Equilibrium plans in constrained environments

In this paper we analyze equilibria in competitive environments under constraints across players'' strategies. This means that the action taken by one player limits the possible choices of the other players. In this context the classical approach, Kakutani''s Fixed Point theorem, does not work. In particular, best replies against a given strategy profile may not be feasible. We extend Kakutani''s Fixed Point theorem to deal with the feasibility issue.Our main motivation to study this problem of co-dependency comes from the field of supply chain planning. A set of buyers is faced with external demand over a planning horizon, and to satisfy this demand they request inputs from a set of suppliers. Both suppliers and buyers face production capacities and the planning is made in a decentralized manner. A well-known coordination scheme for this setting is the upstream approach where the planning of the buyers is used to decide the request to the suppliers. We show the existence of equilibria for two versions of this coordination model. However, we illustrate with an example that the centralized solution is not, in general, an equilibrium, suggesting that regulation may be needed.We also apply our Fixed Point theorem to a production economy, where both supply and demand are upper bounded.operations research and management science;

Binarized support vector machines

The widely used Support Vector Machine (SVM) method has shown to yield very good results in Supervised Classification problems. Other methods such as Classification Trees have become more popular among practitioners than SVM thanks to their interpretability, which is an important issue in Data Mining. In this work, we propose an SVM-based method that automatically detects the most important predictor variables, and the role they play in the classifier. In particular, the proposed method is able to detect those values and intervals which are critical for the classification. The method involves the optimization of a Linear Programming problem, with a large number of decision variables. The numerical experience reported shows that a rather direct use of the standard Column-Generation strategy leads to a classification method which, in terms of classification ability, is competitive against the standard linear SVM and Classification Trees. Moreover, the proposed method is robust, i.e., it is stable in the presence of outliers and invariant to change of scale or measurement units of the predictor variables. When the complexity of the classifier is an important issue, a wrapper feature selection method is applied, yielding simpler, still competitive, classifiers

The Agents-are-Substitutes Property in Continuous Generalized Assignment Problems

The VCG mechanism has some nice properties if the agents-are-substitutes property holds.For example, for combinatorial auctions the property assures that the VCG mechanism is supported by a pricing equilibrium. The existence of such a pricing equilibrium is a necessary condition for the existence of ascending auctions that are equivalent to the VCG mechanism.Although it is known that the agents-are-substitutes property is important in several settings few problems or subclasses of problems are proven to have the property.In this paper we show for a class of problems that the agents-are-substitutes property holds. Moreover we give two rather natural and small extensions that do not have this property in general.Furthermore we show that in our simple problem class we need the possibility of price discrimination.operations research and management science;

Binarized support vector machines

The widely used Support Vector Machine (SVM) method has shown to yield very good results in Supervised Classification problems. Other methods such as Classification Trees have become more popular among practitioners than SVM thanks to their interpretability, which is an important issue in Data Mining. In this work, we propose an SVM-based method that automatically detects the most important predictor variables, and the role they play in the classifier. In particular, the proposed method is able to detect those values and intervals which are critical for the classification. The method involves the optimization of a Linear Programming problem, with a large number of decision variables. The numerical experience reported shows that a rather direct use of the standard Column-Generation strategy leads to a classification method which, in terms of classification ability, is competitive against the standard linear SVM and Classification Trees. Moreover, the proposed method is robust, i.e., it is stable in the presence of outliers and invariant to change of scale or measurement units of the predictor variables. When the complexity of the classifier is an important issue, a wrapper feature selection method is applied, yielding simpler, still competitive, classifiers.Supervised classification, Binarization, Column generation, Support vector machines

A dissimilarity-based approach for Classification

The Nearest Neighbor classifier has shown to be a powerful tool for multiclass classification. In this note we explore both theoretical properties and empirical behavior of a variant of such method, in which the Nearest Neighbor rule is applied after selecting a set of so-called prototypes, whose cardinality is fixed in advance, by minimizing the empirical mis-classification cost. With this we alleviate the two serious drawbacks of the Nearest Neighbor method: high storage requirements and time-consuming queries. The problem is shown to be NP-Hard. Mixed Integer Programming (MIP) programs are formulated, theoretically compared and solved by a standard MIP solver for problem instances of small size. Large sized problem instances are solved by a metaheuristic yielding good classification rules in reasonable time.operations research and management science;

Supervised Classification and Mathematical Optimization

Data Mining techniques often ask for the resolution of optimization problems. Supervised Classification, and, in particular, Support Vector Machines, can be seen as a paradigmatic instance. In this paper, some links between Mathematical Optimization methods and Supervised Classification are emphasized. It is shown that many different areas of Mathematical Optimization play a central role in off-the-shelf Supervised Classification methods. Moreover, Mathematical Optimization turns out to be extremely useful to address important issues in Classification, such as identifying relevant variables, improving the interpretability of classifiers or dealing with vagueness/noise in the data

El papel de la biblioteca en la formación de competencias informacionales e informáticas

Se destaca la importancia de la biblioteca en la implantación y desarrollo de la Alfabetización Informacional como medio imprescindible de formación en competencias informacionales y digitales en la actual sociedad de información. Dicho papel es impulsado por diferentes instituciones internacionales y nacionales. Se hace especial mención de las bibliotecas universitarias en el nuevo Espacio Europeo de Educación Superior y, sobre todo, en el ámbito español donde REBIUN ha adoptado el término de “Competencias Informacionales e Informáticas” (CI2) y ha influido en el paso de una formación tradicional de usuarios a una formación basada en competencias que deben adquirir los alumnos, contribuyendo a mejorar la calidad de la educación. Todo ello apoyado en una planificación y en la transformación de las bibliotecas en Centros de Recursos de Información y Aprendizaje. En este proceso de cambio, la web social 2.0 y 3.0 es elemento esencial de interacción y motivación interna para conseguir que el alumno se convierta en sujeto activo de su propio aprendizaje. La implementación por parte de numerosas bibliotecas de las diferentes herramientas sociales como Facebook y Twitter ha logrado una visibilidad mayor y un elemento dinamizador.The importance of the library in the implementation and development of information literacy as an essential means of training in Information and Digital Competency in the current information society is emphasized. This paper is driven by various international and national institutions. Special mention of university libraries in the new European Higher Education and is made especially in the area where REBIUN Spanish adopted the term "Informational and Computer Literacy" (CI2) and has influenced the passage of a training traditional users to a competency-based training that students should acquire, helping to improve the quality of education. All supported in planning and in the transformation of libraries in Resource Centers Information and Learning. In this process of change, social web 2.0 and 3.0 is an essential element of interaction and internal motivation to get students to become active subjects of their own learning. The implementation by numerous libraries of different social tools such as Facebook and Twitter has achieved greater visibility and a dynamic element

A Greedy Heuristic for a Three-Level Multi-Period Single-Sourcing Problem

In this paper we consider a model for integrating transportation and inventory decisions in a three-level logistics network consisting of plants, warehouses, and retailers (or customers). Our model includes production and throughout capacity constraints, and minimizes production, holding, and tansportation costs in a dynamic environment. We show that the problem can be reformulated as a certain type of assignment problem with convex objective function. Based on this observation, we propose a greedy heuristic for the problem, and illustrate its behaviour on a class of randomly generated problem instances. These experiments suggest that the heuristic may be asymptotically feasible and optimal with probability one in the number of customers

Ecologically Designed Sanitary Sewer Based on Constructed WetlandsTechnology – Case Study in Managua (Nicaragua)

In developed countries the sanitation and treatment of urban wastewater is well sustained and technically solved by means of conventional pipe networksandsubsequentcentralizedtreatments.However,developingcountries lack these infrastructures and are in need of sustainable, decentralized and economically viable solutions for the disposal of their urban wastewaters. In addition to this, there are situations where the demands of conservation of naturalspacesdonotallowintensiveconstructiveproceduresandwhichforce the implementation of sanitary engineering with less environmental impact. We present the Ecological Wastewater Sewer (EWS), an ecological urban sewerage system that simultaneously transports wastewater and improves its quality.Thisinnovativetechnologyisanalternativetoconventionalsanitation piping that has minimal environmental impact. It is based on a successful previous work for the improvement of artificial wetlands in a pilot scheme andatfull-scaleonatestsite.TheEWSisachannel-shapeddevicethatrelies on the application of two key developments: a carefully designed cornered stones layout, and the creation of a natural aeration system. This way, it acts as a separating sewage system that guarantees the presence of a chamber of circulating air within the transportation unit, favouring permanent aerobic conditions in the upper levels of the mass of wastewater. Furthermore, its capacity to set tle suspended solids allows the EWS to be used as a sedimentor in water purification processes. A real-life application of this system proved successful in the sanitation of a district of Managua (Nicaragua). Working with a 100-metre-long street of 20 one-story houses, the system is reported to still be in full operating order after six years. The conclusions and results drawn from its monitoring are meticulously explained in our paper, as well astherecommendations&guidelinesforthedesignofmoreEWSunits,with aim to the popularization of this affordable, efficient and green approach to wastewater sanitation.Andalusian International School of Water Engineering, City hall of SevilleCooperation Office at the University of Sevill