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1.
Supplementary material for paper Comparison of the evolution of the COVID-19 disease between Romania and Italy
Ciprian Chiruţa, Emilian Bulgariu, Jurij Avsec, Brigita Ferčec, Matej Mencinger, 2020, complete scientific database or corpus

Keywords: COVID-19 pandemic evolution, time dependent SIR model, coronavirus
Published: 23.12.2020; Views: 277; Downloads: 582
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2.
Comparison of the evolution of the COVID-19 disease between Romania and Italy
Ciprian Chiruţa, Emilian Bulgariu, Jurij Avsec, Brigita Ferčec, Matej Mencinger, 2020, original scientific article

Abstract: After the outbreak of COVID-19 in Italy, thousands of Romanian citizens who worked in Northern Italy, Spain or Germany returned to Romania. Based on the time-dependent susceptible–infected–recovered—SIR model, this paper compares the evolution of the COVID-19 disease between Romania and Italy, assuming that the parameter value of R0 in the time-dependent SIR model decreases to R1 < R0 after publicly announced restrictions by the government, and increases to a value of R2 < R1 when the restrictions are lifted. Among other things, we answer the questions about the date and extent of the second peak in Italy and Romania with respect to different values of R2 and the duration of the restrictions.
Keywords: COVID-19 pandemic evolution, time dependent SIR model, coronavirus
Published: 22.12.2020; Views: 193; Downloads: 76
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3.
Technological valley of death as an emergent evolutionary phenomenon
Petra Fic, 2019, master's thesis

Abstract: Perceptual researchers often argue that natural selection supports veridical perceptions, respectively those that accurately reflect the environment. They also claim that beings whose perceptions are truer are also more fit. This assumption was tested using standard tools of evolutionary game theory in a simple environment. The result was that more veridical perceptions are not necessarily more successful. In the majority of the parameter space, veridical perceptions are extinct in competition with simplified perceptions, based on adaptive behavior in a given environment. In the thesis, we build upon mentioned territorial games introduced by Mark, Marion, and Hoffman in 2010, and extend four of their territory perception and selection strategies with two novel ones that together constitute a model of technological readiness valley of death. Whenever utility of a resource is not monotonous in the amount of that resource, the technological valley of death emerges. While the development of the science behind these models is in its infancy, modeling and understanding the phenomenon may shed light on progress and related phenomena in society.
Keywords: evolution, perception, utility, Monte Carlo simulation, game theory
Published: 22.11.2019; Views: 455; Downloads: 61
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4.
Differential evolution and large-scale optimization applications
Aleš Zamuda, scientific or documentary film, sound or video publication

Abstract: Differential Evolution (DE) is one of the most popular, high-performance optimization algorithms with variants that have been outperforming others for years. As a result, DE has grown to accommodate wide usage for a variety of disciplines across scientific fields. Differential Evolution and Large-Scale Optimization Applications presents a research-based overview and cross-disciplinary applications of optimization algorithms. Emphasizing applications of Differential Evolution (DE) across sectors and laying the foundation for further use of DE algorithms in real-world settings, this video is an essential resource for researchers, engineers, and graduate-level students. Topics Covered : Algorithms, Optimization, Parallel Differential Evolution, Performance Improvement, Stochastic Methods, Tree Model Reconstruction.
Keywords: differential Evolution, optimization, algorithms, stochastic methods, tree models, tree model reconstruction
Published: 14.05.2019; Views: 574; Downloads: 157
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5.
Multi-objective optimization algorithms with the island metaheuristic for effective project management problem solving
Christina Brester, Ivan Ryzhikov, Eugene Semenkin, 2017, original scientific article

Abstract: Background and Purpose: In every organization, project management raises many different decision-making problems, a large proportion of which can be efficiently solved using specific decision-making support systems. Yet such kinds of problems are always a challenge since there is no time-efficient or computationally efficient algorithm to solve them as a result of their complexity. In this study, we consider the problem of optimal financial investment. In our solution, we take into account the following organizational resource and project characteristics: profits, costs and risks. Design/Methodology/Approach: The decision-making problem is reduced to a multi-criteria 0-1 knapsack problem. This implies that we need to find a non-dominated set of alternative solutions, which are a trade-off between maximizing incomes and minimizing risks. At the same time, alternatives must satisfy constraints. This leads to a constrained two-criterion optimization problem in the Boolean space. To cope with the peculiarities and high complexity of the problem, evolution-based algorithms with an island meta-heuristic are applied as an alternative to conventional techniques. Results: The problem in hand was reduced to a two-criterion unconstrained extreme problem and solved with different evolution-based multi-objective optimization heuristics. Next, we applied a proposed meta-heuristic combining the particular algorithms and causing their interaction in a cooperative and collaborative way. The obtained results showed that the island heuristic outperformed the original ones based on the values of a specific metric, thus showing the representativeness of Pareto front approximations. Having more representative approximations, decision-makers have more alternative project portfolios corresponding to different risk and profit estimations. Since these criteria are conflicting, when choosing an alternative with an estimated high profit, decision-makers follow a strategy with an estimated high risk and vice versa. Conclusion: In the present paper, the project portfolio decision-making problem was reduced to a 0-1 knapsack constrained multi-objective optimization problem. The algorithm investigation confirms that the use of the island meta-heuristic significantly improves the performance of genetic algorithms, thereby providing an efficient tool for Financial Responsibility Centres Management.
Keywords: 0-1 multi-objective constrained knapsack problem, project management portfolio problem, multi-objective evolution-based optimization algorithms, collaborative and cooperative meta-heuristics
Published: 04.05.2018; Views: 721; Downloads: 214
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6.
Understanding management concepts through development of their tool box
Marek Ćwiklicki, 2016, review article

Abstract: This paper offers an alternative approach to defining the management concept. The proposed methodology relies on the identification of tools supporting the given concept. The author assumed that the identification of tools’ evolution gives clearer insights into circumstances of constant development of—by its nature—a more general concept. The tools’ classification resembles a phylogenic tree and is based on the idea of an affinity diagram. To provide the proof for such reasoning, the total quality management (TQM) concept was chosen. This proposition can be useful for better understanding origins and the development of management thought. It clarifies relationships among methods constituting frameworks of quality management.
Keywords: management concept, evolution, tools, total quality management
Published: 14.11.2017; Views: 665; Downloads: 80
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7.
A programming language independent framework for metrics-based software evolution and analysis
Črt Gerlec, Gordana Rakić, Zoran Budimac, Marjan Heričko, 2012, original scientific article

Abstract: Knowledge about different aspects of software quality during software evolution can be valuable information for developers and project managers. It helps to reduce the number of defects and improves the internal structure of software. However, determining softwarećs quality and structure in heterogeneous systems is a difficult task. In this paper, a programming language independent framework for evaluating software metrics and analyzing software structure during software development and its evolution will be presented. The framework consists of the SMIILE tool for calculation of software metrics, extended with an analysis of software structure. The data are stored in a central repository via enriched Concrete Syntax Tree (eCST) for universal source code representation. The framework is demonstrated in a case study. The development of such a framework is a step forward to consistent support for software evolution by providing a change analysis and quality control. The significance of this consistency is growing today, when software projects are more complex, consisting of components developed in diverse programming languages.[Acknowledgments. Work of the second and third author is partially supported by the Serbian Ministry of Science and Technological Development through project no. OI174023 ĆIntelligent Techniquesand Their Integration into Wide-Spectrum Decision SupportĆ. Bilateral project between Slovenian Research Agency and Serbian Ministry of Science and Technological Development (Grant BI-SR/10-11-027) enabled the exchange of visits and ideas between authors of this paper and their institutions.]
Keywords: software evolution, software development, quality, structure, metrics
Published: 06.07.2017; Views: 801; Downloads: 280
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8.
Self-organization of progress across the century of physics
Matjaž Perc, 2013, original scientific article

Abstract: We make use of information provided in the titles and abstracts of over half a million publications that were published by the American Physical Society during the past 119 years. By identifying all unique words and phrases and determining their monthly usage patterns, we obtain quantifiable insights into the trends of physics discovery from the end of the 19th century to today. We show that the magnitudes of upward and downward trends yield heavy-tailed distributions, and that their emergence is due to the Matthew effect. This indicates that both the rise and fall of scientific paradigms is driven by robust principles of self-organization. Data also confirm that periods of war decelerate scientific progress, and that the later is very much subject to globalisation.
Keywords: self-organization, preferential attachment, evolution of progress, history of physics, statistical physics of social systems
Published: 23.06.2017; Views: 583; Downloads: 231
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9.
Optimal robust motion controller design using multi-objective genetic algorithm
Andrej Sarjaš, Rajko Svečko, Amor Chowdhury, 2014, original scientific article

Abstract: This paper describes the use of a multi-objective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with non-negativity conditions. Regional pole placement method is presented with the aims of controllers% structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multi-objective function is composed of different unrelated criteria such as, robust stability, controllers' stability and time performance indexes of closed loops. The design of controllers and multi-objective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm - Differential evolution.
Keywords: disturbance observer, DOB, uncertainty systems, optimal robust control, multi-objective optimization, differential evolution
Published: 15.06.2017; Views: 671; Downloads: 287
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10.
A hybrid bat algorithm
Iztok Fister, Dušan Fister, Xin-She Yang, 2013, original scientific article

Keywords: swarm intelligence, bat algorithm, differential evolution, optimization
Published: 21.12.2015; Views: 1095; Downloads: 9
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