Application of evolutionary rietveld method based XRD phase analysis and a self-configuring genetic algorithm to the inspection of electrolyte composition in aluminum electrolysis baths

The technological inspection of the electrolyte composition in aluminum production is performed using calibration X-ray quantitative phase analysis (QPA). For this purpose, the use of QPA by the Rietveld method, which does not require the creation of multiphase reference samples and is able to take into account the actual structure of the phases in the samples, could be promising. However, its limitations are in its low automation and in the problem of setting the correct initial values of profile and structural parameters. A possible solution to this problem is the application of the genetic algorithm we proposed earlier for finding suitable initial parameter values individually for each sample. However, the genetic algorithm also needs tuning. A self-configuring genetic algorithm that does not require tuning and provides a fully automatic analysis of the electrolyte composition by the Rietveld method was proposed, and successful testing results were presented. © 2018 by the authors. Licensee MDPI, Basel, Switzerland

Automated Toolkit for Encouraging a Producer to Use Innovative Technologies in Environmentally Oriented Economic Development of Mining Regions

The automated toolkit for assessing environmental and investment attractiveness of a mining region and the results of its application are discussed in the article. This toolkit includes the optimization mathematical model, the algorithms for the interaction between a regional control center and a producer within the territory, as well as the automated software package for their analysis. The use of the optimization mathematical model makes it possible to take into account the maximum economic potential of a producer, which determines, respectively, a mining region’s environment pollution potential. Accounting for environmental risks will allow the control center or other decision makers to identify not only the optimal pattern of eco-economic interaction in the region, but also reflect changes in the environmental and investment climate as a combination of economic potential and involved risks. The model and the algorithms of interaction between a regional control center and a producer, as well as the results of their numerical analysis given in this paper, allow considering this toolkit as an effective decision support tool aimed at improving environmental and investment attractiveness of a mining region by encouraging a producer to use the best available technologies and conserve the natural environment

Application of Evolutionary Rietveld Method Based XRD Phase Analysis and a Self-Configuring Genetic Algorithm to the Inspection of Electrolyte Composition in Aluminum Electrolysis Baths

The technological inspection of the electrolyte composition in aluminum production is performed using calibration X-ray quantitative phase analysis (QPA). For this purpose, the use of QPA by the Rietveld method, which does not require the creation of multiphase reference samples and is able to take into account the actual structure of the phases in the samples, could be promising. However, its limitations are in its low automation and in the problem of setting the correct initial values of profile and structural parameters. A possible solution to this problem is the application of the genetic algorithm we proposed earlier for finding suitable initial parameter values individually for each sample. However, the genetic algorithm also needs tuning. A self-configuring genetic algorithm that does not require tuning and provides a fully automatic analysis of the electrolyte composition by the Rietveld method was proposed, and successful testing results were presented

Применение самоконфигурируемого генетического алгоритма для управлeния человеческими ресурсами

This paper describes the problem of human resource management which can appear in many organiza- tions during restructuration periods. The problem is simulated by a dynamic model, similar to a supply chain model with several ranks. The problem of finding the optimal combination of transition coefficients, including the fluctuation coefficients, is transformed into an optimization problem. To solve this prob- lem, a self-configuring genetic algorithm is applied with several constraint handling methods. Additional constraints are defined in order to avoid undesirable oscillations in the system. The results show that this problem can be efficiently solved by the presented methodsВ данной статье описывается задача управления человеческими ресурсами, которая может быть актуальной для организаций в период реструктуризации. Поведение системы описывается динамической имитационной моделью, аналогичной модели цепи поставок с несколькими ранга- ми. Поиск оптимальной комбинации передаточных коэффициентов, включающих также коэф- фициенты флуктуаций, сводится к задаче оптимизации. Для решения этой задачи применяет- ся самоконфигурируемый генетический алгоритм с несколькими методами учета ограничений. Ограничения в данной проблеме возникают в связи с необходимостью избежать нежелатель- ных осцилляций в системе. Результаты показывают, что поставленная задача может быть эффективно решена предложенными методам

Применение самоконфигурируемого генетического алгоритма для управлeния человеческими ресурсами

This paper describes the problem of human resource management which can appear in many organiza- tions during restructuration periods. The problem is simulated by a dynamic model, similar to a supply chain model with several ranks. The problem of finding the optimal combination of transition coefficients, including the fluctuation coefficients, is transformed into an optimization problem. To solve this prob- lem, a self-configuring genetic algorithm is applied with several constraint handling methods. Additional constraints are defined in order to avoid undesirable oscillations in the system. The results show that this problem can be efficiently solved by the presented methodsВ данной статье описывается задача управления человеческими ресурсами, которая может быть актуальной для организаций в период реструктуризации. Поведение системы описывается динамической имитационной моделью, аналогичной модели цепи поставок с несколькими ранга- ми. Поиск оптимальной комбинации передаточных коэффициентов, включающих также коэф- фициенты флуктуаций, сводится к задаче оптимизации. Для решения этой задачи применяет- ся самоконфигурируемый генетический алгоритм с несколькими методами учета ограничений. Ограничения в данной проблеме возникают в связи с необходимостью избежать нежелатель- ных осцилляций в системе. Результаты показывают, что поставленная задача может быть эффективно решена предложенными методам