An optimality criterion for sizing members of heated structures with temperature constraints

A thermal optimality criterion is presented for sizing members of heated structures with multiple temperature constraints. The optimality criterion is similar to an existing optimality criterion for design of mechanically loaded structures with displacement constraints. Effectiveness of the thermal optimality criterion is assessed by applying it to one- and two-dimensional thermal problems where temperatures can be controlled by varying the material distribution in the structure. Results obtained from the optimality criterion agree within 2 percent with results from a closed-form solution and with results from a mathematical programming technique. The thermal optimality criterion augments existing optimality criteria for strength and stiffness related constraints and offers the possibility of extension of optimality techniques to sizing structures with combined thermal and mechanical loading

Allais-anonymity as an alternative to the discounted-sum criterion in the calculus of optimal growth I: Consensual optimality

The objective of this work is to try to define and calculate the optimal growth path, in the presence of exogenous technical change, without resorting to the discounted-sum criterion. The solution suggested is to consider an optimality criterion expressing an Allais-anonymous intergenerational consensus. The partial characterization of consensual optimality was made possible thanks to the decomposition of the dual of the space of sub-geometric sequences of reason p. The main finding is a relation between the marginal rate of substitution between bequest and heritage, and the growth rate, relation which is a necessary condition for consensual optimality. The necessary study of the Pareto-optimality of the consensual optimum is the subject of a forthcoming paper "Allais-anonymity as an alternative to the discounted-sum criterion in the calculus of optimal growth II: Pareto optimality and some economic interpretations".Intergenerational anonymity; Intergenerational equity; Optimal growth; Technical change; Time-preference; Discounted-sum criterion; Consensual criterion; OG economy

Allais-anonymity as an alternative to the discounted-sum criterion in the calculus of optimal growth II: Pareto optimality and some economic interpretations

This paper studies the Pareto-optimality of the consensual optimum established in "Allais-anonymity as an alternative to the discounted-sum criterion I: consensual optimality" (Mabrouk 2006a). For that, a Pareto-optimality criterion is set up by the application of the generalized Karush, Kuhn and Tucker theorem and thanks to the decomposition of the space of geometrically-growing real sequences. That makes it possible to find sufficient conditions so that a bequest-rule path is Pareto-optimal. Through an example, it is then shown that the golden rule must be checked to achieve Allais-anonymous optimality. The introduction of an additive altruism makes it possible to highlight the intergenerational-preference rate compatible with Allais-anonymous optimality. In this approach, it is not any more the optimality which depends on the intergenerational-preference rate, but the optimal intergenerational-preference rate which rises from Allais-anonymous optimality.Intergenerational anonymity; Allais-anonymity; Intergenerational equity; Optimal growth; Technical change; Time-preference; Discounted-sum criterion; Consensual criterion; Pareto-optimality; OG economy.

Intergenerational anonymity as an alternative to the discounted- sum criterion in the calculus of optimal growth I: Consensual optimality

The objective of this work is to try to define and calculate the optimal growth path, in the presence of exogenous technical change, without resorting to the discounted-sum criterion. The solution suggested is to consider an optimality criterion expressing an anonymous intergenerational consensus. The partial characterization of consensual optimality was made possible thanks to the decomposition of the dual of the space of sub-geometric sequences of reason p. The main finding is a relation between the marginal rate of substitution between bequest and heritage and the growth rate, relation which is a necessary condition for consensual optimality. The necessary study of the Pareto-optimality of the consensual optimum is the subject of a forthcoming paper « Intergenerational anonymity as an alternative to the discounted-sum criterion in the calculus of optimal growth II: Pareto-optimality and some economic interpretations »Intergenerational anonymity; Intergenerational equity; Optimal growth; Technical change; Time-preference; Discounted-sum criterion; Consensual criterion; OG economy

Regularization independent of the noise level: an analysis of quasi-optimality

The quasi-optimality criterion chooses the regularization parameter in inverse problems without taking into account the noise level. This rule works remarkably well in practice, although Bakushinskii has shown that there are always counterexamples with very poor performance. We propose an average case analysis of quasi-optimality for spectral cut-off estimators and we prove that the quasi-optimality criterion determines estimators which are rate-optimal {\em on average}. Its practical performance is illustrated with a calibration problem from mathematical finance.Comment: 18 pages, 3 figure

Comparing algorithms and criteria for designing Bayesian conjoint choice experiments.

The recent algorithm to find efficient conjoint choice designs, the RSC-algorithm developed by Sándor and Wedel (2001), uses Bayesian design methods that integrate the D-optimality criterion over a prior distribution of likely parameter values. Characteristic for this algorithm is that the designs satisfy the minimal level overlap property provided the starting design complies with it. Another, more embedded, algorithm in the literature, developed by Zwerina et al. (1996), involves an adaptation of the modified Fedorov exchange algorithm to the multinomial logit choice model. However, it does not take into account the uncertainty about the assumed parameter values. In this paper, we adjust the modified Fedorov choice algorithm in a Bayesian fashion and compare its designs to those produced by the RSC-algorithm. Additionally, we introduce a measure to investigate the utility balances of the designs. Besides the widely used D-optimality criterion, we also implement the A-, G- and V-optimality criteria and look for the criterion that is most suitable for prediction purposes and that offers the best quality in terms of computational effectiveness. The comparison study reveals that the Bayesian modified Fedorov choice algorithm provides more efficient designs than the RSC-algorithm and that the Dand V-optimality criteria are the best criteria for prediction, but the computation time with the V-optimality criterion is longer.A-Optimality; Algorithms; Bayesian design; Bayesian modified Fedorov choice algorithm; Choice; Conjoint choice experiments; Criteria; D-Optimality; Design; Discrete choice experiments; Distribution; Effectiveness; Fashion; G-optimality; Logit; Methods; Model; Multinomial logit; Predictive validity; Quality; Research; RSC-algorithm; Studies; Time; Uncertainty; V-optimality; Value;

An optimality criterion to determine areas of endemism

A formal method was developed to determine areas of endemism. The study region is divided into cells, and the number of species that can be considered as endemic is counted for a given set of cells (= area). Thus, the areas with the maximum number of species considered endemic are preferred. This is the first method for the identification of areas of endemism that implements an optimality criterion directly based on considering the aspects of species distribution that are relevant to endemism. The methodis implemented in two computer programs, NDM and VNDM, available from the authors. © 2002 Society of Systematic Biologists.Fil: Szumik, Claudia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; ArgentinaFil: Cuezzo, Fabiana del Carmen. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; ArgentinaFil: Goloboff, Pablo Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; ArgentinaFil: Chalup, Adriana Elizabeth. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentin