A Multiple Criteria Utility-based Approa h for the Unit Commitment with Wind Power and Pumped Storage Hydro

The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.

Responsibility and Cross-Subsidization in Cost Sharing

We propose two axiomatic theories of cost sharing with the common premise that agents demand comparable -though perhaps different- commodities and are responsible for their own demand. Under partial responsibility the agents are not responsible for the asymmetries of the cost function: two agents consuming the same amount of output always pay the same price; this holds true under full responsibility only if the cost function is symmetric in all individual demands. If the cost function is additively separable, each agent pays her stand alone cost under full responsibility; this holds true under partial responsibility only if, in addition, the cost function is symmetric. By generalizing Moulin and Shenker’s (1999) Distributivity axiom to cost-sharing methods for heterogeneous goods, we identify in each of our two theories a different serial method. The subsidy-free serial method (Moulin, 1995) is essentially the only distributive method meeting Ranking and Dummy. The cross-subsidizing serial method (Sprumont, 1998) is the only distributive method satisfying Separability and Strong Ranking. Finally, we propose an alternative characterization of the latter method based on a strengthening of Distributivity.

Méthode pour l’établissement d’une liste de médicaments remboursables dans le cadre du nouveau programme d’assurance-médicaments en Côte d’Ivoire

Contexte général La Côte d'Ivoire est un pays de l’Afrique de l’Ouest qui a décidé, depuis 2001, d'étendre la couverture des prestations de santé à toute sa population. En effet, cette réforme du système de santé avait pour but de fournir, à chaque ivoirien, une couverture médicale et pharmaceutique. Toutefois, la mise en œuvre de cette réforme était difficile car, contrairement aux pays développés, les pays en développement ont un secteur « informel » échappant à la législation du travail et occupant une place importante. En conséquence, il a été recommandé qu’il y ait deux caisses d'assurance santé, une pour le secteur formel (fonctionnaires) et l'autre pour le secteur informel. Ces caisses auraient légitimité en ce qui a trait aux décisions de remboursement de médicaments. D’ores-et-déjà, il existe une mutuelle de santé appelée la Mutuelle Générale des Fonctionnaires et Agents de l'État de Côte d'Ivoire (MUGEFCI), chargée de couvrir les frais médicaux et pharmaceutiques des fonctionnaires et agents de l’Etat. Celle-ci connaît, depuis quelques années, des contraintes budgétaires. De plus, le processus actuel de remboursement des médicaments, dans cette organisation, ne prend pas en considération les valeurs implicites liées aux critères d'inscription au formulaire. Pour toutes ces raisons, la MUGEFCI souhaite se doter d’une nouvelle liste de médicaments remboursables, qui comprendrait des médicaments sécuritaires avec un impact majeur sur la santé (service médical rendu), à un coût raisonnable. Dans le cadre de cette recherche, nous avons développé une méthode de sélection des médicaments pour des fins de remboursement, dans un contexte de pays à faibles revenus. Cette approche a ensuite été appliquée dans le cadre de l’élaboration d’une nouvelle liste de médicaments remboursables pour la MUGEFCI. Méthode La méthode de sélection des médicaments remboursables, développée dans le cadre de cette recherche, est basée sur l'Analyse de Décision Multicritère (ADM). Elle s’articule autour de quatre étapes: (1) l'identification et la pondération des critères pertinents d'inscription des médicaments au formulaire (combinant revue de la littérature et recherche qualitative, suivies par la réalisation d’une expérience de choix discrets); (2) la détermination d'un ensemble de traitements qui sont éligibles à un remboursement prioritaire; (3) l’attribution de scores aux traitements selon leurs performances sur les niveaux de variation de chaque critère, et (4) le classement des traitements par ordre de priorité de remboursement (classement des traitements selon un score global, obtenu après avoir additionné les scores pondérés des traitements). Après avoir défini la liste des médicaments remboursables en priorité, une analyse d’impact budgétaire a été réalisée. Celle-ci a été effectuée afin de déterminer le coût par patient lié à l'utilisation des médicaments figurant sur la liste, selon la perspective de la MUGEFCI. L’horizon temporel était de 1 an et l'analyse portait sur tous les traitements admissibles à un remboursement prioritaire par la MUGEFCI. En ce qui concerne la population cible, elle était composée de personnes assurées par la MUGEFCI et ayant un diagnostic positif de maladie prioritaire en 2008. Les coûts considérés incluaient ceux des consultations médicales, des tests de laboratoire et des médicaments. Le coût par patient, résultant de l'utilisation des médicaments figurant sur la liste, a ensuite été comparé à la part des dépenses par habitant (per capita) allouée à la santé en Côte d’Ivoire. Cette comparaison a été effectuée pour déterminer un seuil en deçà duquel la nouvelle liste des médicaments remboursables en priorité était abordable pour la MUGEFCI. Résultats Selon les résultats de l’expérience de choix discrets, réalisée auprès de professionnels de la santé en Côte d'Ivoire, le rapport coût-efficacité et la sévérité de la maladie sont les critères les plus importants pour le remboursement prioritaire des médicaments. Cela se traduit par une préférence générale pour les antipaludiques, les traitements pour l'asthme et les antibiotiques indiqués pour les infections urinaires. En outre, les résultats de l’analyse d’impact budgétaire suggèrent que le coût par patient lié à l'utilisation des médicaments figurant sur la liste varierait entre 40 et 160 dollars américains. Etant donné que la part des dépenses par habitant allouées à la santé en Côte d’Ivoire est de 66 dollars américains, l’on pourrait conclure que la nouvelle liste de médicaments remboursables serait abordable lorsque l'impact économique réel de l’utilisation des médicaments par patient est en deçà de ces 66 dollars américains. Au delà de ce seuil, la MUGEFCI devra sélectionner les médicaments remboursables en fonction de leur rang ainsi que le coût par patient associé à l’utilisation des médicaments. Plus précisément, cette sélection commencera à partir des traitements dans le haut de la liste de médicaments prioritaires et prendra fin lorsque les 66 dollars américains seront épuisés. Conclusion Cette étude fait la démonstration de ce qu’il est possible d'utiliser l’analyse de décision multicritère pour développer un formulaire pour les pays à faibles revenus, la Côte d’Ivoire en l’occurrence. L'application de cette méthode est un pas en avant vers la transparence dans l'élaboration des politiques de santé dans les pays en développement.

Approches générales de résolution pour les problèmes multi-attributs de tournées de véhicules et confection d'horaires

Thèse réalisée en cotutelle entre l'Université de Montréal et l'Université de Technologie de Troyes

Visibility and proximity on triangulated surfaces

En aquesta tesi es solucionen problemes de visibilitat i proximitat sobre superfícies triangulades considerant elements generalitzats. Com a elements generalitzats considerem: punts, segments, poligonals i polígons. Les estrategies que proposem utilitzen algoritmes de geometria computacional i hardware gràfic. Comencem tractant els problemes de visibilitat sobre models de terrenys triangulats considerant un conjunt d'elements de visió generalitzats. Es presenten dos mètodes per obtenir, de forma aproximada, mapes de multi-visibilitat. Un mapa de multi-visibilitat és la subdivisió del domini del terreny que codifica la visibilitat d'acord amb diferents criteris. El primer mètode, de difícil implementació, utilitza informació de visibilitat exacte per reconstruir de forma aproximada el mapa de multi-visibilitat. El segon, que va acompanyat de resultats d'implementació, obté informació de visibilitat aproximada per calcular i visualitzar mapes de multi-visibilitat discrets mitjançant hardware gràfic. Com a aplicacions es resolen problemes de multi-visibilitat entre regions i es responen preguntes sobre la multi-visibilitat d'un punt o d'una regió. A continuació tractem els problemes de proximitat sobre superfícies polièdriques triangulades considerant seus generalitzades. Es presenten dos mètodes, amb resultats d'implementació, per calcular distàncies des de seus generalitzades sobre superfícies polièdriques on hi poden haver obstacles generalitzats. El primer mètode calcula, de forma exacte, les distàncies definides pels camins més curts des de les seus als punts del poliedre. El segon mètode calcula, de forma aproximada, distàncies considerant els camins més curts sobre superfícies polièdriques amb pesos. Com a aplicacions, es calculen diagrames de Voronoi d'ordre k, i es resolen, de forma aproximada, alguns problemes de localització de serveis. També es proporciona un estudi teòric sobre la complexitat dels diagrames de Voronoi d'ordre k d'un conjunt de seus generalitzades en un poliedre sense pesos.

Key performance indicators (KPIs) and priority setting in using the multi-attribute approach for assessing sustainable intelligent buildings

The main objectives of this paper are to: firstly, identify key issues related to sustainable intelligent buildings (environmental, social, economic and technological factors); develop a conceptual model for the selection of the appropriate KPIs; secondly, test critically stakeholder's perceptions and values of selected KPIs intelligent buildings; and thirdly develop a new model for measuring the level of sustainability for sustainable intelligent buildings. This paper uses a consensus-based model (Sustainable Built Environment Tool- SuBETool), which is analysed using the analytical hierarchical process (AHP) for multi-criteria decision-making. The use of the multi-attribute model for priority setting in the sustainability assessment of intelligent buildings is introduced. The paper commences by reviewing the literature on sustainable intelligent buildings research and presents a pilot-study investigating the problems of complexity and subjectivity. This study is based upon a survey perceptions held by selected stakeholders and the value they attribute to selected KPIs. It is argued that the benefit of the new proposed model (SuBETool) is a ‘tool’ for ‘comparative’ rather than an absolute measurement. It has the potential to provide useful lessons from current sustainability assessment methods for strategic future of sustainable intelligent buildings in order to improve a building's performance and to deliver objective outcomes. Findings of this survey enrich the field of intelligent buildings in two ways. Firstly, it gives a detailed insight into the selection of sustainable building indicators, as well as their degree of importance. Secondly, it tesst critically stakeholder's perceptions and values of selected KPIs intelligent buildings. It is concluded that the priority levels for selected criteria is largely dependent on the integrated design team, which includes the client, architects, engineers and facilities managers.

Assessing the environmental performance of English arable and livestock holdings using data from the Farm Accountancy Data Network (FADN)

Agri-environment schemes (AESs) have been implemented across EU member states in an attempt to reconcile agricultural production methods with protection of the environment and maintenance of the countryside. To determine the extent to which such policy objectives are being fulfilled, participating countries are obliged to monitor and evaluate the environmental, agricultural and socio-economic impacts of their AESs. However, few evaluations measure precise environmental outcomes and critically, there are no agreed methodologies to evaluate the benefits of particular agri-environmental measures, or to track the environmental consequences of changing agricultural practices. In response to these issues, the Agri-Environmental Footprint project developed a common methodology for assessing the environmental impact of European AES. The Agri-Environmental Footprint Index (AFI) is a farm-level, adaptable methodology that aggregates measurements of agri-environmental indicators based on Multi-Criteria Analysis (MCA) techniques. The method was developed specifically to allow assessment of differences in the environmental performance of farms according to participation in agri-environment schemes. The AFI methodology is constructed so that high values represent good environmental performance. This paper explores the use of the AFI methodology in combination with Farm Business Survey data collected in England for the Farm Accountancy Data Network (FADN), to test whether its use could be extended for the routine surveillance of environmental performance of farming systems using established data sources. Overall, the aim was to measure the environmental impact of three different types of agriculture (arable, lowland livestock and upland livestock) in England and to identify differences in AFI due to participation in agri-environment schemes. However, because farm size, farmer age, level of education and region are also likely to influence the environmental performance of a holding, these factors were also considered. Application of the methodology revealed that only arable holdings participating in agri-environment schemes had a greater environmental performance, although responses differed between regions. Of the other explanatory variables explored, the key factors determining the environmental performance for lowland livestock holdings were farm size, farmer age and level of education. In contrast, the AFI value of upland livestock holdings differed only between regions. The paper demonstrates that the AFI methodology can be used readily with English FADN data and therefore has the potential to be applied more widely to similar data sources routinely collected across the EU-27 in a standardised manner.

Blind channel acquisition and channel estimation for multi-rate multicarrier DS-CDMA communications

Multi-rate multicarrier DS-CDMA is a potentially attractive multiple access method for future wireless networks that must support multimedia, and thus multi-rate, traffic. Considering that high performance detection such as coherent demodulation needs the explicit knowledge of the channel, this paper proposes a subspace-based blind adaptive algorithm for timing acquisition and channel estimation in asynchronous multirate multicarrier DS-CDMA systems, which is applicable to both multicode and variable spreading factor systems.

Sustainable urban metabolism as a link between bio-physical sciences and urban planning: the BRIDGE project

Urban metabolism considers a city as a system with flows of energy and material between it and the environment. Recent advances in bio-physical sciences provide methods and models to estimate local scale energy, water, carbon and pollutant fluxes. However, good communication is required to provide this new knowledge and its implications to endusers (such as urban planners, architects and engineers). The FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) aimed to address this gap by illustrating the advantages of considering these issues in urban planning. The BRIDGE Decision Support System (DSS) aids the evaluation of the sustainability of urban planning interventions. The Multi Criteria Analysis approach adopted provides a method to cope with the complexity of urban metabolism. In consultation with targeted end-users, objectives were defined in relation to the interactions between the environmental elements (fluxes of energy, water, carbon and pollutants) and socioeconomic components (investment costs, housing, employment, etc.) of urban sustainability. The tool was tested in five case study cities: Helsinki, Athens, London, Florence and Gliwice; and sub-models were evaluated using flux data selected. This overview of the BRIDGE project covers the methods and tools used to measure and model the physical flows, the selected set of sustainability indicators, the methodological framework for evaluating urban planning alternatives and the resulting DSS prototype.

Multi-hop amplify-and-forward relaying cooperation in the presence of I/Q imbalance

In this paper, multi-hop cooperative networks implementing channel state information (CSI)-assisted amplify-and-forward (AF) relaying in the presence of in-phase and quadrature-phase (I/Q) imbalance are investigated. We propose a compensation algorithm for the I/Q imbalance. The performance of the multi-hop CSI-assisted AF cooperative networks with and without compensation for I/Q imbalance in Nakagami-m fading environment is evaluated in terms of average symbol error probability. Numerical results are provided and show that the proposed compensation method can effectively mitigate the impact of I/Q imbalance.

Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

Multiple-criteria decision analysis for integrated catchment management

Implementation of integrated catchment management (ICM) is hampered by the lack of a conceptual framework for explaining how landowners select farming systems for their properties. Benefit–cost analysis (a procedure that estimates the costs and benefits of alternative actions or policies) has limitations in this regard, which might be overcome by using multiple-criteria decision analysis (MCDA). MCDA evaluates and ranks alternatives based on a landowner's preferences (weights) for multiple-criteria and the values of those criteria. A MCDA approach to ICM is superior to benefit–cost analysis which focuses only on the monetary benefits and costs, because it: 1) recognizes that human activities within a catchment are motivated by multiple and often competing criteria and/or constraints; 2) does not require monetary valuation of criteria; 3) allows trade-offs between criteria to be measured and evaluated; 4) explicitly considers how the spatial configuration of farming systems in a catchment influences the values of criteria; 5) is comprehensive, knowledge-based, and stakeholder oriented which greatly increases the likelihood of resolving catchment problems; and 6) allows consideration of the fairness and sustainability of land and water resource management decisions. A MCDA based on an additive, multiple-criteria utility function containing five economic and environmental criteria was used to score and rank five farming systems. The rankings were based on the average criteria weights for a sample of 20 farmers in a US catchment. The most profitable farming system was the lowest-ranked farming system. Three possible reasons for this result are evaluated. First, the MCDA method might cause respondents to express socially acceptable attitudes towards environmental criteria even when they are not important from a personal viewpoint. Second, the MCDA method could inflate the ranks of less profitable farming systems for the simple reason that it allows the respondent to assign non-zero weights to non-economic criteria. Third, the MCDA might provide a better framework for evaluating a landowner's selection of farming systems than the profit maximization model.

Interlink decision making index (IDMI) : a simple tool/concept to assist decision making for sustainability part 2 : calculation and examples of IDMI

There is an apparent gap between the LCA or other assessment's outcomes and its effective application in the decision making process. It is needed to provide to the decision makers a simple, less human interfered mechanism that integrates all the key criteria (environmental, economic, technical and safety etc.). The proposed index: Interlink Decision Making Index (IDMI) has all these features: simple, interlink (all criteria) and automatically and quantified influence of critical criteria (ie. no human weighting needed) and is able to assist the multi-criteria decision making for sustainability based on the outcomes of specific assessments (eg. LCA, BIA etc.). The index represents a pure numerical value and does not necessarily have any physical meanings, but it reflects the total merits of a particular option once the normal decision making criteria and (up to two) critical criteria (Ce) have been chosen. Then, without arbitrarily weighting process, the comparison and selection of the best possible option, ie. decision can be made based on the derived IDMI results. Two hypothetical examples are presented in the part 2 of the paper to demonstrate the application of the IDMI concept and it's differences with the traditional "tabular method" in the decision making process.

Dual-random ensemble method for multi-label classification of biological data

This paper presents a dual-random ensemble multi-label classification method for classification of multi-label data. The method is formed by integrating and extending the concepts of feature subspace method and random k-label set ensemble multi-label classification method. Experiemental results show that the developed method outperforms the exisiting multi-lable classification methods on three different multi-lable datasets including the biological yeast and genbase datasets.

A triple-random ensemble classification method for mining multi-label data

This paper presents a triple-random ensemble learning method for handling multi-label classification problems. The proposed method integrates and develops the concepts of random subspace, bagging and random k-label sets ensemble learning methods to form an approach to classify multi-label data. It applies the random subspace method to feature space, label space as well as instance space. The devised subsets selection procedure is executed iteratively. Each multi-label classifier is trained using the randomly selected subsets. At the end of the iteration, optimal parameters are selected and the ensemble MLC classifiers are constructed. The proposed method is implemented and its performance compared against that of popular multi-label classification methods. The experimental results reveal that the proposed method outperforms the examined counterparts in most occasions when tested on six small to larger multi-label datasets from different domains. This demonstrates that the developed method possesses general applicability for various multi-label classification problems.