Pub. online:1 Jan 2018Type:Research ArticleOpen Access
Journal:Informatica
Volume 29, Issue 1 (2018), pp. 21–39
Abstract
The heliostat field of Solar Central Receiver Systems takes up to 50% of the initial investment and can cause up to 40% of energetic loss in operation. Hence, it must be carefully optimized. Design procedures usually rely on particular heliostat distribution models. In this work, optimization of the promising biomimetic distribution model is studied. Two stochastic population-based optimizers are applied to maximize the optical efficiency of fields: a genetic algorithm, micraGA, and a memetic one, UEGO. As far as the authors know, they have not been previously applied to this problem. However, they could be a good option according to their structure. Additionally, a Brute-Force Grid is used to estimate the global optimum and a Pure-Random Search is applied as a baseline reference. Our empirical results show that many different configurations of the distribution model lead to very similar solutions. Although micraGA exhibits poor performance, UEGO achieves the best results in a reduced time and seems appropriate for the problem at hand.
Journal:Informatica
Volume 27, Issue 2 (2016), pp. 323–334
Abstract
This paper reviews the interplay between global optimization and probability models, concentrating on a class of deterministic optimization algorithms that are motivated by probability models for the objective function. Some complexity results are described for the univariate and multivariate cases.
Journal:Informatica
Volume 22, Issue 4 (2011), pp. 471–488
Abstract
We describe an adaptive algorithm for approximating the global minimum of a continuous univariate function. The convergence rate of the error is studied for the case of a random objective function distributed according to the Wiener measure.
Journal:Informatica
Volume 10, Issue 1 (1999): Special Issue on Programming Theory, Information System Engineering, Software Engineering, and Artificial Intelligence, pp. 109–126
Abstract
This article provides a brief introduction to an approach toward data conversion development. The article discusses activities in the area of conversion software development, as well as a model for the life cycle of this development process. Also analyzed is a possible method of tool support for the development process.
Journal:Informatica
Volume 3, Issue 2 (1992), pp. 241–246
Abstract
The Freudian psychoanalysis in its modern form assumes that activities of a patient depend on his physical and mental state (“energy”), and result in maintaining his life, in useless waste of his energy (“symptoms”), and in (“useful”) contribution to the society and to patient's energy level.
Another contribution to patient's energy level comes from the society. It comprises life amenities, medication, and “education”. Patient's mental state is characterized by two parameters, “symbolic” and “imaginary”. Both parameters affect the outcome of patient activities, and are affected by contributions to his “energy”.
A mathematical description of this model as a dynamical system is presented. Significance of obtained solutions for psychoanalysis is discussed.