Wyniki wyszukiwania - BazTech

1

Managing human factor risk: an interpretable decision support system for preselecting PTSD symptoms in occupational groups

Dardzińska-Głębocka Agnieszka, Kasperczuk Anna, Gardocki Grzegorz

Production Engineering Archives

|

2025

|

Vol. 31, Iss. 3

419--425

EN

Occupational stress is a critical human factor that affects efficiency, safety, and the continuity of operational processes, particularly in high-risk professions such as uniformed services. The aim of this study was to develop and validate an interpretable decision support system (DSS) for the early prescreening of employees exhibiting symptoms of post-traumatic stress disorder (PTSD). To this end, the J48 decision tree algorithm was applied to extract classification rules based on psychological symptoms defined in the DSM-5. The performance of the J48 model was compared with Support Vector Machine and Random Forest algorithms. Among the evaluated models, J48 demonstrated the highest overall effectiveness, achieving top results across all key metrics, including an F1-score of 0.976 and a ROC Area of 0.987. The generated classification rules ensure model transparency and interpretability - features essential for practical implementation in organizational occupational health procedures. The proposed tool contributes to the field of human factors engineering by offering a practical solution for managing mental health risks, ultimately supporting improved safety and operational performance in organizational settings.

2

Implementacja metod uczenia maszynowego do zarządzania ruchem lotniczym

Kaczorowski Piotr

Journal of KONBiN

|

2025

|

Vol. 55, iss.1

137--153

EN

Despite significant technological advancements, various factors continue to affect the safety and efficiency of multiple industries, including air transportation. One of the critical challenges in this field remains flight delays, which not only generate substantial economic costs but also pose potential risks to operational safety. This paper explores the application of machine learning methods for delay prediction and airport capacity modeling. Regression algorithms, decision trees, and reinforcement learning techniques were employed to analyze operational data. The study findings indicate that implementing machine learning models enables more precise delay forecasting, supporting decision-making processes and optimizing air traffic management.

PL

Współczesny rozwój technologii, mimo swego zaawansowania, nie eliminuje problemów wpływających na bezpieczeństwo i efektywność różnych dziedzin życia, w tym transportu lotniczego. Jednym z kluczowych wyzwań w tej branży pozostają opóźnienia, które mogą generować nie tylko znaczące koszty, lecz także negatywnie wpływać na bezpieczeństwo operacji lotniczych. W artykule przedstawiono zastosowanie metod uczenia maszynowego do predykcji opóźnień oraz modelowania przepustowości lotnisk. Wykorzystano algorytmy regresji, drzewa decyzyjne oraz uczenie ze wzmocnieniem do analizy danych operacyjnych. Wyniki badań wskazują, że implementacja modeli uczenia maszynowego umożliwia bardziej precyzyjne prognozowanie opóźnień, wspierając procesy decyzyjne oraz optymalizację zarządzania ruchem lotniczym.

3

Applying additive manufacturing technologies to a supply chain: A Petri net-based decision model

Patalas-Maliszewska Justyna, Wiśniewski Remigiusz, Zhou MengChu, Topczak Marcin, Wojnakowski Marcin

International Journal of Applied Mathematics and Computer Science

|

2024

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Vol. 34, no. 3

513--525

EN

Nowadays, applying additive manufacturing (AM) technologies into a supply chain (SC) permits realization of the so-called “demand chains” and transformation of conventional production to mass customization. However, integration of AM technologies within an SC indicates the need to support managers’ decision about such an investment. Therefore, this work develops a Petri net-based decision support model that determines the changes in an SC by adopting AM and improving customer-perceived value (CPV), based on a case study regarding a real-life metal production process. The basis for building such a model is the supply chain operation reference model (SCOR), focusing on CPV, due to the need for redesigning the SC starting from the customer instead of the company. To achieve the research objective, this work introduces a novel verification methodology for a Petri net-based decision model. The research results show that applying the developed model, which is based on the selected characteristics of the production process and parameters describing the potential integration of AM within the SC, allows managers to perceive a scenario in the form of graphical models about positive or negative impacts of introducing AM into the SC. The managers find the Petri net-based decision support model presented in this paper a beneficial tool to support the implementation of changes in an SC and show the potential increase in customer satisfaction thanks to the integration of AM within an SC.

4

Implementation of decision support system for ecological environment planning of urban green space

Feng Sijing

Ecological Chemistry and Engineering. S

|

2024

|

Vol. 31, nr 2

177--192

EN

As a highly concentrated residential area, urban development and population concentration have caused serious environmental pollution problems that threaten the safety of the water and atmospheric resources that humans rely on for survival. To address this issue, the importance of urban green space (UGS) has become increasingly prominent. This paper collected data related to UGS (green space coverage, vegetation type, environmental quality, population distribution, etc.) for processing, used the entropy algorithm to build an ecological environment assessment model, and then used the particle swarm optimisation algorithm to optimise the model accordingly. Finally, a decision support system was proposed for UGS ecological environment planning, which comprehensively considered future environmental changes. Through comparison before and after the application of decision support system, this paper tested and verified several indicators such as green space coverage, biological diversity index, and climate adaptability. Among them, after the application of the decision support system, the green space coverage rate has increased year by year, and many indicators in the biological diversity index have improved significantly. The average climate adaptability of traditional UGS planning was 70%, while the average climate adaptability of decision support system green space planning was 90%, which has been significantly improved. The outcome shows that the system has a notable effect in improving the climate adaptation and ecological quality of the city.

5

System wspomagający wykrywanie treści wizualnych i tekstowych zagrażających bezpieczeństwu dzieci w cyberprzestrzeni

Niewiadomska-Szynkiewicz Ewa, Różycka Martyna, Staciwa Katarzyna, Nyczka Katarzyna

Cybersecurity and Law

|

2023

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Vol. 10 (2)

202--220

PL

W ostatnich latach obserwuje się istotny wzrost zagrożeń bezpieczeństwa dzieci w cyberprzestrzeni. Do tych o największym ciężarze gatunkowym należą angażowanie dzieci w nielegalne zachowania online (np. uwodzenie, nagabywanie czy szantaż na tle seksualnym), a także wytwarzanie nacechowanych seksualnie treści z ich udziałem. W tej sytuacji podstawowego znaczenia nabiera budowanie wśród najmłodszych członków naszego społeczeństwa świadomości cyberzagrożeń oraz nabywanie przez nich umiejętności bezpiecznego korzystania z przypisanych cyberprzestrzeni produktów i usług. Podstawowym działaniem na rzecz skutecznej ochrony dzieci w tym środowisku jest także wczesne wykrywanie i zgłaszanie odpowiednim organom występujących w nim przypadków nielegalnych zachowań i treści. Ważną rolę odgrywają zespoły takie jak Dyżurnet. pl2, do którego zadań należy obecnie reagowanie na zgłoszone przez użytkowników cyberprzestrzeni potencjalnie nielegalne treści, a w najbliższej przyszłości być może także prowadzenie proaktywnych działań w tym obszarze. Doświadczenia Dyżurnet.pl jednoznacznie pokazują, że skuteczne wykrywanie takich treści wymaga automatyzacji działań i odpowiednich narzędzi informatycznych. W artykule został prezentowany nowatorski system monitorowania sieci i wspomagania decyzji wykorzystujący metody sztucznej inteligencji, w tym uczenia głębokiego do automatycznego wykrywania potencjalnie szkodliwych materiałów takich, jak: treści przedstawiające wykorzystywanie seksualne dzieci (Child Sexual Abuse Material – CSAM), treści erotyczne z udziałem dzieci, treści pornograficzne z wytworzonym lub przetworzonym obrazem dziecka oraz stanowiące pornografię z udziałem dorosłych.

EN

In recent years, there has been a significant increase in threats to children’s safety in cyberspace. The most serious of these include children’s participation in illegal online activities and the production of sexually explicit content involving them. Therefore, it is of fundamental importance to build awareness of cyber threats among our society’s youngest members and teach them skills for the safe use of products and services assigned to cyberspace. A key action for effectively protecting children in this environment is the early detection and reporting to the relevant authorities of illegal behavior and child abuse content. Teams such as Dyżurnet.pl, whose tasks currently include responding to potentially illegal content reported by cyberspace users, and in the near future, possibly also conducting proactive activities in this area, play an important role here. The experience of Dyżurnet.pl clearly shows that effective detection of such content requires automation of activities and appropriate IT tools. This paper presents a novel network monitoring and decision support system using artificial intelligence methods, including deep learning, to automatically detect potentially harmful material, such as Child Sexual Abuse Material (CSAM), erotic content involving children, pornographic content with a created or processed image of a child and pornography involving adults.

6

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

7

Mathematical methods of signal analysis applied in medical diagnostic

Ciecierski Konrad A.

International Journal of Applied Mathematics and Computer Science

|

2020

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Vol. 30, no. 3

449--462

EN

Digital signal processing, such as filtering, information extraction, and fusion of various results, is currently an integral part of advanced medical therapies. It is especially important in neurosurgery during deep-brain stimulation procedures. In such procedures, the surgical target is accessed using special electrodes while not being directly visible. This requires very precise identification of brain structures in 3D space throughout the surgery. In the case of deep-brain stimulation surgery for Parkinson’s disease (PD), the target area—the subthalamic nucleus (STN)—is located deep within the brain. It is also very small (just a few millimetres across), which makes this procedure even more difficult. For this reason, various signals are acquired, filtered, and finally fused, to provide the neurosurgeon with the exact location of the target. These signals come from preoperative medical imaging (such as MRI and CT), and from recordings of brain activity carried out during surgery using special brain-implanted electrodes. Using the method described in this paper, it is possible to construct a decision-support system that, during surgery, analyses signals recorded within the patient’s brain and classifies them as recorded within the STN or not. The constructed classifier discriminates signals with a sensitivity of 0.97 and a specificity of 0.96. The described algorithm is currently used for deep-brain stimulation surgeries among PD patients.

8

Geodata influencing land market and sustainable development

Gaudesius Rimvydas

Geodesy and Cartography

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2020

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Vol. 69, no. 1

3--17

EN

The suitability of a land plot in a real estate market could be identified as a good investment because the land plot is deemed as popular. This activity is important for economic growth, who is one of the sustainable development goals. Mostly, all research in this field is focused on sustainability as well as the opinions of professionals. However, this field should be explored from another side which is based on real geodata. Criteria and its weight are very important in decision support systems. The correct criteria can help in selection of the best real estate object for an investment, but it is not only useful but also and a challenging task that has not yet been solved. The methods of research are data graphical analysis, correlation, decision supporting systems, etc. The research aims at determining the significance of the connections and using them as the criteria in the selected decision supporting method. In addition, it will be determined which decision supporting method defines the most suitable object for investment. These new criteria are proposed for operation in the land use models. Furthermore, it has been identified as one criterion, which is significant in the urban and agrarian territories. Also it turned out, that the land plot is the most active when it is as far from a densely built-up residential territory as possible and as close to a school, and when the land plot is as large as possible.

9

Agricultural management on the basis of information technologies

Sivakovska Olena, Rudinets Mykola, Poteichuk Mykhailo

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

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2019

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T. 9, nr 3

82--85

EN

The article presents conceptually scientific and methodological principles of agricultural management on the basis of Information Technologies. It has determined the main directions of using Information Technologies in Agricultural Manufacturing. It has systematically investigated the manufacturing by agricultural producers, and it has determined and stressed the main functions and relationships between the two systemic parts – technical and technological as well as organizational and technical. There have been determined the hierarchical structure of the configuration for the husbandry systems. It was explored that this configuration consists of nine main parts, and which of them have their own configuration. It was a conceptually determined processes of architecture management of agricultural programs (portfolios) and the configuration of agricultural products. The developed structural and project approach to configurations management of systemic parts for agricultural manufacturing is the part of scientific and methodological principles of this manufacturing management using Information Technologies.

PL

Artykuł przedstawia koncepcje naukowe i metodologiczne zasady zarządzania rolnictwem na podstawie technologii informacyjnych. Określono główne kierunki wykorzystania technologii informacyjnych w produkcji rolniczej. Systematycznie badano produkcję przez producentów rolnych. Ustalono i podkreślono główne funkcje i związki między dwiema częściami systemowymi – techniczną i technologiczną oraz organizacyjną i techniczną. Określono hierarchiczną strukturę konfiguracji systemu agrarnego. Zbadano, że ta konfiguracja składa się z dziewięciu głównych części, które mają własną konfigurację. Określono koncepcyjnie procesy zarządzania architekturą programów rolniczych (portfeli) i konfiguracji produktów rolnych. Opracowane podejście strukturalne i projektowe do zarządzania konfiguracjami części systemowych do produkcji rolniczej jest częścią naukowych i metodologicznych zasad zarządzania produkcją z wykorzystaniem technologii informatycznych.

10

Scheduling trucks in a multi-door cross-docking system with time windows

Ozden G., Saricicek I.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2019

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Vol. 67, nr 2

344--362

EN

Cross-docking is a strategy that distributes products directly from a supplier or manufacturing plant to a customer or retail chain, reducing handling or storage time. This study focuses on the truck scheduling problem, which consists of assigning each truck to a door at the dock and determining the sequences for the trucks at each door considering the time-window aspect. The study presents a mathematical model for door assignment and truck scheduling with time windows at multi-door cross-docking centers. The objective of the model is to minimize the overall earliness and tardiness for outbound trucks. Simulated annealing (SA) and tabu search (TS) algorithms are proposed to solve largesized problems. The results of the mathematical model and of meta-heuristic algorithms are compared by generating test problems for different sizes. A decision support system (DSS) is also designed for the truck scheduling problem for multi-door cross-docking centers. Computational results show that TS and SA algorithms are efficient in solving large-sized problems in a reasonable time.

11

Zastosowanie rozmytej metody delfickiej do wyboru optymalnej pozycji zawodnika

Lawnik M., Banasik A.

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

|

2018

|

z. 127

117--123

PL

W artykule przedstawiono system ekspercki pomagający szkoleniowcom drużyny sportowej na optymalne obsadzenie danej pozycji w drużynie spośród dostępnych zawodników. System ten oparty jest o rozmytą metodę delficką, która na podstawie ocen sztabowców ocenia każdego z zawodników. Zawodnik z najwyższą notą jest rekomendowany na daną pozycję w drużynie. Działanie systemu przedstawiono na przykładzie obsadzenia pozycji napastnika w drużynie piłkarskiej w oparciu o oficjalne wytyczne Polskiego Związku Piłki Nożnej. Uzyskane wyniki sugerują, że proponowane rozwiązanie może być zastosowane do dowolnej zespołowej dyscypliny sportowej.

EN

The article presents expert system which helps coaches to optimal position setting in a team among all available players’. The system is based on fuzzy Delphi method which contains coaches raitings on each player. The highest note player is recommended on the specific position. The use of the system was presented on an example of striker position in football teat based on Polish Football Association model. Presented results shows that the solution can be implemented in any team sport discipline.

12

Rozmyty system wspomagania decyzji na przykładzie próby obrony rzutów karnych

Banasik A., Krakowczyk J., Lawnik M.

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2018

|

z. 127

9--16

PL

W artykule przedstawiono system wspomagania decyzji pomagający bramkarzowi w obronie rzutu karnego. Wykorzystuje on zbiory rozmyte i podejście Bellmana-Zadeha do podejmowania decyzji. Zaproponowane rozwiązanie zostało zaimplementowane w postaci aplikacji webowej, która może zostać wykorzystana również w pokrewnych zagadnieniach dotyczących innych sportów zespołowych. Działanie aplikacji jak i realizacja algorytmu zostały przedstawione na przykładzie numerycznym.

EN

This article presents decision support system helping the goalkeeper in defending the penalty kicks. It is based on fuzzy sets and Bellman-Zadeh’s approach in decision making. The proposed solution was implemented in web application, which can be used in similar approaches in team sports. The application and realization of the algorithm was shown on numerical example.

13

Analiza gotowości małych i średnich przedsiębiorstw do implementacji strategicznej karty wyników

Grochowski K.

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

|

2018

|

z. 127

73--82

PL

Współcześni przedsiębiorcy powinni tworzyć własne, a zarazem niepowtarzalne koncepcje działań, biorąc pod uwagę teraźniejsze i przyszłe zmiany otoczenia. Polskie małe i średnie przedsiębiorstwa w swojej codziennej działalności nadal uczą się zachowań rynkowych i strategicznych. Celem artykułu była ocena gotowości małych i średnich przedsiębiorstw usług transportowych do wdrożenia rozwiązań Strategicznej Karty Wyników. Dobra diagnoza może dostarczyć wskazówek do prawidłowego zastosowania narzędzia analizy strategicznej, co ułatwi proces monitorowania poziomu realizacji założonych celów.

EN

Polish small and medium-sized enterprises continue to learn market and strategic behavior in their day-to-day operations. The aim of the study has been to assess the willingness of small and medium-sized transport service companies to implement Balanced Scorecard. A good diagnosis can provide guidance for the correct application of the strategic analysis tool, which will facilitate the process of monitoring the level of achievement of goals.

14

Adaptive Decision Support System in Network Centric Warfare Process

Dudczyk J., Rybak Ł.

Elektronika : konstrukcje, technologie, zastosowania

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2018

|

Vol. 59, nr 7

39--42

EN

The article presents a concept of Adaptive Decision Support System (ADSS) which makes it possible to realize a network centric warfare strategy. The introduction of this article presents the significance of data processing by information and communication systems on the computerized battlefield. Also, it consists of a description of the process which aims at gaining knowledge from relational databases in terms of building situational awareness and organizing informational advantage. The strategic thought cycle in terms of building an adaptive information and communication system is presented in this work as well. A further part of the article describes the general architecture of decision support system applications, points out and defines their key elements. Finally, an original concept of decision-making model in adaptive DSS is suggested as an idea in which k-Nearest Neighbours classificator and the method of machine learning are used to realize the assumption concerning the adaptation of the system to dynamic conditions on the battlefield. The direction of research as well as possibilities of potential solution optimization are also indicated in this article.

PL

W artykule zaproponowano koncepcję adaptacyjnego systemu wspomagania decyzji ADSS (ang. Adaptive Decision Support System) pozwalającego na realizację strategii walki sieciocentrycznej. Na wstępie przedstawiono istotę przetwarzania danych przez systemy teleinformatyczne na zinformatyzowanym polu walki. Scharakteryzowano proces wydobywania wiedzy z relacyjnych baz danych w kontekście budowania świadomości sytuacyjnej oraz organizowania przewagi informacyjnej. Przedstawiono cykl myślenia strategicznego w kontekście budowania adaptacyjnego systemu teleinformatycznego. Następnie opisano ogólną architekturę aplikacji wspomagających decyzję, wskazano oraz scharakteryzowano kluczowe ich elementy. Ostatecznie zaproponowano autorską koncepcję modelu decyzyjnego w adaptacyjnym DSS wykorzystującą klasyfikator k-najbliższych sąsiadów oraz metodę uczenia maszynowego, co pozwoliło na realizację założenia dotyczącego przystosowywania się systemu do dynamicznych warunków pola walki. Ponadto wskazano kierunek badań oraz możliwości ewentualnej optymalizacji rozwiązania.

15

Niepewność w modelowaniu rozwoju sytuacji radiacyjnej za pomocą Systemów Wspomagania Decyzji

Jaroszek A.

Bezpieczeństwo Jądrowe i Ochrona Radiologiczna

|

2018

|

nr 2 (112)

34--40

16

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

|

2018

|

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.

17

Durability analysis of forging tools after different variants of surface treatment using a decision-support system based on artificial neural networks

Mrzygłód B., Hawryluk M., Gronostajski Z., Opaliński A., Kaszuba M., Polak S., Widomski P., Ziemba J., Zwierzchowski M.

Archives of Civil and Mechanical Engineering

|

2018

|

Vol. 18, no. 4

1079--1091

EN

This article concerns a decision-support system based on artificial neural networks (ANN) enabling analysis and forecasting of the durability of forging tools used in the hot forging process of a cover forging – a sealing element of the driveshaft in road freight vehicles. The process of knowledge acquisition, adopted neural network architecture and parameters of the developed network are presented. In addition, 3 variants of a hybrid layer (gas nitrided layer GN + PVD coating) were applied to the selected tools (punches applied in the 2nd top forging operation): GN/AlCrTiN, GN/AlCrTiSiN, and GN/CrN, in order to improve durability, and the resultant tools were also compared to standard tools (with only gas nitriding) and regenerated tools (after repair welding regeneration). The indispensable knowledge about the durability of selected forging tools (after various surface engineering variants), required for the process of learning, testing and validation for various neural network architectures was obtained from comprehensive, multi-year studies. These studies covered, among other things: operational observation of the forging process, macroscopic analysis combined with scanning of tools’ working surfaces, microhardness measurements, microstructural analysis and numerical modeling of the forging process. The developed machine-learning dataset was a collection of approx. 900 knowledge records. The input (independent) variables were: number of forgings manufactures, pressing forces, temperature on selected tool surfaces, friction path and type of protective layer applied to tool. Meanwhile, output (dependent) variables were: geometrical loss of tool material and percentage share of the four main destructive mechanisms. Obtained results indicate the validity of employing ANN-based IT tools to build decision-support systems for the purpose of analyzing and forecasting the durability of forging tools.

18

The model of decision-making in selecting the optimal configuration of the hybrid renewable energy systems

Shulyma O., Shendryk V., Pakstas A.

Silesian Journal of Pure and Applied Mathematics

|

2017

|

Vol. 7, iss. 1

5--20

EN

The purpose of this study is twofold: first, it is aimed at determining the architecture, energy balance of the system and the operational logic of the requests for energy use. Second, a defining a methodology that can help energy planners in the choice of the more appropriate alternatives of hybrid renewable energy system. Based on energy balance and operational logic within HRESs is proposed to conduct optimization research within socio-economic and energy efficiency scenarios. This research is proposed to use within DSS that can support the decision makers in selecting criteria, alternatives and trade-offs, thus making the energy planning simple. The methodology is divided in 3 steps: The selection of system structure in general, the determination of parameters of the system elements in all possible variants, and finally the estimation of efficiency and choosing the optimal variant of the system. For each alternatives is calculated the utility function within scenarios.

19

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.

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Optymalizacja wielokryterialna w procesie produkcji mebli

Kłosowski G., Kozłowski E.

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

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2017

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T. 7, nr 4

101--106

PL

Opracowanie dotyczy zastosowania programowania liniowego całkowitoliczbowego w optymalizacji wielokryterialnej. Celem badań było opracowanie modelu sterownika decyzyjnego umożliwiającego jednoczesną minimalizację poziomu zapasów półfabrykatów wygenerowanych w procesie cięcia, jak i odpadów po rozkroju. Zadaniem sterownika było dobranie odpowiedniego programu rozkroju z uwzględnieniem zamówień produkcyjnych, bieżących zapasów półfabrykatów i ograniczeń odnośnie dopuszczalnych poziomów zapasów.

EN

This paper concerns the use of integer linear programming in a multi-criteria optimization. The aim of the research was to develop a model of the decision support system allowing simultaneous minimization of the intermediate products stocks level and waste generated in the process of cutting. The goal of controller was to select the appropriate cutting program, including production orders, the current inventory and limits on permissible stocks levels.