Notes on the Solution of Dynamic Optimization Problems with Explicit Controls in Discrete-Time Economic Models

Йордан Йорданов, Андрей Василев - В работата се изследват методи за решаването на задачи на оптималното управление в дискретно време с безкраен хоризонт и явни управления. Дадена е обосновка на една процедура за решаване на такива задачи, базирана на множители на Лагранж, коята често се употребява в икономическата литература. Извеждени са необходимите условия за оптималност на базата на уравнения на Белман и са приведени достатъчни условия за оптималност при допускания, които често се използват в икономиката.

Riemann-Hilbert Problems with Canonical Normalization and Families of Commuting Operators

2010 Mathematics Subject Classification: 35Q15, 31A25, 37K10, 35Q58.

First-Order Conditions for Optimization Problems with Quasiconvex Inequality Constraints

2000 Mathematics Subject Classification: 90C46, 90C26, 26B25, 49J52.

A származtatott termékek árazása és annak problémái az egyensúlyelmélet szempontjából (Pricing of derived products and problems with it in terms of equilibrium theory)

A szerző röviden összefoglalja a származtatott termékek árazásával kapcsolatos legfontosabb ismereteket és problémákat. A derivatív árazás elmélete a piacon levő termékek közötti redundanciát kihasználva próbálja meghatározni az egyes termékek relatív árát. Ezt azonban csak teljes piacon lehet megtenni, és így csak teljes piac esetén lehetséges a hasznossági függvények fogalmát az elméletből és a ráépülő gyakorlatból elhagyni, ezért a kockázatsemleges árazás elve félrevezető. Másképpen fogalmazva: a származtatott termékek elmélete csak azon az áron képes a hasznossági függvény fogalmától megszabadulni, ha a piac szerkezetére a valóságban nem teljesülő megkötéseket tesz. Ennek hangsúlyozása mind a piaci gyakorlatban, mind az oktatásban elengedhetetlen. / === / The author sums up briefly the main aspects and problems to do with the pricing of derived products. The theory of derivative pricing uses the redundancy among products on the market to arrive at relative product prices. But this can be done only on a complete market, so that only with a complete market does it become possible to omit from the theory and the practice built upon it the concept of utility functions, and for that reason the principle of risk-neutral pricing is misleading. To put it another way, the theory of derived products is capable of freeing itself from the concept of utility functions only at a price where in practice it places impossible restrictions on the market structure. This it is essential to emphasize in market practice and in teaching.

Speaking with different voices: the problems with English law and psychiatric injury

Private law courts in the UK have maintained the de minimis threshold as a condition precedent for a successful claim for the infliction of mental harm. This de minimis threshold necessitates the presence of a ‘recognised psychiatric illness’ as opposed to ‘mere emotion’. This standard has also been adopted by the criminal law courts when reading the Offences Against the Person Act 1861 to include non-physical injury. In determining the cut-off point between psychiatric injury and mere emotion, the courts have adopted a generally passive acceptance of expert testimony and the guidelines used by mental health professionals to make diagnoses. Yet these guidelines were developed for use in a clinical setting, not a legal one. This article examines the difficulty inherent in utilising the ‘dimensional’ diagnostic criteria used by mental health professionals to answer ‘categorical’ legal questions. This is of particular concern following publication of the new diagnostic manual, DSM-V in 2013, which will further exacerbate concerns about compatibility. It is argued that a new set of diagnostic guidelines, tailored specifically for use in a legal context, is now a necessity.

Multi-stage scheduling problems with precedence constraints

Abstract not available

Positive solutions for parametric Dirichlet problems with indefinite potential and superdiffusive reaction

We consider a parametric semilinear Dirichlet problem driven by the Laplacian plus an indefinite unbounded potential and with a reaction of superdifissive type. Using variational and truncation techniques, we show that there exists a critical parameter value λ_{∗}>0 such that for all λ> λ_{∗} the problem has least two positive solutions, for λ= λ_{∗} the problem has at least one positive solutions, and no positive solutions exist when λ∈(0,λ_{∗}). Also, we show that for λ≥ λ_{∗} the problem has a smallest positive solution.

Zombie pedagogies: the problems with using the undead in public pedagogies for emergencies

The well-known Hollywood ‘zombie’ genre has recently begun to invade programs and training courses in disaster control and emergency prevention. The author explores the consequences of a transfer of an entertainment metaphor into real US military policies. Is it possible that this implies attuning the populace to catastrophies by means of edutainment? And does this, as Preston argues, in some ways ‘de-humanize’ one’s adversaries? The article points to a fatal dialectics and disturbing elements of a post-ethical disposition. This results not only in some sort of inevitable legitimation of the ‘war on terror’ leaving behind all tenets of civil society. It also permits, subcutaneously, to act without restrictions against certain groups as if they were ‘undeads’.

Efficient algorithms to solve scheduling problems with a variety of optimization criteria

La programmation par contraintes est une technique puissante pour résoudre, entre autres, des problèmes d’ordonnancement de grande envergure. L’ordonnancement vise à allouer dans le temps des tâches à des ressources. Lors de son exécution, une tâche consomme une ressource à un taux constant. Généralement, on cherche à optimiser une fonction objectif telle la durée totale d’un ordonnancement. Résoudre un problème d’ordonnancement signifie trouver quand chaque tâche doit débuter et quelle ressource doit l’exécuter. La plupart des problèmes d’ordonnancement sont NP-Difficiles. Conséquemment, il n’existe aucun algorithme connu capable de les résoudre en temps polynomial. Cependant, il existe des spécialisations aux problèmes d’ordonnancement qui ne sont pas NP-Complet. Ces problèmes peuvent être résolus en temps polynomial en utilisant des algorithmes qui leur sont propres. Notre objectif est d’explorer ces algorithmes d’ordonnancement dans plusieurs contextes variés. Les techniques de filtrage ont beaucoup évolué dans les dernières années en ordonnancement basé sur les contraintes. La proéminence des algorithmes de filtrage repose sur leur habilité à réduire l’arbre de recherche en excluant les valeurs des domaines qui ne participent pas à des solutions au problème. Nous proposons des améliorations et présentons des algorithmes de filtrage plus efficaces pour résoudre des problèmes classiques d’ordonnancement. De plus, nous présentons des adaptations de techniques de filtrage pour le cas où les tâches peuvent être retardées. Nous considérons aussi différentes propriétés de problèmes industriels et résolvons plus efficacement des problèmes où le critère d’optimisation n’est pas nécessairement le moment où la dernière tâche se termine. Par exemple, nous présentons des algorithmes à temps polynomial pour le cas où la quantité de ressources fluctue dans le temps, ou quand le coût d’exécuter une tâche au temps t dépend de t.

Tensor Completion for Multidimensional Inverse Problems with Applications to Magnetic Resonance Relaxometry

This thesis deals with tensor completion for the solution of multidimensional inverse problems. We study the problem of reconstructing an approximately low rank tensor from a small number of noisy linear measurements. New recovery guarantees, numerical algorithms, non-uniform sampling strategies, and parameter selection algorithms are developed. We derive a fixed point continuation algorithm for tensor completion and prove its convergence. A restricted isometry property (RIP) based tensor recovery guarantee is proved. Probabilistic recovery guarantees are obtained for sub-Gaussian measurement operators and for measurements obtained by non-uniform sampling from a Parseval tight frame. We show how tensor completion can be used to solve multidimensional inverse problems arising in NMR relaxometry. Algorithms are developed for regularization parameter selection, including accelerated k-fold cross-validation and generalized cross-validation. These methods are validated on experimental and simulated data. We also derive condition number estimates for nonnegative least squares problems. Tensor recovery promises to significantly accelerate N-dimensional NMR relaxometry and related experiments, enabling previously impractical experiments. Our methods could also be applied to other inverse problems arising in machine learning, image processing, signal processing, computer vision, and other fields.

Definition of Model-based diagnosis problems with Altarica

International audience

Nonlinear periodic problems with a jumping reaction

We consider a periodic problem driven by the scalar $p-$Laplacian and with a jumping (asymmetric) reaction. We prove two multiplicity theorems. The first concerns the nonlinear problem ($1

Quenching phenomenon of singular parabolic problems with L1 initial data

We extend some previous existence results for quenching type parabolic problems involving a negative power of the unknown in the equation to the case of merely integrable initial data. We show that L1 Ω is the suitable framework to obtain the continuous dependence with respect to some norm of the initial datum; This way we answer to the question raised by several authors in the previous literature. We also show the complete quenching phenomena for such a L1-initial datum.

Measure-valued mass evolution problems with flux boundary conditions and solution-dependent velocities

In this paper we prove well-posedness for a measure-valued continuity equation with solution-dependent velocity and flux boundary conditions, posed on a bounded one-dimensional domain. We generalize the results of an earlier paper [J. Differential Equations, 259 (2015), pp. 10681097] to settings where the dynamics are driven by interactions. In a forward-Euler-like approach, we construct a time-discretized version of the original problem and employ those results as a building block within each subinterval. A limit solution is obtained as the mesh size of the time discretization goes to zero. Moreover, the limit is independent of the specific way of partitioning the time interval [0, T]. This paper is partially based on results presented in Chapter 5 of [Evolution Equations for Systems Governed by Social Interactions, Ph.D. thesis, Eindhoven University of Technology, 2015], while a number of issues that were still open there are now resolved.

Power flow forecasting and smart charging for electric vehicle charging systems with photovoltaic integration

An essential role in the global energy transition is attributed to Electric Vehicles (EVs) the energy for EV traction can be generated by renewable energy sources (RES), also at a local level through distributed power plants, such as photovoltaic (PV) systems. However, EV integration with electrical systems might not be straightforward. The intermittent RES, combined with the high and uncontrolled aggregate EV charging, require an evolution toward new planning and paradigms of energy systems. In this context, this work aims to provide a practical solution for EV charging integration in electrical systems with RES. A method for predicting the power required by an EV fleet at the charging hub (CH) is developed in this thesis. The proposed forecasting method considers the main parameters on which charging demand depends. The results of the EV charging forecasting method are deeply analyzed under different scenarios. To reduce the EV load intermittency, methods for managing the charging power of EVs are proposed. The main target was to provide Charging Management Systems (CMS) that modulate EV charging to optimize specific performance indicators such as system self-consumption, peak load reduction, and PV exploitation. Controlling the EV charging power to achieve specific optimization goals is also known as Smart Charging (SC). The proposed techniques are applied to real-world scenarios demonstrating performance improvements in using SC strategies. A viable alternative to maximize integration with intermittent RES generation is the integration of energy storage. Battery Energy Storage Systems (BESS) may be a buffer between peak load and RES production. A sizing algorithm for PV+BESS integration in EV charging hubs is provided. The sizing optimization aims to optimize the system's energy and economic performance. The results provide an overview of the optimal size that the PV+BESS plant should have to improve whole system performance in different scenarios.