally engage the learner and both are designed to encourage interactive teaching / learning. PBL is student centered. TBL, in contrast, is typically instructor centered. The PBL Executive Committee of the UTHSC-Houston Medical School, in an attempt to capture the pedagogical advantages of PBL and of TBL, implemented a unique PBL experience into the ICE/PBL course during the final block of PBL instruction in year 2. PBL cases provided the content knowledge for focused learning. The subsequent, related TBL exercises fostered integration / critical thinking about each of these cases. [See PDF for complete abstract]

Gaslini's tracheal team: preliminary experience after one year of paediatric airway reconstructive surgery.

Background: congenital and acquired airway anomalies represent a relatively common albeit challenging problem in a national tertiary care hospital. In the past, most of these patients were sent to foreign Centres because of the lack of local experience in reconstructive surgery of the paediatric airway. In 2009, a dedicated team was established at our Institute. Gaslini's Tracheal Team includes different professionals, namely anaesthetists, intensive care specialists, neonatologists, pulmonologists, radiologists, and ENT, paediatric, and cardiovascular surgeons. The aim of this project was to provide these multidisciplinary patients, at any time, with intensive care, radiological investigations, diagnostic and operative endoscopy, reconstructive surgery, ECMO or cardiopulmonary bypass. Aim of this study is to present the results of the first year of airway reconstructive surgery activity of the Tracheal Team.Methods: between September 2009 and December 2010, 97 patients were evaluated or treated by our Gaslini Tracheal Team. Most of them were evaluated by both rigid and flexible endoscopy. In this study we included 8 patients who underwent reconstructive surgery of the airways. Four of them were referred to our centre or previously treated surgically or endoscopically without success in other Centres.Results: Eight patients required 9 surgical procedures on the airway: 4 cricotracheal resections, 2 laryngotracheoplasties, 1 tracheal resection, 1 repair of laryngeal cleft and 1 foreign body removal with cardiopulmonary bypass through anterior tracheal opening. Moreover, in 1 case secondary aortopexy was performed. All patients achieved finally good results, but two of them required two surgeries and most required endoscopic manoeuvres after surgery. The most complex cases were the ones who had already been previously treated.Conclusions: The treatment of paediatric airway anomalies requires a dedicated multidisciplinary approach and a single tertiary care Centre providing rapid access to endoscopic and surgical manoeuvres on upper and lower airways and the possibility to start immediately cardiopulmonary bypass or ECMO.The preliminary experience of the Tracheal Team shows that good results can be obtained with this multidisciplinary approach in the treatment of complicated cases. The centralization of all the cases in one or few national Centres should be considered.

Evolving team compositions by agent swapping

Optimizing collective behavior in multiagent systems requires algorithms to find not only appropriate individual behaviors but also a suitable composition of agents within a team. Over the last two decades, evolutionary methods have emerged as a promising approach for the design of agents and their compositions into teams. The choice of a crossover operator that facilitates the evolution of optimal team composition is recognized to be crucial, but so far, it has never been thoroughly quantified. Here, we highlight the limitations of two different crossover operators that exchange entire agents between teams: restricted agent swapping (RAS) that exchanges only corresponding agents between teams and free agent swapping (FAS) that allows an arbitrary exchange of agents. Our results show that RAS suffers from premature convergence, whereas FAS entails insufficient convergence. Consequently, in both cases, the exploration and exploitation aspects of the evolutionary algorithm are not well balanced resulting in the evolution of suboptimal team compositions. To overcome this problem, we propose combining the two methods. Our approach first applies FAS to explore the search space and then RAS to exploit it. This mixed approach is a much more efficient strategy for the evolution of team compositions compared to either strategy on its own. Our results suggest that such a mixed agent-swapping algorithm should always be preferred whenever the optimal composition of individuals in a multiagent system is unknown.

Rewarding civil service performance through team bonuses : findings, analysis and recommendations

Performance-related pay within public organizations is continuing to spread. Although it can help to strengthen an entrepreneurial spirit in civil servants, its implementation is marred by technical, financial, managerial and cultural problems. This article identifies an added problem, namely the contradiction that exists between a managerial discourse that emphasizes the team and collective performance, on the one hand, and the use of appraisal and reward tools that are above all individual, on the other. Based on an empirical survey carried out within Swiss public organizations, the analysis shows that the team is currently rarely taken into account and singles out the principal routes towards an integrated system for the management and rewarding of civil servants.

El proyecto ‘Ecosportech’ como ejemplo de universidad emprendedora. Una experiencia a base del ‘Problem Based Learning’

El objetivo de este artículo es presentar el proyecto EcoSPORTech, cuya finalidad es la creación de una empresa social con jóvenes para la realización de actividades deportivas/ocio en el medio natural, integrando las nuevas tecnologías. Este proyecto supone una colaboración interdisciplinaria dentro de la Universidad de Vic, entre las facultades de Empresa y Comunicación (FEC), la de Ciencias de la Salud y el Bienestar (FCSB) y la de Educación (FE) e integra un equipo de profesionales procedentes de los ámbitos de la empresa, el marketing, el periodismo, el deporte y la terapia ocupacional. Estos profesores formarán al grupo de jóvenes con los que se creará la empresa y dirigirán la misma. Esta empresa (cooperativa) se integra en el vivero de empresas sociales que se está creando en la Universidad de Vic.