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1

LEAS: An AI-based Demonstrator as Decision Support Tool for Traffic Monitoring at VTS Centers

Stach Thomas, Koch Paul

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2025

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Vol. 19 No. 1

301--308

EN

Maritime traffic is prevalent worldwide, with particularly high density in coastal waters. To ensure safety and efficiency, Vessel Traffic Service (VTS) centers monitor and coordinate maritime traffic. For this purpose, VTS centers utilize various sensor and communication technologies such as radar, Automatic Identification System (AIS), electro-optical systems or radio communication. Additionally, any Vessel Traffic Service Operator (VTSO) is motivated to utilize a Decision Support Tool (DST). The LEAS project addresses emerging challenges at VTS centers. One key challenge results from the continuous evolution of maritime traffic, in particular, its ever increasing automation and autonomization. Another key challenge is the growing shortage of skilled workers. Consequently, it is crucial to process increasing volume of maritime traffic data while maintaining or improving safety and efficiency. DSTs at VTS centers must be adapted to these emerging challenges, accordingly. In the LEAS project, we develop and evaluate a demonstrator which represents a DST. This demonstrator is being developed in close collaboration with VTSOs to address these challenges. Most notably, it has a situation detection which makes use of Artificial Intelligence (AI) methods and displays relevant information in an intuitive Human-Machine Interface (HMI). The demonstrator is evaluated using simulated traffic scenarios in the German Bight and Baltic Sea, with VTSOs as test subjects. This paper provides an overview of the project and demonstrator. First, we introduce the key requirements for the demonstrator and discuss their impact on the system architecture. Next, we present its AI-based situation detection. We explain the underlying formalism of the situation detection and resolution as well as its implementation in the demonstrator. Finally, we evaluate the capabilities and limitations. The paper concludes with an outlook to future work with focus on potential deployment at DST at VTS centers.

2

Dependence of the Maximum Approach Distance on the Shape of the Ship's Safe Domain

Burmaka Igor, Zhukov Dmytro

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2025

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Vol. 19 No. 1

265--268

EN

In work analytical expressions are resulted for a calculation minimum - possible distance of rapprochement in the case of application of domains of elliptic and difficult form. Shown graphic dependence minimum - possible distance of rapprochement from foreshortening of ships which are drawn together, for the domains of both types. It is shown that the domains of elliptic and difficult form have a similar character of change minimum - possible distance of rapprochement depending on foreshortening of ships.

3

Zastosowanie telemetrycznego monitoringu w czasie rzeczywistym jako podstawa Systemu Wspierania Decyzji dla Zbiornika Sulejowskiego

Chamerska Aleksandra, Skąpski Ksawery, Jarosiewicz Paweł, Izydorczyk Katarzyna, Biernacki Mariusz, Frątczak Wojciech

Gospodarka Wodna

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2023

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Nr 10

13--15

PL

Antropopresja wywiera znaczący wpływ na ekosystemy wodne, stwarzając pilną potrzebę skutecznego monitoringu i zarządzania wodami powierzchniowymi, zwłaszcza w kontekście postępującej eutrofizacji. Rozwiązaniem, które może przyczynić się do poprawy efektywności podejmowania decyzji w zarządzaniu zlewniowym, jest monitoring w czasie rzeczywistym (monitoring real-time). Wydłużony czas reakcji, brak ciągłości wyników i niepewność wynikająca z pracy próbkobiorcy to główne ograniczenia tradycyjnych metod monitoringowych. Dlatego technologie monitorowania wody w czasie rzeczywistym są obiecującym rozwiązaniem pozwalającym przezwyciężyć ograniczenia tradycyjnych metod. W artykule została przedstawiona koncepcja pilotażowej telemetrycznej sieci stacji monitoringu real-time w zlewni rzeki Pilicy, która powstała w ramach projektu LIFE Pilica. Monitoring w czasie rzeczywistym, współdziałający z ekohydrologiczną wiedzą naukową, umożliwia dogłębne zrozumienie „pulsacji” ekosystemów wodnych oraz dynamiki transportu zanieczyszczeń biogenicznych. Ta synergia może w przyszłości umożliwić podejmowanie bardziej świadomych decyzji w zakresie zarządzania zasobami wodnymi, zwłaszcza pod kątem zapobiegania eutrofizacji.

EN

Anthropopressure has a significant impact on water ecosystems, resulting in an urgent need for efficient surface waters monitoring and management, especially in the context of the progressing eutrophication. A solution that may contribute to the improvement of the catchment area management decision-making efficiency is the real-time monitoring. Extended reaction times, lack of continuity of results and incertitude related to the work of persons taking samples are the main limitations of the conventional monitoring methods. Therefore, real-time water monitoring technologies are a promising solution that may eliminate the constraints related to traditional methods. The article presents the concept of a pilot real-time telemetric monitoring stations network in the Pilica river basin under the LIFE Pilica project. Real-time monitoring combined with ecohydrological scientific knowledge allows for a deep understanding of the water ecosystems 'pulsations' and the biogenic pollutions transport dynamics. In the future, this synergy may lead to taking more informed decisions in the scope of water resources management, especially in order to prevent the eutrophication.

4

Prediction of Selected Mechanical Properties in Austempered Ductile Iron with Different Wall Thickness by the Decision Support Systems

Jaśkowiec Krzysztof, Opaliński Andrzej, Kustra Piotr, Jach D., Wilk-Kołodziejczyk Dorota

Archives of Foundry Engineering

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2023

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Vol. 23, iss. 2

137--144

EN

The structure of Austempered Ductile Iron (ADI) is depend of many factors at individual stages of casting production. There is a rich literature documenting research on the relationship between heat treatment and the resulting microstructure of cast alloy. A significant amount of research is conducted towards the use of IT tools for indications production parameters for thin-walled castings, allowing for the selection of selected process parameters in order to obtain the expected properties. At the same time, the selection of these parameters should make it possible to obtain as few defects as possible. The input parameters of the solver is chemical composition Determined by the previous system module. Target wall thickness and HB of the product determined by the user. The method used to implement the solver is the method of Particle Swarm Optimization (PSO). The developed IT tool was used to determine the parameters of heat treatment, which will ensure obtaining the expected value for hardness. In the first stage, the ADI cast iron heat treatment parameters proposed by the expert were used, in the next part of the experiment, the settings proposed by the system were used. Used of the proposed IT tool, it was possible to reduce the number of deficiencies by 3%. The use of the solver in the case of castings with a wall thickness of 25 mm and 41 mm allowed to indication of process parameters allowing to obtain minimum mechanical properties in accordance with the PN-EN 1564:2012 standard. The results obtained by the solver for the selected parameters were verified. The indicated parameters were used to conduct experimental research. The tests obtained as a result of the physical experiment are convergent with the data from the solver.

5

Binary Classification of Agricultural Crops Using Sentinel Satellite Data and Machine Learning Techniques

Bertellini Paolo, D'Addese Gianluca, Franchini Giorgia, Parisi Simone, Scribano Carmelo, Zanirato Daniele, Bertogna Marko

Annals of Computer Science and Information Systems

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2023

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Vol. 35

859--864

EN

The advent of high-resolution satellite imagery, such as Sentinel 1 and Sentinel 2, has provided valuable data for various applications, including crop classification. This paper presents a study on the classification of agricultural fields using indices derived from Sentinel satellite imagery. Specifically, we focus on creating binary classifiers capable of distinguishing between different crops, namely Tomatoes, Soy, Sugar Beets, Rice, and Wheat. The paper investigates various preprocessing techniques to create a dataset suitable for machine learning methods, such as Random Forests, which require a fixed number of features. Additionally, we demonstrate that linear interpolation and out-of-scale values have equivalent performance in terms of classification accuracy. Furthermore, we address the issue of imbalanced datasets commonly encountered in agricultural field classification. We explore different balancing techniques that can significantly improve the performance of machine learning methodologies. The motivation for this work stems from the growing interest in Agriculture 4.0, and it serves as a valuable tool to verify farmers' claims, especially in relation to state subsidies for specific crops of interest. Understanding the crop type present in the field represents highly valuable information that can serve as a foundation for subsequent analyses or as input for calibrating models, such as Decision Support Systems. Overall, this study contributes to the field of agricultural research and provides insights into the application of Machine Learning techniques for crop classification using satellite imagery. The findings offer practical implications for monitoring and optimizing agricultural practices in the context of precision farming and sustainable agriculture.

6

Conceptual Model Creation for Automated Self-training System of Functional Control and Detection of Railway Transport

Oralbekova Ayaulym, Amanova Marzhana, Rustambekova Kamila, Kaskatayev Zhanat, Kisselyova Olga, Nurgaliyeva Roza

International Journal of Electronics and Telecommunications

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2021

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Vol. 67, No. 4

603--608

EN

In order to improve the operational reliability and service life of the main systems, components and assemblies (SCA) of railway transport (RT), it is necessary to timely detect (diagnose) their defects, including the use of the methods of intellectual analysis and data processing. One of the promising approaches to the synthesis of the SCA functional control system is the use of intelligent technology (INTECH) methods. This technology is based on maximizing the information capacity of an automated decision support system for detecting faults during its training.

7

Mining clinical pathways for daily insulin therapy of diabetic children

Deja Rafal, Froelich Wojciech, Deja Grazyna

International Journal of Applied Mathematics and Computer Science

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2021

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Vol. 31, no. 1

107--121

EN

We propose a decision support framework (DSF) assisting insulin therapy of diabetic children. Our DSF relies on a medical treatment graph (MTG), which models and graphically represents clinical pathways. Using the MTG, it is possible to plan and adapt medical decisions dependent upon the current health state of a patient and the progress of the treatment. Our MTG fits well with the requirements of clinical practice. The presented work is a cooperative effort of researchers in computer science and medicine. The MTG model has been thoroughly tested and validated using real-world clinical data. The usefulness of the approach has been confirmed by physicians.

8

An AHP-based Decision Support System for Personnel Selection for Manager Position in Businesses

Calp Muhammed Hanefi, Agarwal Shivani

Annals of Computer Science and Information Systems

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2021

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Vol. 28

1--7

EN

Humanity is one of the most important resources for businesses. Because, with human resources, the data of the institution can be obtained and information can be produced by processing. Thus, human resources make the business a learning and dynamic organization and ensure its continuity. In enterprises, personnel selection (in terms of quantity or quality) is carried out within the scope of Human Resources Management. This selection process usually takes place when a group of decision makers evaluates the candidates according to some criteria and their own opinions. However, this situation prevents an objective and fair selection. For this reason, in this study, a decision support system (DSS) has been developed by using the Analytical Hierarchy Process (AHP), one of the Multi-Criteria Decision Making (MCDM) methods, to ensure objectivity and to select the most suitable personnel for the job description. The said DSS provides the selection of the marketing manager among the personnel working in an enterprise. For this, the 10 employees working in the marketing department of the enterprise for the longest time were taken into account. When the results are examined, it is seen that the most qualified personnel can be selected successfully in cases where customer satisfaction, performance value and number of projects are prioritized

9

Application of the Decision Support System RODOS in the Event of Nuclear Reactor Accident with Scenario of Release of Radioactive Isotopes to the Atmosphere

Jaroszek Adam Sylwester

Prace Instytutu Elektrotechniki

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2020

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Z. 281

49--60

PL

Systemy wspomagania decyzji cieszą się coraz większą popularnością ze względu na szybkie dostarczanie informacji o rozwoju sytuacji radiacyjnej po awarii jądrowej z uwolnieniem izotopów promieniotwórczych do powietrza atmosferycznego. Systemy te są wykorzystywane jako narzędzie bezpośrednio stosowane w sytuacji awaryjnej oraz jako narzędzie do przeprowadzenia przed inwestycyjnych obliczeń z zakresu planowania awaryjnego. Artykuł przedstawia podstawowe funkcjonalności systemu wspomagania decyzji RODOS. Program służy do przeprowadzania prognoz rozwoju zdarzeń radiacyjnych z uwolnieniem izotopów promieniotwórczych do atmosfery w wyniku awarii w elektrowniach jądrowych.

EN

Decision support systems are increasingly popular due to the fast delivery of information about development of the situation during the nuclear accidents. The information provided by decision support systems facilitate proper selection of necessary protective actions and correct allocation of services involved in the activities. The RODOS system is designed for forecasting the dispersion of radioactive isotopes in the atmosphere. It can be used in case of real radiological nuclear emergency as well as for emergency preparedness purpose.

10

Wyznaczanie kluczowych wskaźników wydajności procesu produkcyjnego – część II: badania przemysłowe

Król Dariusz, Skowroński Jan, Zaręba Maciej, Bartecki Krzysztof

Pomiary Automatyka Robotyka

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2020

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R. 24, nr 3

19--28

PL

Zastosowanie nowych technologii w Przemyśle 4.0 umożliwia lepszą organizację, monitorowanie, kontrolę oraz skuteczną optymalizację procesów produkcyjnych, szczególnie w zakresie wydajności. Prezentowane rozwiązanie opiera się na hierarchicznej analizie wskaźników efektywności, w tym głównie na kontroli wskaźnika ogólnej efektywności zasobów produkcyjnych OEE. Rosnąca liczba możliwych do uzyskania skwantyfikowanych sygnałów monitorujących pracę maszyn, temperaturę otoczenia czy częstotliwość drgań sprawia, że narzędzia wspomagające decyzje są coraz bardziej wyrafinowane i, poza prezentacją obecnego stanu zasobów, coraz częściej obejmują także analizę predykcyjną. Opisywane narzędzie PUPMT pozwala zidentyfikować kluczowe zdarzenia, które mają istotny wpływ na bieżącą lub przyszłą efektywność produkcji. Umożliwia także analizę typu what-if, dopuszczając symulację wpływu projektowanych zmian, a wyniki tej symulacji uzależnia od skutków podobnych zmian, które miały miejsce w przeszłości w danym przedsiębiorstwie. Dzięki automatycznej identyfikacji potencjalnych zależności rozwiązanie dostosowuje się do specyfiki firmy lub wybranej jednostki produkcyjnej. Początkowe rozdziały zawierają m.in. opis najważniejszych metod wykorzystywanych w rozwiązaniu PUPMT. W dalszej części przedstawiono wybrane wyniki badań przemysłowych, które przeprowadzono na kilkudziesięciu jednostkach produkcyjnych.

EN

The use of new technologies in Industry 4.0 enables better organization, monitoring, control and effective optimization of production processes, especially in terms of efficiency. The solution is based on a hierarchical analysis of key performance indicators, including mainly the control of Overall Equipment Effectiveness (OEE). The growing number of quantifiable signals monitoring machine operation, ambient temperature or even the frequency of vibrations makes decision support tools more and more sophisticated. Moreover, they also include predictive analysis in addition to presentations of the current state of resources. PUPMT tool allows identifying key events that have a significant impact on current or future production efficiency. It also allows the what-iftype analysis, running the simulation of the impact of the proposed changes, and the results of this simulation depend on the effects of similar changes that occurred in the past in a given enterprise. Thanks to the automatic identification of potential dependencies, the proposed solution adapts to the specifics of a given company or even a selected production unit. The paper in the first part contains a description of the essential methods used in the PUPMT tool. The second part presents selected results of industrial research, which were carried out on several dozen production units.

11

Multi-criteria comparative analysis of the use of subtractive and additive technologies in the manufacturing of offshore machinery components

Deja Mariusz, Siemiątkowski Mieczysław Stanisław, Zieliński Dawid

Polish Maritime Research

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2020

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nr 3

71--81

EN

The dynamic development of additive manufacturing technologies, especially over the last few years, has increased the range of possible industrial applications of 3D printed elements. This is a consequence of the distinct advantages of additive techniques, which include the possibility of improving the mechanical strength of products and shortening lead times. Offshore industry is one of these promising areas for the application of additive manufacturing. This paper presents a decision support method for the manufacturing of offshore equipment components, and compares a standard subtractive method with an additive manufacturing approach. An analytic hierarchy process was applied to select the most effective and efficient production method, considering CNC milling and direct metal laser sintering. A final set of decision criteria that take into account the specifics of the offshore industry sector are provided.

12

Project prioritizing in a manufacturing – service enterprise with application of the fuzzy logic

Marek-Kolodziej Katarzyna, Lapunka Iwona

Management and Production Engineering Review

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2020

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Vol. 11, No. 4

81--91

EN

The article includes presentation of fuzzy numbers application in projects prioritizing at manufacturing and service providing enterprises. The following criteria have been applied as a basis for projects prioritizing analysis in enterprise: NPV index, linked with the enterprise strategic aims, project execution cost, project time, project scope and risk. As the criteria selected were of measurable and non-measurable character in projects prioritizing evaluation, the fuzzy decision making system has been developed, in which a linguistic value has been defined for each criterion of projects prioritizing. Knowledge base has been developed afterwards, presenting cause-effect dependencies in projects prioritizing. Knowledge base consisted of conditional rules. Fuzzy system of decision making in project prioritizing has been developed in MATLAB application. The decision making fuzzy system established, constitutes an efficient tool for projects prioritizing, on the basis of criteria given and concluding system developed. The obtained analysis results provide basis for the decision making parties to set the projects execution sequences.

13

Digital assets for project-based studies and data-driven project management

Miller Gloria J.

Annals of Computer Science and Information Systems

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2020

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Vol. 21

591--594

EN

Projects offer learning opportunities and digital data that can be analyzed through a multitude of theoretical lenses. They are key vehicles for economic and social action, and they are also a primary source of innovation, research, and organizational change. This research involves a survey of digital assets available through a project; specifically, it identifies sources of data that can be used for practicing data-driven, context-specific project management, or for project-based academic research. It identified four categories of data sources - communications, reports/records, model representations, and computer systems - and 48 digital assets. The list of digital assets can be inputs in the creation of project artifacts and sources for monitoring and controlling project activities and for sense-making in retrospectives or lessons learned. Moreover, this categorization is useful for decision support and artificial intelligence systems model development that requires real-world data.

14

An extensive analysis of online restaurant reviews: a case study of the Amazonian Culinary Tourism

Fernandes Junior Luiz Carlos Silva, Silva Junior Jorge, Jacob Junior Antônio, Lobato Fábio

Annals of Computer Science and Information Systems

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2020

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Vol. 21

81--84

EN

Analyzing User-Generated Content present in social media has become mandatory for companies looking for maintaining competitiveness. These data contain information such as consumer opinions, and recommendations that are seen as rich sources of information for the development of decision support systems. When observing the state of the art, it was found that there is a lack of antecedents that address the analysis of online reviews of Brazilian restaurants. In this sense, the focus of this work is to fill this gap through a case study of Santar\'em city. The results show that professionals in this segment can use these analyzes in order to improve the user's experiences and increase their profits.

15

Maintenance as a combination of intelligent IT systems and strategies: a literature review

Metso L., Baglee D., Marttonen-Arola S.

Management and Production Engineering Review

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2018

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Vol. 9, No. 1

51--64

EN

This study provides a systematic review of the existing academic literature describing the key components of eMaintenance. The current literature is reviewed by utilizing a number of academic databases including Scopus, SpringerLink and ScienceDirect, and Google Search is used to find relevant academic and peer-reviewed journal articles concerning eMaintenance. The literature describes eMaintenance as an advanced maintenance strategy that takes advantage of the Internet, information and communication technologies, wireless technologies and cloud computing. eMaintenance systems are used to provide real time analyses based on real time data to offer a number of solutions and to define maintenance tasks. The collection and analysis of appropriate maintenance and process data are critical to create robust ‘maintenance intelligence’ and finally improvements in manufacturing costs, safety, environmental impact, and equipment reliability. This paper describes how the scientific discussion on eMaintenance has expanded significantly during the last decade, creating a need for an up-to-date review. As a conclusion, three research gaps in the area of eMaintenance are identified, including evaluating the benefits of eMaintenance, agreeing on a comprehensive definition, and developing tools and structures for cooperative eMaintenance.

16

Validity and timing in decision support systems

Petrov O., Horoshko V., Aleksander M., Basiura B., Hokhlacheva Y.

Autobusy : technika, eksploatacja, systemy transportowe

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2018

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R. 19, nr 12

1116--1122

EN

Based on the principle of synthesizing the matrix of transitional probabilities, processes of decision-making support by means of the truncated procedures of type (k/n)n (k≤n) are considered. Obtained expressions for calculating the time-efficiency of the processes of decision support using procedures type (k/4)4 are shown. There are given calculated by the expressions obtained data time efficiency, which will enable a quantitative comparison between different procedures and select the best of them on the basis of specific practical tasks.

17

Decision support system in freight transport based on vehicle routing problem with quality criterion

Szczepański E., Jachimowski R., Żak J.

Archives of Transport System Telematics

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2018

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Vol. 11, iss. 3

49--56

EN

Deliveries planning in transport systems is a complicated task and require taking into account a wide range of factors. Enterprises wanting to propose solutions that meet the clients’ needs and be competitive on the market must prepare their offer based on decision support systems including factors characteristic for the real process. The aim of the article is to present a concept of a decision support system based on a multi-criteria vehicle routing problem in real conditions (Real-World VRP). Taking into account the latest trends in the optimization of the delivery plan, the model includes three criteria - the cost, time and success rate of the delivery plan as a criterion relating to the quality of the delivery plan. Among other assumptions, it should be pointed out that the heterogeneous structure of the rolling stock has been taken into account, the number of which is not limited, the vehicles return to the place of origin. The travel time of the connection and the time of loading operations are random variables. The limited driver’s work time and driving time were also applied. The effect of the work presented in the article is the concept of the decision support system in the freight transport, taking into account the quality criterion of the delivery plan.

18

The assessment of supply chain effectiveness

Jacyna-Gołda I., Izdebski M., Szczepański E., Gołda P.

Archives of Transport

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2018

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Vol. 45, iss. 1

43--52

EN

This paper presents the problem of the assessment of the supply chains in the context of their effectiveness. In this paper the concepts of a supply chain and effectiveness were characterized. The supply chain is a structure of entities which are connected with each other by the use of material and financial flows and functional, structural, technological, economic and information dependencies. Entities such as: suppliers, final recipients, entrepreneurs, warehouse facilities, supply centers, logistics operators, carriers, etc. perform material flows from suppliers to recipients. The concept of efficiency, in general terms, refers to economic rationality and means the relationship between the achieved or expected effects and the expenditures incurred. Additionally, indicators of measuring the effectiveness of the supply chain were described. In order to assess the effectiveness of the supply chain the decision model was developed. Optimization is crucial in decision support systems. The development of an appropriate model for mapping the behavior of a real object or system and formulating an optimization task is a necessary activity in effective management. This is even more important if we want to be competitive. Along with the development of decision support systems, as well as the development of systems for data acquisition on the system functioning, which feed optimization models in ever more detailed form, complex decision models are created that take into account many optimization criteria and require a large amount of data. It allows, however, to ensure the sustainable development of the system and simultaneous implementation of its basic tasks. The main aim of this paper is to present the stages and assumptions of the model for assessing the effectiveness of the supply chain. The main data input, constraints of the model, the criteria functions were determined.

19

The use of Petri nets in decision support systems based on intelligent multiply source data analysis

Rymarczyk T., Kłosowski G., Cieplak T.

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

|

2017

|

T. 7, nr 4

24--27

EN

The paper deals with the design of data analysis systems for business process automation. A general scheme of decision support system was developed in which one of the modules is based on Petri Nets. The way of implementation of Petri Net model in optimization problem regarding serviceoriented decision support system was shown. The Petri Net model of distribution workflow was presented and simulation experiments was completed. As a result the optimal solution as a set of parameters was emerged.

PL

Artykuł dotyczy problematyki projektowania zautomatyzowanych systemów analizy danych biznesowych. Opracowano ogólny model systemu wspomagania decyzji, w którym jeden z modułów funkcjonuje w oparciu o sieci Petriego. Zaprezentowano sposób implementacji sieci Petriego do realizacji zadań optymalizacyjnych dotyczących zorientowanego na usługi systemu wspomagania decyzji. Przeprowadzono szereg eksperymentów symulacyjnych wykorzystując model przepływu pracy utworzony na bazie sieci Petriego. Rezultatem badań było wyłonienie optymalnego zbioru parametrów procesu biznesowego.

20

Supply chain risk management by Monte Carlo method

Rymarczyk T., Kłosowski G.

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

|

2017

|

T. 7, nr 4

20--23

EN

In this paper, the conceptual model of risk-based cost estimation for completing tasks within supply chain is presented. This model is a hybrid. Its main unit is based on Monte Carlo Simulation (MCS). Due to the fact that the important and difficult to evaluate input information is vector of risk-occur probabilities the use of artificial intelligence method was proposed. The model assumes the use of fuzzy logic or artificial neural networks – depending on the availability of historical data. The presented model could provide support to managers in making valuation decisions regarding various tasks in supply chain management.

PL

W artykule zaprezentowano przykład zastosowania hybrydowego systemu wspomagania decyzji w kontekście zarządzania ryzykiem w łańcuchu dostaw. Główny moduł sterownika bazuje na koncepcji symulacji Monte Carlo. Wektor danych wejściowych zawiera istotne informacje, których wyrażenie w postaci zmiennych ilościowych stanowi wyzwanie, w związku z czym zaproponowano użycie sztucznej inteligencji. W zależności od dostępności do danych historycznych, sterownik decyzyjny zastosuje sieci neuronowe lub logikę rozmytą. Zaprezentowane rozwiązanie może stanowić wsparcie dla menedżerów podczas podejmowania decyzji będących odpowiedzią na różnorodne ryzyka w obszarze zarządzania łańcuchem dostaw.