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.

Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services

We define a capacity reserve model to dimension passenger car service installations according to the demographic distribution of the area to be serviced by using hospital?s emergency room analogies. Usually, service facilities are designed applying empirical methods, but customers arrive under uncertain conditions not included in the original estimations, and there is a gap between customer?s real demand and the service?s capacity. Our research establishes a valid methodology and covers the absence of recent researches and the lack of statistical techniques implementation, integrating demand uncertainty in a unique model built in stages by implementing ARIMA forecasting, queuing theory, and Monte Carlo simulation to optimize the service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Our model has proved to be a useful tool for optimal decision making under uncertainty integrating the prediction of the cost implicit in the reserve capacity to serve unexpected demand and defining a set of new process indicators, such us capacity, occupancy, and cost of capacity reserve never studied before. The new indicators are intended to optimize the service operation. This set of new indicators could be implemented in the information systems used in the passenger car services.

Service capacity reserve under uncertainty by hospital's ER's analogies: a practical model for car services

El objetivo de esta investigación consiste en definir un modelo de reserva de capacidad, por analogías con emergencias hospitalarias, que pueda ser implementado en el sector de servicios. Este está específicamente enfocado a su aplicación en talleres de servicio de automóviles. Nuestra investigación incorpora la incertidumbre de la demanda en un modelo singular diseñado en etapas que agrupa técnicas ARIMA, teoría de colas y simulación Monte Carlo para definir los conceptos de capacidad y ocupación de servicio, que serán utilizados para minimizar el coste implícito de la reserva capacidad necesaria para atender a clientes que carecen de cita previa. Habitualmente, las compañías automovilísticas estiman la capacidad de sus instalaciones de servicio empíricamente, pero los clientes pueden llegar bajo condiciones de incertidumbre que no se tienen en cuenta en dichas estimaciones, por lo que existe una diferencia entre lo que el cliente realmente demanda y la capacidad que ofrece el servicio. Nuestro enfoque define una metodología válida para el sector automovilístico que cubre la ausencia genérica de investigaciones recientes y la habitual falta de aplicación de técnicas estadísticas en el sector. La equivalencia con la gestión de urgencias hospitalarias se ha validado a lo largo de la investigación en la se definen nuevos indicadores de proceso (KPIs) Tal y como hacen los hospitales, aplicamos modelos estocásticos para dimensionar las instalaciones de servicio de acuerdo con la distribución demográfica del área de influencia. El modelo final propuesto integra la predicción del coste implícito en la reserva de capacidad para atender la demanda no prevista. Asimismo, se ha desarrollado un código en Matlab que puede integrarse como un módulo adicional a los sistemas de información (DMS) que se usan actualmente en el sector, con el fin de emplear los nuevos indicadores de proceso definidos en el modelo. Los resultados principales del modelo son nuevos indicadores de servicio, tales como la capacidad, ocupación y coste de reserva de capacidad, que nunca antes han sido objeto de estudio en la industria automovilística, y que están orientados a gestionar la operativa del servicio. ABSTRACT Our aim is to define a Capacity Reserve model to be implemented in the service sector by hospital's emergency room (ER) analogies, with a practical approach to passenger car services. A stochastic model has been implemented using R and a Monte Carlo simulation code written in Matlab and has proved a very useful tool for optimal decision making under uncertainty. The research integrates demand uncertainty in a unique model which is built in stages by implementing ARIMA forecasting, Queuing Theory and a Monte Carlo simulation to define the concepts of service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Usually, passenger car companies estimate their service facilities capacity using empirical methods, but customers arrive under uncertain conditions not included in the estimations. Thus, there is a gap between customer’s real demand and the dealer’s capacity. This research sets a valid methodology for the passenger car industry to cover the generic absence of recent researches and the generic lack of statistical techniques implementation. The hospital’s emergency room (ER) equalization has been confirmed to be valid for the passenger car industry and new process indicators have been defined to support the study. As hospitals do, we aim to apply stochastic models to dimension installations according to the demographic distribution of the area to be serviced. The proposed model integrates the prediction of the cost implicit in the reserve capacity to serve unexpected demand. The Matlab code could be implemented as part of the existing information technology systems (ITs) to support the existing service management tools, creating a set of new process indicators. Main model outputs are new indicators, such us Capacity, Occupancy and Cost of Capacity Reserve, never studied in the passenger car service industry before, and intended to manage the service operation.

Contributions to uncertainty reduction in the estimation of PV plants performance

Esta tesis doctoral presenta un procedimiento integral de control de calidad en centrales fotovoltaicas, que comprende desde la fase inicial de estimación de las expectativas de producción hasta la vigilancia del funcionamiento de la instalación una vez en operación, y que permite reducir la incertidumbre asociada su comportamiento y aumentar su fiabilidad a largo plazo, optimizando su funcionamiento. La coyuntura de la tecnología fotovoltaica ha evolucionado enormemente en los últimos años, haciendo que las centrales fotovoltaicas sean capaces de producir energía a unos precios totalmente competitivos en relación con otras fuentes de energía. Esto hace que aumente la exigencia sobre el funcionamiento y la fiabilidad de estas instalaciones. Para cumplir con dicha exigencia, es necesaria la adecuación de los procedimientos de control de calidad aplicados, así como el desarrollo de nuevos métodos que deriven en un conocimiento más completo del estado de las centrales, y que permitan mantener la vigilancia sobre las mismas a lo largo del tiempo. Además, los ajustados márgenes de explotación actuales requieren que durante la fase de diseño se disponga de métodos de estimación de la producción que comporten la menor incertidumbre posible. La propuesta de control de calidad presentada en este trabajo parte de protocolos anteriores orientados a la fase de puesta en marcha de una instalación fotovoltaica, y las complementa con métodos aplicables a la fase de operación, prestando especial atención a los principales problemas que aparecen en las centrales a lo largo de su vida útil (puntos calientes, impacto de la suciedad, envejecimiento…). Además, incorpora un protocolo de vigilancia y análisis del funcionamiento de las instalaciones a partir de sus datos de monitorización, que incluye desde la comprobación de la validez de los propios datos registrados hasta la detección y el diagnóstico de fallos, y que permite un conocimiento automatizado y detallado de las plantas. Dicho procedimiento está orientado a facilitar las tareas de operación y mantenimiento, de manera que se garantice una alta disponibilidad de funcionamiento de la instalación. De vuelta a la fase inicial de cálculo de las expectativas de producción, se utilizan los datos registrados en las centrales para llevar a cabo una mejora de los métodos de estimación de la radiación, que es la componente que más incertidumbre añade al proceso de modelado. El desarrollo y la aplicación de este procedimiento de control de calidad se han llevado a cabo en 39 grandes centrales fotovoltaicas, que totalizan una potencia de 250 MW, distribuidas por varios países de Europa y América Latina. ABSTRACT This thesis presents a comprehensive quality control procedure to be applied in photovoltaic plants, which covers from the initial phase of energy production estimation to the monitoring of the installation performance, once it is in operation. This protocol allows reducing the uncertainty associated to the photovoltaic plants behaviour and increases their long term reliability, therefore optimizing their performance. The situation of photovoltaic technology has drastically evolved in recent years, making photovoltaic plants capable of producing energy at fully competitive prices, in relation to other energy sources. This fact increases the requirements on the performance and reliability of these facilities. To meet this demand, it is necessary to adapt the quality control procedures and to develop new methods able to provide a more complete knowledge of the state of health of the plants, and able to maintain surveillance on them over time. In addition, the current meagre margins in which these installations operate require procedures capable of estimating energy production with the lower possible uncertainty during the design phase. The quality control procedure presented in this work starts from previous protocols oriented to the commissioning phase of a photovoltaic system, and complete them with procedures for the operation phase, paying particular attention to the major problems that arise in photovoltaic plants during their lifetime (hot spots, dust impact, ageing...). It also incorporates a protocol to control and analyse the installation performance directly from its monitoring data, which comprises from checking the validity of the recorded data itself to the detection and diagnosis of failures, and which allows an automated and detailed knowledge of the PV plant performance that can be oriented to facilitate the operation and maintenance of the installation, so as to ensure a high operation availability of the system. Back to the initial stage of calculating production expectations, the data recorded in the photovoltaic plants is used to improved methods for estimating the incident irradiation, which is the component that adds more uncertainty to the modelling process. The development and implementation of the presented quality control procedure has been carried out in 39 large photovoltaic plants, with a total power of 250 MW, located in different European and Latin-American countries.

A methodology to estimate uncertainty for emission projections through sensitivity analysis

Air pollution abatement policies must be based on quantitative information on current and future emissions of pollutants. As emission projections uncertainties are inevitable and traditional statistical treatments of uncertainty are highly time/resources consuming, a simplified methodology for nonstatistical uncertainty estimation based on sensitivity analysis is presented in this work. The methodology was applied to the “with measures” scenario for Spain, concretely over the 12 highest emitting sectors regarding greenhouse gas and air pollutants emissions. Examples of methodology application for two important sectors (power plants, and agriculture and livestock) are shown and explained in depth. Uncertainty bands were obtained up to 2020 by modifying the driving factors of the 12 selected sectors and the methodology was tested against a recomputed emission trend in a low economic-growth perspective and official figures for 2010, showing a very good performance. Implications: A solid understanding and quantification of uncertainties related to atmospheric emission inventories and projections provide useful information for policy negotiations. However, as many of those uncertainties are irreducible, there is an interest on how they could be managed in order to derive robust policy conclusions. Taking this into account, a method developed to use sensitivity analysis as a source of information to derive nonstatistical uncertainty bands for emission projections is presented and applied to Spain. This method simplifies uncertainty assessment and allows other countries to take advantage of their sensitivity analyses.

What role does climate change play in agricultural market uncertainty? An integrated assessment taking into account market-driven adjustments

Recent studies point to climate change being one of the long-term drivers of agricultural market uncertainty. To advance in the understanding of the influence of climate change on future agricultural market developments, we compare a reference scenario for 2030 with alternative simulation scenarios that differ regarding: (1) emission scenarios; (2) climate projections; and (3) the consideration of carbon fertilization effects. For each simulation scenario, the CAPRI model provides global and EU-wide impacts of climate change on agricultural markets. Results show that climate change would considerably affect agrifood markets up to 2030. Nevertheless, market-driven adaptation strategies (production intensification, trade adjustments) would soften the impact of yield shocks on supply and demand. As a result, regional changes in production would be lower than foreseen by other studies focused on supply effects.

Uncertainty in Structural Interpretation : Lessons to be learnt

Peer reviewed

Resolving taxonomic uncertainty in vulnerable elasmobranchs : are the Madeira skate (Raja maderensis) and the thornback ray (Raja clavata) distinct species?

We are grateful to all those who helped with sample collection. This includes the MEDITS survey programme (IEO Mallorca) for Mediterranean samples. Portugal mainland samples were collected under the EU Data Collection Framework (DCF, PNAB). Azores specimens from the Department of Oceanography and Fisheries (DOP) of the University of the Azores (UAc) were collected under the project DEMERSAIS “Monitorização das espécies demersais dos Açores” financed by the Azorean government, and the project DEECON “Unravelling population connectivity for sustainable fisheries in the Deep Sea” project approved by the European Science Foundation (ESF) under the EUROCORES programme (proposal No 06-EuroDEEP-FP-008 & SFRH-EuroDEEP/0002/2007). This study was funded by the UK Natural Environment Research Council (NERC) Oceans 2025 Strategic Research Programme Theme 6 (Science for Sustainable Marine Resources). REB was supported by the Fisheries Society of the British Isles (FSBI), BSP was funded by the Fundação para a Ciência e a Tecnologia, SFRH/BPD/72351/2010 and JL was supported by The Alasdair Downes Marine Conservation Fund.

Prominin, a novel microvilli-specific polytopic membrane protein of the apical surface of epithelial cells, is targeted to plasmalemmal protrusions of non-epithelial cells

Using a new mAb raised against the mouse neuroepithelium, we have identified and cDNA-cloned prominin, an 858-amino acid-containing, 115-kDa glycoprotein. Prominin is a novel plasma membrane protein with an N-terminal extracellular domain, five transmembrane segments flanking two short cytoplasmic loops and two large glycosylated extracellular domains, and a cytoplasmic C-terminal domain. DNA sequences from Caenorhabditis elegans predict the existence of a protein with the same features, suggesting that prominin is conserved between vertebrates and invertebrates. Prominin is found not only in the neuroepithelium but also in various other epithelia of the mouse embryo. In the adult mouse, prominin has been detected in the brain ependymal layer, and in kidney tubules. In these epithelia, prominin is specific to the apical surface, where it is selectively associated with microvilli and microvilli-related structures. Remarkably, upon expression in CHO cells, prominin is preferentially localized to plasma membrane protrusions such as filopodia, lamellipodia, and microspikes. These observations imply that prominin contains information to be targeted to, and/or retained in, plasma membrane protrusions rather than the planar cell surface. Moreover, our results show that the mechanisms underlying targeting of membrane proteins to microvilli of epithelial cells and to plasma membrane protrusions of non-epithelial cells are highly related.

Dissection of De Novo Membrane Insertion Activities of Internal Transmembrane Segments of ATP-Binding-Cassette Transporters: Toward Understanding Topological Rules for Membrane Assembly of Polytopic Membrane Proteins

The membrane assembly of polytopic membrane proteins is a complicated process. Using Chinese hamster P-glycoprotein (Pgp) as a model protein, we investigated this process previously and found that Pgp expresses more than one topology. One of the variations occurs at the transmembrane (TM) domain including TM3 and TM4: TM4 inserts into membranes in an Nin-Cout rather than the predicted Nout-Cin orientation, and TM3 is in cytoplasm rather than the predicted Nin-Cout orientation in the membrane. It is possible that TM4 has a strong activity to initiate the Nin-Cout membrane insertion, leaving TM3 out of the membrane. Here, we tested this hypothesis by expressing TM3 and TM4 in isolated conditions. Our results show that TM3 of Pgp does not have de novo Nin-Cout membrane insertion activity whereas TM4 initiates the Nin-Cout membrane insertion regardless of the presence of TM3. In contrast, TM3 and TM4 of another polytopic membrane protein, cystic fibrosis transmembrane conductance regulator (CFTR), have a similar level of de novo Nin-Cout membrane insertion activity and TM4 of CFTR functions only as a stop-transfer sequence in the presence of TM3. Based on these findings, we propose that 1) the membrane insertion of TM3 and TM4 of Pgp does not follow the sequential model, which predicts that TM3 initiates Nin-Cout membrane insertion whereas TM4 stops the insertion event; and 2) “leaving one TM segment out of the membrane” may be an important folding mechanism for polytopic membrane proteins, and it is regulated by the Nin-Cout membrane insertion activities of the TM segments.

Folding and activity of circularly permuted forms of a polytopic membrane protein

The transmembrane subunit of the Glc transporter (IICBGlc), which mediates uptake and concomitant phosphorylation of glucose, spans the membrane eight times. Variants of IICBGlc with the native N and C termini joined and new N and C termini in the periplasmic and cytoplasmic surface loops were expressed in Escherichia coli. In vivo transport/in vitro phosphotransferase activities of the circularly permuted variants with the termini in the periplasmic loops 1 to 4 were 35/58, 32/37, 0/3, and 0/0% of wild type, respectively. The activities of the variants with the termini in the cytoplasmic loops 1 to 3 were 0/25, 0/4 and 24/70, respectively. Fusion of alkaline phosphatase to the periplasmic C termini stabilized membrane integration and increased uptake and/or phosphorylation activities. These results suggest that internal signal anchor and stop transfer sequences can function as N-terminal signal sequences in a circularly permuted α-helical bundle protein and that the orientation of transmembrane segments is determined by the amino acid sequence and not by the sequential appearance during translation. Of the four IICBGlc variants with new termini in periplasmic loops, only the one with the discontinuity in loop 4 is inactive. The sequences of loop 4 and of the adjacent TM7 and TM8 are conserved in all phosphoenolpyruvate-dependent carbohydrate:phosphotransferase system transporters of the glucose family.

Governance and Uncertainty

Government actors create law against a backdrop of uncertainty. Limited information, unpredictable events, and lack of understanding interfere with accurately predicting a legal regime’s costs, benefits, and effects on other legal and social programs and institutions. Does the availability of no-fault divorce increase the number of terminated marriages? Will bulk-collection of telecommunications information about American citizens reveal terrorist plots? Can a sensitive species breed in the presence of oil and gas wells? The answers to these questions are far from clear, but lawmakers must act nonetheless. The problems posed by uncertainty cut across legal fields. Scholars and regulators in a variety of contexts recognize the importance of uncertainty, but no systematic, generally-applicable framework exists for determining how law should account for gaps in information. This Article suggests such a framework and develops a novel typology of strategies for accounting for uncertainty in governance. This typology includes “static law,” as well as three varieties of “dynamic law.” “Static law” is a legal rule initially intended to last in perpetuity. “Dynamic law” is intended to change, and includes: (1) durational regulation, or fixed legal rules with periodic opportunities for amendment or repeal; (2) adaptive regulation, or malleable legal rules with procedural mechanisms allowing rules to change; and (3) contingent regulation, or malleable legal rules with triggering mechanisms to substantively change to the rules. Each of these strategies, alone or in combination, may best address the uncertainty inherent in a particular lawmaking effort. This Article provides a diagnostic framework that lawmakers can use to identify optimal strategies. Ultimately, this approach to uncertainty yields immediate practical benefits by enabling lawmakers to better structure governance.

Robust linear semi-infinite programming duality under uncertainty

In this paper, we propose a duality theory for semi-infinite linear programming problems under uncertainty in the constraint functions, the objective function, or both, within the framework of robust optimization. We present robust duality by establishing strong duality between the robust counterpart of an uncertain semi-infinite linear program and the optimistic counterpart of its uncertain Lagrangian dual. We show that robust duality holds whenever a robust moment cone is closed and convex. We then establish that the closed-convex robust moment cone condition in the case of constraint-wise uncertainty is in fact necessary and sufficient for robust duality. In other words, the robust moment cone is closed and convex if and only if robust duality holds for every linear objective function of the program. In the case of uncertain problems with affinely parameterized data uncertainty, we establish that robust duality is easily satisfied under a Slater type constraint qualification. Consequently, we derive robust forms of the Farkas lemma for systems of uncertain semi-infinite linear inequalities.

Multi-objective optimization of environmentally conscious chemical supply chains under demand uncertainty

In this work, we analyze the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.