As companies operate in a competitive environment, where the struggle for survival on the market is rather tough, the top management face new challenges to identify methods, and even techniques, which allows it to select from the market those assets that provide an optimal ratio between the acquisition cost and the economic performance. In this context, a fuzzy logic managerial decision tool for the assets acquisition is proposed with the paper. The algorithm has three main components: the matrix of the membership degree of the existing bids to asset selection criteria, using fuzzy triangular numbers; the vector of the global membership degree of the bids to the selection criteria and the maximum of the global membership degree as an inference operator for establishing the validated bids by the algorithm. Two scenarios of asset acquisition were tested. After simulations, it was determined that the proposed fuzzy logic managerial decision tool combines, with very good results, the acquisition cost of the assets with their economic performance.

This research sets the basis for modeling the performance indicators of financial assets using triangular neutrosophic fuzzy numbers. This type of number allows for the modeling of financial assets performance indicators by taking into consideration all the possible scenarios of their achievement. The key performance indicators (KPIs) modeled with the help of triangular fuzzy neutrosophic numbers are the return on financial assets, the financial assets risk, and the covariance between financial assets. Thus far, the return on financial assets has been studied using statistical indicators, like the arithmetic and geometric mean, or using the financial risk indicators with the help of the squared deviations from the mean and covariance. These indicators are well known as the basis of portfolio theory. This paper opens the perspective of modeling these three mentioned statistical indicators using triangular neutrosophic fuzzy numbers due to the major advantages they have. The first advantage of the neutrosophic approach is that it includes three possible symmetric scenarios of the KPIs achievement, namely the scenario of certainty, the scenario of non-realization, and the scenario of indecision, in which it cannot be appreciated whether the performance indicators are or are not achieved. The second big advantage is its data series clustering, representing the financial performance indicators by which these scenarios can be delimitated by means of neutrosophic fuzzy numbers in very good, good or weak performance indicators. This clustering is realized by means of the linguistic criteria and measuring the belonging degree to a class of indicators using fuzzy membership functions. The third major advantage is the selection of risk mitigation analysis scenarios and the formation of financial assets’ optimal portfolios.

As the evacuation problem has attracted and continues to attract a series of researchers due to its high importance both for saving human lives and for reducing the material losses in such situations, the present paper analyses whether the evacuation doors configuration in the case of classrooms and lecture halls matters in reducing the evacuation time. For this aim, eighteen possible doors configurations have been considered along with five possible placements of desks and chairs. The doors configurations have been divided into symmetrical and asymmetrical clusters based on the two doors positions within the room. An agent-based model has been created in NetLogo which allows a fast configuration of the classrooms and lecture halls in terms of size, number of desks and chairs, desks and chair configuration, exits' size, the presence of fallen objects, type of evacuees and their speed. The model has been used for performing and analyzing various scenarios. Based on these results, it has been observed that, in most cases, the symmetrical doors configurations provide good/optimal results, while only some of the asymmetrical doors configurations provide comparable/better results. The model is configurable and can be used in various scenarios.Symmetry 2020, 12, 627 2 of 25 demonstrated the beneficial effect of such an obstacle, a series of other studies have followed [28], some of them revealing a smaller positive effect [29,30], others stating the influence based on the dimension and position of the obstacle [31], while others proving the ineffectiveness of such a situation [32,33]. In a recent paper, Zuriguel et al. [34] studied the effect of an obstacle placed in front of the exit, and the authors concluded that this situation slightly favors the evacuation of the persons near the wall, prompting a debate on the role of the column in an evacuation process. Even more, the role of the exit location is questioned in Wu et al. [3], in which the authors conduct an experiment using mice and changing the position of the exit door by moving it from the long to the short wall of the test container.Depending on the type of the environment in which the evacuation might take place, a series of studies in the literature have addressed the evacuation of ships [35], metro stations [11,36], metro trains and high-speed trains [37,38], hospitals [39,40], stadiums [41], concert halls [42], supermarkets [43], rooms [34,44], auditorium [45], classrooms and lecture halls [18,46,47], ascending stair evacuation [48], large indoor building spaces [49], large buildings [50], large exterior spaces [51], etc.Among the public building evacuation situations, classrooms and the lecture halls hold an important place, as these spaces generally present a high population density and a restrained evacuation capacity [18,52]. The seat and desk placement among these types of learning rooms can take various forms, which, combined with the exit doors' positions, can have an impact on the overall evacuation time [53]. Furthermore, the complexity of the i...

Purpose The purpose of this paper is to focus on the adjustment of the GM(1, 2) errors for financial data series that measures changes in the public sector financial indicators, taking into account that the errors in grey models remain a key problem in reconstructing the original data series. Design/methodology/approach Adjusting the errors in grey models must follow some rules that most often cannot be determined based on the chaotic trends they register in reconstructing data series. In order to ensure the adjustment of these errors, for improving the robustness of GM(1, 2), was constructed an adaptive fuzzy controller which is based on two input variables and one output variable. The input variables in the adaptive fuzzy controller are: the absolute error ε i 0 ( k ) [ % ] of GM(1, 2), and the distance between two values x i 0 ( k ) [ % ] , while the output variable is the error adjustment A ε i 0 ( k ) [ % ] determined with the help of the above-mentioned input variables. Findings The adaptive fuzzy controller has the advantage that sets the values for error adjustments by the intensity (size) of the errors, in this way being possible to determine the value adjustments for each element of the reconstructed financial data series. Originality/value To ensure a robust process of planning the financial resources, the available financial data are used for long periods of time, in order to notice the trend of the financial indicators that need to be planned. In this context, the financial data series could be reconstituted using grey models that are based on sequences of financial data that best describe the status of the analyzed indicators and the status of the relevant factors of influence. In this context, the present study proposes the construction of a fuzzy adaptive controller that with the help of the output variable will ensure the error’s adjustment in the reconstituted data series with GM(1, 2).

Abstract:The fuzzy logic system developed in this research paper seeks to identify the financial risk of projects financed from structural funds when changes occur in project values, in the duration of the projects and in the implementation durations. Those two factors are known to influence the financial risk. The fuzzy system was simulated using Matlab and the results showed its operation and the conclusion that the financial risk of the project is dependent on the developments values and on the implementation duration. The developed and tested fuzzy logic system provides information on financial risk intensity organized into three categories: small, medium and large and on the inflection point of transition from low risk to high risk. This is considered an early warning system for the management staff with responsibilities in structural funds.

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This paper focuses on the environmental conflicts induced by insufficient continuous snow cover on the ski areas in Romania. The case study aims envisions the area of Southern Carpathians, Latoriței Mountains, belonging to the group of Parâng Mountains. The area chosen to develop and improve the artificial snow system was conducted for in the proposed ski area, Obârşia Lotrului. This fulfilled a necessary condition (geomorphological and climatic) for the development of the ski domain. The methodology focuses on two main stages phases. In the first stage phase, based on the GIS, the areas that have shown problems in terms of continuity of the snow layer and its thickness were identified, while the second phase, there is a supposed optimization based on Fuzzy logic for the installation of artificial snow. The corresponding thickness of snow for a longer period of time can lead to a higher socio-economic efficiency, as well as the increase of the use duration of the respective ski area, and also a prevention mechanism to environmental conflicts that may arise. The proposed study supports civil society by optimizing artificial snow machines through a positive impact on water resources allocated to a ski area in order to maintain a continuous snow cover.

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