Optimal management of microgrids

Desenvolupament dels models matemàtics necessaris per a controlar de forma òptima la microxarxa existent als laboratoris del Institut de Recerca en Energia de Catalunya. Els algoritmes s'implementaran per tal de simular el comportament i posteriorment es programaran directament sobre els elements de la microxarxa per verificar el seu correcte funcionament.. Desenvolupament dels models matemàtics necessaris per a controlar de forma òptima la microxarxa existent als laboratoris del Institut de Recerca en Energia de Catalunya. Els algoritmes s'implementaran per tal de simular el comportament i posteriorment es programaran directament sobre els elements de la microxarxa per verificar el seu correcte funcionament.

Plataforma automatizada de detección de malware

Es descriu el disseny i posterior implementació de la nova plataforma d’automatització del servei ofert per Internet Security Auditors, S.L. destinada a l’anàlisi de dominis d’Internet amb la finalitat de detectar possibles infeccions que afectin a usuaris de la web. El sistema actual conté algunes deficiències, de manera que aquest text presenta una nova versió, la qual aporta millores molt significatives com ara una gestió més òptima, o un disseny renovat i escalable de la informació i els diferents processos. Així mateix es dota al sistema d’un control d’errors centralitzat, amb enviament d’alàrmes en temps real, i una agrupació i centralització dels resultats.

The COPD control panel: towards personalised medicine in COPD

Background Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease whose assessment and management have traditionally been based on the severity of airflow limitation (forced expiratory volume in 1 s (FEV1)). Yet, it is now clear that FEV1 alone cannot describe the complexity of the disease. In fact, the recently released Global Initiative for Chronic Obstructive Lung Disease (GOLD), 2011 revision has proposed a new combined assessment method using three variables (symptoms, airflow limitation and exacerbations). Methods Here, we go one step further and propose that in the near future physicians will need a"control panel" for the assessment and optimal management of individual patients with complex diseases, including COPD, that provides a path towards personalised medicine. Results We propose that such a"COPD control panel" should include at least three different domains of the disease: severity, activity and impact. Each of these domains presents information on different"elements" of the disease with potential prognostic value and/or with specific therapeutic requirements. All this information can be easily incorporated into an"app" for daily use in clinical practice. Conclusion We recognise that this preliminary proposal needs debate, validation and evolution (eg, including"omics" and molecular imaging information in the future), but we hope that it may stimulate debate and research in the field.

Blood pressure levels and haematoma growth in patients with Intracerebral Haemorrhage (ICH) A retrospective observational study

Intracerebral haemorrhage (ICH) is a spontaneous extravasation of blood into brain parenchyma. Although ICH represents approximately only 15% of all strokes, it is one of the major causes of stroke-related death and disability. One of the causes of poor outcome is the haematoma growth. The association between elevated blood pressure (BP) and haematoma enlargement in acute ICH has not been clarified. Our objective is to try to identify this relationship that may suggest an immediate target for intervention to possibly improve outcomes in patients with spontaneous ICH and might settle the controversy surrounding the optimal management of blood pressure.We propose a retrospective revision using a sample present in our database of approximately 250 patients with primary ICH and less than 12h from symptoms onset. Systolic blood pressure levels (SBP) are assessed at baseline, at 6h, at 12h, at 24h and at 72h, being these last four the average levels of the different recordings during those time intervals. Haematoma growth will be defined as an increase in the volume of intraparenchymal haemorrhage of >33% as measured by image analysis on the 24-hour CT or 72-hour CT compared with the baseline CT scan. A qualified neuroradiologist not informed of the aim of the study, will review the CT images. The secondary objective will be to correlate the BP levels in the acute phase of ICH with clinical outcome. We will evaluate early neurologic deterioration at 72h by using the National Institutes of Health Stroke Scale (NIHSS); outcome at 90 days by using the modified Rankin scale and mortality at 72h and 90 days. The statistical analysis will be adjusted by possibly confounding variables

Cooperative Transmission and Radio Resources Management for Wireless Networks

Report for the scientific sojourn at the Multimedia Communications Laboratory, University of Texas at Dallas, USA, from September to December 2005. The cooperative transmission has been analyzed taking a broadcast relay channel which assumes a scenario with one source and multiple destinations. Moreover, in order to improve the performance in terms of mutual information, it has been considered that for each destination there is another nearby terminal (called relay) which will help to improve the performance of the destination. This scheme combines different types of channels considered in the information theory, such as the relay channel, broadcast channel and interference channel (if the relays transmit information intended only to its associated destination). In this work, the author has studied the optimal way to encode the signals for the different users, known as capacity region (i.e. related to radio resources management ), of the broadcast relay channel.

Fiscal insurance and debt management in OECD economies

Assuming the role of debt management is to provide hedging against fiscal shocks we consider three questions: i) what indicators can be used to assess the performance of debt management? ii) how well have historical debt management policies performed? and iii) how is that performance affected by variations in debt issuance? We consider these questions using OECD data on the market value of government debt between 1970 and 2000. Motivated by both the optimal taxation literature and broad considerations of debt stability we propose a range of performance indicators for debt management. We evaluate these using Monte Carlo analysis and find that those based on the relative persistence of debt perform best. Calculating these measures for OECD data provides only limited evidence that debt management has helped insulate policy against unexpected fiscal shocks. We also find that the degree of fiscal insurance achieved is not well connected to cross country variations in debt issuance patterns. Given the limited volatility observed in the yield curve the relatively small dispersion of debt management practices across countries makes little difference to the realised degree of fiscal insurance.

In Search of a theory of debt management

A growing literature integrates theories of debt management into models of optimal fiscal policy. One promising theory argues that the composition of government debt should be chosen so that fluctuations in the market value of debt offset changes in expected future deficits. This complete market approach to debt management is valid even when the government only issues non-contingent bonds. A number of authors conclude from this approach that governments should issue long term debt and invest in short term assets. We argue that the conclusions of this approach are too fragile to serve as a basis for policy recommendations. This is because bonds at different maturities have highly correlated returns, causing the determination of the optimal portfolio to be ill-conditioned. To make this point concrete we examine the implications of this approach to debt management in various models, both analytically and using numerical methods calibrated to the US economy. We find the complete market approach recommends asset positions which are huge multiples of GDP. Introducing persistent shocks or capital accumulation only worsens this problem. Increasing the volatility of interest rates through habits partly reduces the size of these simulations we find no presumption that governments should issue long term debt ? policy recommendations can be easily reversed through small perturbations in the specification of shocks or small variations in the maturity of bonds issued. We further extend the literature by removing the assumption that governments every period costlessly repurchase all outstanding debt. This exacerbates the size of the required positions, worsens their volatility and in some cases produces instability in debt holdings. We conclude that it is very difficult to insulate fiscal policy from shocks by using the complete markets approach to debt management. Given the limited variability of the yield curve using maturities is a poor way to substitute for state contingent debt. The result is the positions recommended by this approach conflict with a number of features that we believe are important in making bond markets incomplete e.g allowing for transaction costs, liquidity effects, etc.. Until these features are all fully incorporated we remain in search of a theory of debt management capable of providing robust policy insights.

Enhancing fault management performance of two-step QoS routing algorithms in GMPLS networks

In this paper a novel methodology aimed at minimizing the probability of network failure and the failure impact (in terms of QoS degradation) while optimizing the resource consumption is introduced. A detailed study of MPLS recovery techniques and their GMPLS extensions are also presented. In this scenario, some features for reducing the failure impact and offering minimum failure probabilities at the same time are also analyzed. Novel two-step routing algorithms using this methodology are proposed. Results show that these methods offer high protection levels with optimal resource consumption

On optimal computation of MPLS label binding for multipoint-to-point connections

Most network operators have considered reducing Label Switched Routers (LSR) label spaces (i.e. the number of labels that can be used) as a means of simplifying management of underlaying Virtual Private Networks (VPNs) and, hence, reducing operational expenditure (OPEX). This letter discusses the problem of reducing the label spaces in Multiprotocol Label Switched (MPLS) networks using label merging - better known as MultiPoint-to-Point (MP2P) connections. Because of its origins in IP, MP2P connections have been considered to have tree- shapes with Label Switched Paths (LSP) as branches. Due to this fact, previous works by many authors affirm that the problem of minimizing the label space using MP2P in MPLS - the Merging Problem - cannot be solved optimally with a polynomial algorithm (NP-complete), since it involves a hard- decision problem. However, in this letter, the Merging Problem is analyzed, from the perspective of MPLS, and it is deduced that tree-shapes in MP2P connections are irrelevant. By overriding this tree-shape consideration, it is possible to perform label merging in polynomial time. Based on how MPLS signaling works, this letter proposes an algorithm to compute the minimum number of labels using label merging: the Full Label Merging algorithm. As conclusion, we reclassify the Merging Problem as Polynomial-solvable, instead of NP-complete. In addition, simulation experiments confirm that without the tree-branch selection problem, more labels can be reduced

Stochastic optimal bid to electricity markets with environmental risk constraints

There are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) in the current energy market framework. Environmental policy issues have become more and more important for fossil-fuelled power plants and they have to be considered in their management, giving rise to emission limitations. This work allows to investigate the influence of both the allowances and emission reduction plan, and the incorporation of the derivatives medium-term commitments in the optimal generation bidding strategy to the day-ahead electricity market. Two different technologies have been considered: the coal thermal units, high-emission technology, and the combined cycle gas turbine units, low-emission technology. The Iberian Electricity Market and the Spanish National Emissions and Allocation Plans are the framework to deal with the environmental issues in the day-ahead market bidding strategies. To address emission limitations, some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), have been extended. This study offers to electricity generation utilities a mathematical model to determinate the individual optimal generation bid to the wholesale electricity market, for each one of their generation units that maximizes the long-run profits of the utility abiding by the Iberian Electricity Market rules, the environmental restrictions set by the EU Emission Trading Scheme, as well as the restrictions set by the Spanish National Emissions Reduction Plan. The economic implications for a GenCo of including the environmental restrictions of these National Plans are analyzed and the most remarkable results will be presented.

Network revenue management with product-specific no-shows

Revenue management practices often include overbooking capacity to account for customerswho make reservations but do not show up. In this paper, we consider the network revenuemanagement problem with no-shows and overbooking, where the show-up probabilities are specificto each product. No-show rates differ significantly by product (for instance, each itinerary andfare combination for an airline) as sale restrictions and the demand characteristics vary byproduct. However, models that consider no-show rates by each individual product are difficultto handle as the state-space in dynamic programming formulations (or the variable space inapproximations) increases significantly. In this paper, we propose a randomized linear program tojointly make the capacity control and overbooking decisions with product-specific no-shows. Weestablish that our formulation gives an upper bound on the optimal expected total profit andour upper bound is tighter than a deterministic linear programming upper bound that appearsin the existing literature. Furthermore, we show that our upper bound is asymptotically tightin a regime where the leg capacities and the expected demand is scaled linearly with the samerate. We also describe how the randomized linear program can be used to obtain a bid price controlpolicy. Computational experiments indicate that our approach is quite fast, able to scale to industrialproblems and can provide significant improvements over standard benchmarks.

Beyond Smith's rule: An optimal dynamic index, rule for single machine stochastic scheduling with convex holding costs

Most research on single machine scheduling has assumedthe linearity of job holding costs, which is arguablynot appropriate in some applications. This motivates ourstudy of a model for scheduling $n$ classes of stochasticjobs on a single machine, with the objective of minimizingthe total expected holding cost (discounted or undiscounted). We allow general holding cost rates that are separable,nondecreasing and convex on the number of jobs in eachclass. We formulate the problem as a linear program overa certain greedoid polytope, and establish that it issolved optimally by a dynamic (priority) index rule,whichextends the classical Smith's rule (1956) for the linearcase. Unlike Smith's indices, defined for each class, ournew indices are defined for each extended class, consistingof a class and a number of jobs in that class, and yieldan optimal dynamic index rule: work at each time on a jobwhose current extended class has larger index. We furthershow that the indices possess a decomposition property,as they are computed separately for each class, andinterpret them in economic terms as marginal expected cost rate reductions per unit of expected processing time.We establish the results by deploying a methodology recentlyintroduced by us [J. Niño-Mora (1999). "Restless bandits,partial conservation laws, and indexability. "Forthcomingin Advances in Applied Probability Vol. 33 No. 1, 2001],based on the satisfaction by performance measures of partialconservation laws (PCL) (which extend the generalizedconservation laws of Bertsimas and Niño-Mora (1996)):PCL provide a polyhedral framework for establishing theoptimality of index policies with special structure inscheduling problems under admissible objectives, which weapply to the model of concern.

When to carry eccentric products? Optimal retail assortment under consumer returns

To understand whether retailers should consider consumer returns when merchandising, we study howthe optimal assortment of a price-taking retailer is influenced by its return policy. The retailer selects itsassortment from an exogenous set of horizontally differentiated products. Consumers make purchase andkeep/return decisions in nested multinomial logit fashion. Our main finding is that the optimal assortmenthas a counterintuitive structure for relatively strict return policies: It is optimal to offer a mix of the mostpopular and most eccentric products when the refund amount is sufficiently low, which can be viewed asa form of risk sharing between the retailer and consumers. In contrast, if the refund is sufficiently high, orwhen returns are disallowed, optimal assortment is composed of only the most popular products (a commonfinding in the literature). We provide preliminary empirical evidence for one of the key drivers of our results:more eccentric products have higher probability of return conditional on purchase. In light of our analyticalfindings and managerial insights, we conclude that retailers should take their return policies into accountwhen merchandising.

Revenue management under general discrete choice model of consumer behavior

Customer choice behavior, such as 'buy-up' and 'buy-down', is an importantphe-nomenon in a wide range of industries. Yet there are few models ormethodologies available to exploit this phenomenon within yield managementsystems. We make some progress on filling this void. Specifically, wedevelop a model of yield management in which the buyers' behavior ismodeled explicitly using a multi-nomial logit model of demand. Thecontrol problem is to decide which subset of fare classes to offer ateach point in time. The set of open fare classes then affects the purchaseprobabilities for each class. We formulate a dynamic program todetermine the optimal control policy and show that it reduces to a dynamicnested allocation policy. Thus, the optimal choice-based policy caneasily be implemented in reservation systems that use nested allocationcontrols. We also develop an estimation procedure for our model based onthe expectation-maximization (EM) method that jointly estimates arrivalrates and choice model parameters when no-purchase outcomes areunobservable. Numerical results show that this combined optimization-estimation approach may significantly improve revenue performancerelative to traditional leg-based models that do not account for choicebehavior.

Optimal law enforcement and criminal organization

In this paper, we take an organizational view of organized crime. In particular, we study the organizational consequences of product illegality attending at the following characteristics: (i) contracts are not enforceable in court, (ii) all participants are subject to the risk of being punished, (iii) employees present a major threat to the entrepreneur having the most detailed knowledge concerning participation, (iv) separation between ownership and management is difficult because record-keeping and auditing augments criminal evidence.