On the stability of the optimal value and the optimal set in optimization problems

The paper develops a stability theory for the optimal value and the optimal set mapping of optimization problems posed in a Banach space. The problems considered in this paper have an arbitrary number of inequality constraints involving lower semicontinuous (not necessarily convex) functions and one closed abstract constraint set. The considered perturbations lead to problems of the same type as the nominal one (with the same space of variables and the same number of constraints), where the abstract constraint set can also be perturbed. The spaces of functions involved in the problems (objective and constraints) are equipped with the metric of the uniform convergence on the bounded sets, meanwhile in the space of closed sets we consider, coherently, the Attouch-Wets topology. The paper examines, in a unified way, the lower and upper semicontinuity of the optimal value function, and the closedness, lower and upper semicontinuity (in the sense of Berge) of the optimal set mapping. This paper can be seen as a second part of the stability theory presented in [17], where we studied the stability of the feasible set mapping (completed here with the analysis of the Lipschitz-like property).

A parameter-free approach for solving combinatorial optimization problems through biased randomization of efficient heuristics

This paper discusses the use of probabilistic or randomized algorithms for solving combinatorial optimization problems. Our approach employs non-uniform probability distributions to add a biased random behavior to classical heuristics so a large set of alternative good solutions can be quickly obtained in a natural way and without complex conguration processes. This procedure is especially useful in problems where properties such as non-smoothness or non-convexity lead to a highly irregular solution space, for which the traditional optimization methods, both of exact and approximate nature, may fail to reach their full potential. The results obtained are promising enough to suggest that randomizing classical heuristics is a powerful method that can be successfully applied in a variety of cases.

An Analysis of black-box optimization problems in reinsurance: evolutionary-based approaches

Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.

Avaluació Interna als Centres de Secundària : Anàlisi de la situació actual : beneficis, problemes i riscos

El treball es proposa dur a terme un estudi descriptiu sobre la situació de l'avaluació interna a tres centres de secundària per tal de conèixer quina és la situació actual, quines actuacions es porten a terme explícitament o implícitament i quins beneficis se'n deriven o poden derivar-se'n, així com també quins són els problemes i reticències que comporta i els riscos que pot originar la posada en pràctica, tant conscientment com inconscient, d'aquesta avaluació interna.

La formación de usuarios en una biblioteca virtual universitaria

En un context d'educació a distància i amb usuaris virtuals, la formació en l'ús dels serveis i recursos d'una biblioteca universitària requereix d'una adaptació de les formes tradicionalment ofertes des de les Biblioteques presencials al nou entorn amb mètodes nous i innovadors. En aquest sentit, la Biblioteca de l'UOC ha desenvolupat noves vies de comunicació i nous formats per poder difondre serveis i per formar els nostres usuaris en l'ús d'aquests. La característica comuna de la majoria d'ells, és la de ser 'formació a distància' que es du a terme a través d'un 'Campus virtual'. Les diferents opcions seran analitzades en la comunicació així com les problemàtiques i avantatges que presenten els diversos mètodes de formació duts a terme per les biblioteques universitàries en entorns virtuals.

El arte que traduce. 1995-2010: la traducción como mediación cultural en los procesos de transmisión y recepción de las obras de arte

El trabajo de investigación realizado durante los tres últimos años de beca se centra en las teorías críticas y en las prácticas artísticas contemporáneas que utilizan la traducción como mediación cultural en los procesos de transmisión y recepción de las obras de arte contemporáneo. En el contexto artistico contemporáneo la traducción es entendida como intercambio, adaptación, traslado o transacción. Tomando como referentes conceptuales las teorías nacidas en el marco interdisciplinar de los Estudios Visuales y de los Estudios de Traducción, dicha investigación se ha centrado en el análisis del fenómeno de la traducción en la producción artística. A partir de este análisis se han investigado las conexiones entre estas disciplinas humanísticas y la práctica artística, así como la problemática que éstas conllevan en la formulación de nuevos criterios y nuevas categorías de la Historia del Arte actual. En la práctica artística cuestiones relativas a la traducción se han podido integrar al arte visual: por un lado como práctica indispensable para la comprensión e interpretación de la obra de arte entre diferentes contextos geográficos o culturales, y por otro, como elemento “formal” indispensable para la realización de los artefactos artísticos que, a su vez, quieren interpretar diferentes realidades sociales, antropológicas o políticas. Sobretodo a partir de la serie On Translation del artista catalán Antoni Muntadas, así como de otros artistas de varios contextos geográficos y culturales, se han analizado las dinámicas prácticas y teóricas de la traducción que acompañan el proceso de la realización de los artefactos artísticos. Muchas de estas obras de arte contemporáneo asimilando los significantes propios del contexto cultural, social, político, económico, y utilizando elementos formales variados (sobretodo tecnológicos) necesitan de un análisis interdisciplinar.

Signalling and Productivity Effects of Overeducation: Is It Really a Waste of Resources?

Overeducation raises concerns that governments may be overinvesting in education. To inform the debate, this paper studies the impact of overeducation on productivity. We advance the literature by considering that returns to overeducation may be due both to productivity and signalling effects. To disentangle both effects, we apply Wolpin’s (1977) methodology and compare the rates of return of screened (employed) and unscreened (selfemployed) workers. To overcome well-known endogeneity problems due to unobserved heterogeneity, we estimate a panel with individual and employment-status fixed effects. Our results show that signalling effects are relevant and that overeducation does not carry a productivity penalty. Keywords: Overeducation, signalling model, human capital model, unobserved heterogeneity. JEL classification: I20, J24, J31.

A multi-objective model for a multi-period distribution management problem

The problems arising in commercial distribution are complex and involve several players and decision levels. One important decision is relatedwith the design of the routes to distribute the products, in an efficient and inexpensive way.This article deals with a complex vehicle routing problem that can beseen as a new extension of the basic vehicle routing problem. The proposed model is a multi-objective combinatorial optimization problemthat considers three objectives and multiple periods, which models in a closer way the real distribution problems. The first objective is costminimization, the second is balancing work levels and the third is amarketing objective. An application of the model on a small example, with5 clients and 3 days, is presented. The results of the model show the complexity of solving multi-objective combinatorial optimization problems and the contradiction between the several distribution management objective.

Adaptive approach heuristics for the generalized assignment problem

The Generalized Assignment Problem consists in assigning a setof tasks to a set of agents with minimum cost. Each agent hasa limited amount of a single resource and each task must beassigned to one and only one agent, requiring a certain amountof the resource of the agent. We present new metaheuristics forthe generalized assignment problem based on hybrid approaches.One metaheuristic is a MAX-MIN Ant System (MMAS), an improvedversion of the Ant System, which was recently proposed byStutzle and Hoos to combinatorial optimization problems, and itcan be seen has an adaptive sampling algorithm that takes inconsideration the experience gathered in earlier iterations ofthe algorithm. Moreover, the latter heuristic is combined withlocal search and tabu search heuristics to improve the search.A greedy randomized adaptive search heuristic (GRASP) is alsoproposed. Several neighborhoods are studied, including one basedon ejection chains that produces good moves withoutincreasing the computational effort. We present computationalresults of the comparative performance, followed by concludingremarks and ideas on future research in generalized assignmentrelated problems.

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.

Open inflation and the singulary boundary

The singularity in the Hawking-Turok model of open inflation has some appealing properties, such as the fact that its action is integrable. Also, if one thinks of the singularity as the boundary of spacetime, then the Gibbons-Hawking term is nonvanishing and finite. Here, we consider a model where the gravitational and scalar fields are coupled to a dynamical membrane. The singular instanton can then be obtained as the limit of a family of no-boundary solutions where both the geometry and the scalar field are regular. Using this procedure, the contribution of the singularity to the Euclidean action is just 1/3 of the Gibbons-Hawking term. Unrelated to this issue, we also point out that the singularity acts as a reflecting boundary for scalar perturbations and gravity waves. Therefore, the quantization of cosmological perturbations seems to be well posed in this background.

Practical algorithms for a family of waterfilling solutions

Many engineering problems that can be formulatedas constrained optimization problems result in solutionsgiven by a waterfilling structure; the classical example is thecapacity-achieving solution for a frequency-selective channel.For simple waterfilling solutions with a single waterlevel and asingle constraint (typically, a power constraint), some algorithmshave been proposed in the literature to compute the solutionsnumerically. However, some other optimization problems result insignificantly more complicated waterfilling solutions that includemultiple waterlevels and multiple constraints. For such cases, itmay still be possible to obtain practical algorithms to evaluate thesolutions numerically but only after a painstaking inspection ofthe specific waterfilling structure. In addition, a unified view ofthe different types of waterfilling solutions and the correspondingpractical algorithms is missing.The purpose of this paper is twofold. On the one hand, itoverviews the waterfilling results existing in the literature from aunified viewpoint. On the other hand, it bridges the gap betweena wide family of waterfilling solutions and their efficient implementationin practice; to be more precise, it provides a practicalalgorithm to evaluate numerically a general waterfilling solution,which includes the currently existing waterfilling solutions andothers that may possibly appear in future problems.

Algorithm optimization for solving crew scheduling problems

In this paper, we are proposing a methodology to determine the most efficient and least costly way of crew pairing optimization. We are developing a methodology based on algorithm optimization on Eclipse opensource IDE using the Java programming language to solve the crew scheduling problems.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Some optimization and decision problems in proportional reinsurance

Reinsurance is one of the tools that an insurer can use to mitigate the underwriting risk and then to control its solvency. In this paper, we focus on the proportional reinsurance arrangements and we examine several optimization and decision problems of the insurer with respect to the reinsurance strategy. To this end, we use as decision tools not only the probability of ruin but also the random variable deficit at ruin if ruin occurs. The discounted penalty function (Gerber & Shiu, 1998) is employed to calculate as particular cases the probability of ruin and the moments and the distribution function of the deficit at ruin if ruin occurs.