Optimization methods for the operating room management under uncertainty: stochastic programming vs. decomposition approach

The operating theatres are the engine of the hospitals; proper management of the operating rooms and its staff represents a great challenge for managers and its results impact directly in the budget of the hospital. This work presents a MILP model for the efficient schedule of multiple surgeries in Operating Rooms (ORs) during a working day. This model considers multiple surgeons and ORs and different types of surgeries. Stochastic strategies are also implemented for taking into account the uncertain in surgery durations (pre-incision, incision, post-incision times). In addition, a heuristic-based methods and a MILP decomposition approach is proposed for solving large-scale ORs scheduling problems in computational efficient way. All these computer-aided strategies has been implemented in AIMMS, as an advanced modeling and optimization software, developing a user friendly solution tool for the operating room management under uncertainty.

A methodology proposal to obtain operational parameter forecasts and operational risk assessment in container terminals

Las terminales de contenedores son sistemas complejos en los que un elevado número de actores económicos interactúan para ofrecer servicios de alta calidad bajo una estricta planificación y objetivos económicos. Las conocidas como "terminales de nueva generación" están diseñadas para prestar servicio a los mega-buques, que requieren tasas de productividad que alcanzan los 300 movimientos/ hora. Estas terminales han de satisfacer altos estándares dado que la competitividad entre terminales es elevada. Asegurar la fiabilidad de las planificaciones del atraque es clave para atraer clientes, así como reducir al mínimo el tiempo que el buque permanece en el puerto. La planificación de las operaciones es más compleja que antaño, y las tolerancias para posibles errores, menores. En este contexto, las interrupciones operativas deben reducirse al mínimo. Las principales causas de dichas perturbaciones operacionales, y por lo tanto de incertidumbre, se identifican y caracterizan en esta investigación. Existen una serie de factores que al interactuar con la infraestructura y/o las operaciones desencadenan modos de fallo o parada operativa. Los primeros pueden derivar no solo en retrasos en el servicio sino que además puede tener efectos colaterales sobre la reputación de la terminal, o incluso gasto de tiempo de gestión, todo lo cual supone un impacto para la terminal. En el futuro inmediato, la monitorización de las variables operativas presenta gran potencial de cara a mejorar cualitativamente la gestión de las operaciones y los modelos de planificación de las terminales, cuyo nivel de automatización va en aumento. La combinación del criterio experto con instrumentos que proporcionen datos a corto y largo plazo es fundamental para el desarrollo de herramientas que ayuden en la toma de decisiones, ya que de este modo estarán adaptadas a las auténticas condiciones climáticas y operativas que existen en cada emplazamiento. Para el corto plazo se propone una metodología con la que obtener predicciones de parámetros operativos en terminales de contenedores. Adicionalmente se ha desarrollado un caso de estudio en el que se aplica el modelo propuesto para obtener predicciones de la productividad del buque. Este trabajo se ha basado íntegramente en datos proporcionados por una terminal semi-automatizada española. Por otro lado, se analiza cómo gestionar, evaluar y mitigar el efecto de las interrupciones operativas a largo plazo a través de la evaluación del riesgo, una forma interesante de evaluar el effecto que eventos inciertos pero probables pueden generar sobre la productividad a largo plazo de la terminal. Además se propone una definición de riesgo operativo junto con una discusión de los términos que representan con mayor fidelidad la naturaleza de las actividades y finalmente, se proporcionan directrices para gestionar los resultados obtenidos. Container terminals are complex systems where a large number of factors and stakeholders interact to provide high-quality services under rigid planning schedules and economic objectives. The socalled next generation terminals are conceived to serve the new mega-vessels, which are demanding productivity rates up to 300 moves/hour. These terminals need to satisfy high standards because competition among terminals is fierce. Ensuring reliability in berth scheduling is key to attract clients, as well as to reduce at a minimum the time that vessels stay the port. Because of the aforementioned, operations planning is becoming more complex, and the tolerances for errors are smaller. In this context, operational disturbances must be reduced at a minimum. The main sources of operational disruptions and thus, of uncertainty, are identified and characterized in this study. External drivers interact with the infrastructure and/or the activities resulting in failure or stoppage modes. The later may derive not only in operational delays but in collateral and reputation damage or loss of time (especially management times), all what implies an impact for the terminal. In the near future, the monitoring of operational variables has great potential to make a qualitative improvement in the operations management and planning models of terminals that use increasing levels of automation. The combination of expert criteria with instruments that provide short- and long-run data is fundamental for the development of tools to guide decision-making, since they will be adapted to the real climatic and operational conditions that exist on site. For the short-term a method to obtain operational parameter forecasts in container terminals. To this end, a case study is presented, in which forecasts of vessel performance are obtained. This research has been entirely been based on data gathered from a semi-automated container terminal from Spain. In the other hand it is analyzed how to manage, evaluate and mitigate disruptions in the long-term by means of the risk assessment, an interesting approach to evaluate the effect of uncertain but likely events on the long-term throughput of the terminal. In addition, a definition for operational risk evaluation in port facilities is proposed along with a discussion of the terms that better represent the nature of the activities involved and finally, guidelines to manage the results obtained are provided.

Orchestration of energy efficiency capabilities for a sustainable network management

The energy demand for operating Information and Communication Technology (ICT) systems has been growing, implying in high operational costs and consequent increase of carbon emissions. Both in datacenters and telecom infrastructures, the networks represent a significant amount of energy spending. Given that, there is an increased demand for energy eficiency solutions, and several capabilities to save energy have been proposed. However, it is very dificult to orchestrate such energy eficiency capabilities, i.e., coordinate or combine them in the same network, ensuring a conflict-free operation and choosing the best one for a given scenario, ensuring that a capability not suited to the current bandwidth utilization will not be applied and lead to congestion or packet loss. Also, there is no way in the literature to do this taking business directives into account. In this regard, a method able to orchestrate diferent energy eficiency capabilities is proposed considering the possible combinations and conflicts among them, as well as the best option for a given bandwidth utilization and network characteristics. In the proposed method, the business policies specified in a high-level interface are refined down to the network level in order to bring highlevel directives into the operation, and a Utility Function is used to combine energy eficiency and performance requirements. A Decision Tree able to determine what to do in each scenario is deployed in a Software Defined Network environment. The proposed method was validated with diferent experiments, testing the Utility Function, checking the extra savings when combining several capabilities, the decision tree interpolation and dynamicity aspects. The orchestration proved to be valid to solve the problem of finding the best combination for a given scenario, achieving additional savings due to the combination, besides ensuring a conflict-free operation.

Organizational design, quality management and competitive advantage in hotels

Purpose – The aim of this study is to examine the relationship between practices of quality management (QM) and the characteristics of organizational design, and QM and competitive advantage. Design/methodology/approach – The study uses a partial least squares approach to test these relationships in 350 hotels in Spain. Findings – The findings show that QM influences specialization, formalization and interdepartmental interactions, and that QM practices influence both cost and differentiation competitive advantage. The results also indicate the importance of QM strategic and operational systems as practices that have a key impact on the characteristics of organizational design. Similarly, the QM operational system is key in the relationship between QM and cost competitive advantage. Finally, the QM operational, information and strategic systems positively influence differentiation competitive advantage. Practical implications – When hotels adopt QM practices, there will be significant changes in a number of organizational variables, including specialization, formalization and interdepartmental interactions. This paper provides empirical evidence that QM practices improve both cost and differentiation competitive advantage in the hotel industry. Originality/value – There has been little research on the effects of QM on organizational design in the hotel industry. The contribution of this paper is that analyze the effects of QM on organizational design and competitive advantage, extending knowledge about these issues in a specific sector.

Operational capabilities’ typology: an evolution from operational practices

Operational capabilities são caracterizadas como um recurso interno da firma e fonte de vantagem competitiva. Porém, a literatura de estratégia de operações fornece uma definição constitutiva inadequada para as operational capabilities, desconsiderando a relativização dos diferentes contextos, a limitação da base empírica, e não explorando adequadamente a extensa literatura sobre práticas operacionais. Quando as práticas operacionais são operacionalizadas no ambiente interno da firma, elas podem ser incorporadas as rotinas organizacionais, e através do conhecimento tácito da produção se transformar em operational capabilities, criando assim barreiras à imitação. Apesar disso, poucos são os pesquisadores que exploram as práticas operacionais como antecedentes das operational capabilities. Baseado na revisão da literatura, nós investigamos a natureza das operational capabilities; a relação entre práticas operacionais e operational capabilities; os tipos de operational capabilities que são caracterizadas no ambiente interno da firma; e o impacto das operational capabilities no desempenho operacional. Nós conduzimos uma pesquisa de método misto. Na etapa qualitativa, nós conduzimos estudos de casos múltiplos com quatro firmas, duas multinacionais americanas que operam no Brasil, e duas firmas brasileiras. Nós coletamos os dados através de entrevistas semi-estruturadas com questões semi-abertas. Elas foram baseadas na revisão da literatura sobre práticas operacionais e operational capabilities. As entrevistas foram conduzidas pessoalmente. No total 73 entrevistas foram realizadas (21 no primeiro caso, 18 no segundo caso, 18 no terceiro caso, e 16 no quarto caso). Todas as entrevistas foram gravadas e transcritas literalmente. Nós usamos o sotware NVivo. Na etapa quantitativa, nossa amostra foi composta por 206 firmas. O questionário foi criado a partir de uma extensa revisão da literatura e também a partir dos resultados da fase qualitativa. O método Q-sort foi realizado. Um pré-teste foi conduzido com gerentes de produção. Foram realizadas medidas para reduzir Variância de Método Comum. No total dez escalas foram utilizadas. 1) Melhoria Contínua; 2) Gerenciamento da Informação; 3) Aprendizagem; 4) Suporte ao Cliente; 5) Inovação; 6) Eficiência Operacional; 7) Flexibilidade; 8) Customização; 9) Gerenciamento dos Fornecedores; e 10) Desempenho Operacional. Nós usamos análise fatorial confirmatória para confirmar a validade de confiabilidade, conteúdo, convergente, e discriminante. Os dados foram analisados com o uso de regressões múltiplas. Nossos principais resultados foram: Primeiro, a relação das práticas operacionais como antecedentes das operational capabilities. Segundo, a criação de uma tipologia dividida em dois construtos. O primeiro construto foi chamado de Standalone Capabilities. O grupo consiste de zero order capabilities tais como Suporte ao Cliente, Inovação, Eficiência Operacional, Flexibilidade, e Gerenciamento dos Fornecedores. Estas operational capabilities têm por objetivo melhorar os processos da firma. Elas têm uma relação direta com desempenho operacional. O segundo construto foi chamado de Across-the-Board Capabilities. Ele é composto por first order capabilities tais como Aprendizagem Contínua e Gerenciamento da Informação. Estas operational capabilities são consideradas dinâmicas e possuem o papel de reconfigurar as Standalone Capabilities.

Integrated traffic simulation model - phase I. Volume 4: revisions to the UTCS-1 traffic simulation model to enhance operational efficiency. Final report.

Federal Highway Administration, Washington, D.C.

Pedestrian safety programs - a review of the literature and operational experience. Final report.

Federal Highway Administration, Office of Research, Washington, D.C.

IVHS Institutional and Legal Issues Program. Review of the Travlink and Genesis operational tests. Final report.

Federal Highway Administration, Washington, D.C.

ITS Institutional and Legal Issues Program. Review of the Houston Smart Commuter operational test. Final report.

Transportation Department, Joint Program Office for Intelligent Transportation Systems, Washington, D.C.

Emergency care systems demonstration projects. Volume 3: operational plans. Final report.

National Highway Safety Bureau, Washington, D.C.

IVHS Institutional and Legal Issues Program. Review of the FAST-TRAC operational test. Final report.

Federal Highway Administration, Washington, D.C.

Procedures manual for the post-operational reporting and data extension countermeasure.

National Highway Traffic Safety Administration, Washington, D.C.

Evaluation guidelines for the advanced public transportation systems operational tests.

Federal Transit Administration, Washington, D.C.

Composting at Johnson City; final report on Joint USEPA-TVA Composting Project with operational data, 1967-1971 /

Prepared for U. S. Environmental Protection Agency, Office of Solid Waste Management Programs.

The management oversight and risk tree-MORT : including systems developed by the Idaho Operations Office and Aerojet Nuclear Company,

"February 12, 1973."