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Wyszukujesz frazę "decision-making algorithm" wg kryterium: Wszystkie pola


Wyświetlanie 1-19 z 19
Tytuł:
A generalization of the Zionts-Wallenius multiple criteria decision making algorithm
Autorzy:
Kaliszewski, I.
Zionts, S.
Powiązania:
https://bibliotekanauki.pl/articles/970490.pdf
Data publikacji:
2004
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
wielokryterialne podejmowanie decyzji
zagadnienie wypukłe
zamiana
selekcja portfela
multiple criteria decision making
convex problems
trade-off
portfolio selection
Opis:
In multicriteria problem solving, much can be learned by observing the decision-making process. Some, if not many, of the theoretical constructs used in some academically-generated models are simply not necessary. Taking this into account, we generalize the Zionts-Wallenius Multiple Criteria Decision Making Algorithm. We generalize the approach so that it can solve general convex problems. We do this by drawing from other methods, and by incorporating what we have learned in our work. To deal with the class of convex problems we face, we broaden the concept of tradeoff, and use global tradeoffs. Theory is developed, and then a method incorporating the theory is presented. A small example is included. We discuss how our development enriches decision-making tools currently available. We discuss applications in finance and technology.
Źródło:
Control and Cybernetics; 2004, 33, 3; 477-500
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Management decision-making algorithm development for planning activities that reduce the production risk level
Autorzy:
Kruzhilko, O.
Maystrenko, V.
Powiązania:
https://bibliotekanauki.pl/articles/368696.pdf
Data publikacji:
2019
Wydawca:
Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
Tematy:
safety and health management
risk assessment
algorithmization
zarządzanie bezpieczeństwem i higieną pracy
ocena ryzyka
algorytmizacja
Opis:
Purpose: Algorithm development for a measures phased expert assessment to reduce production risk at an industrial enterprise to adapt the expert method to the conditions for specific problem solving. Design/methodology/approach: To develop an algorithm for making management decisions, a step-by-step solution process was used. If the problem is solved under conditions of complete or partial uncertainty, an expert method of estimation was applied. In the mathematical model of management decision-making used criterion approach. At the same time, the methods of Sevij, Wald, and Hurwitz are considered to determine the criterion for choosing management decisions. Findings: A phased expert assessment of measures that reduce production risk at an industrial enterprise with the introduction of weighting factors in specified criteria is proposed. The expediency of applying the method of expert assessments and the Hurwitz criterion when planning measures to reduce industrial injuries is justified, since this approach links the preventive measures in the field of labour protection with the results of risk assessment and reduces subjectivity in making management decisions. Research limitations/implications: The proposed algorithm for expert assessment of measures to reduce production risk is universal for industrial enterprises. Practical implications: An algorithm has been developed to substantiate managerial decisions to reduce the production risks of the occurrence of traumatic events when planning preventive measures, which involves applying criteria for selecting measures based on the method of expert assessments and applying the Gurwitz criterion. Originality/value: Developed a consistent model of industrial risk management, which is based on a component method of assessing the risk of traumatic events and a mathematical model of management decisions. This model differs from the existing ones, taking into account all available risk-relevant information of the enterprise, stimulates preventive activity, and allows establishing the dependence of the level of industrial risk on the validity of measures on occupational safety and reducing the influence of the subjective component of expert judgments.
Źródło:
Journal of Achievements in Materials and Manufacturing Engineering; 2019, 93, 1-2; 41-49
1734-8412
Pojawia się w:
Journal of Achievements in Materials and Manufacturing Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Machine vision in autonomous vehicles: designing and testing the decision making algorithm based on entity attribute value model
Autorzy:
Shubenkova, Ksenia
Zabinski, Krzysztof
Powiązania:
https://bibliotekanauki.pl/articles/2056098.pdf
Data publikacji:
2021
Wydawca:
Sieć Badawcza Łukasiewicz. Przemysłowy Instytut Motoryzacji
Tematy:
autonomous driving
unmanned vehicle
machine vision
decision rules
Decision Table
Opis:
If we speak about the Smart City’s transport system, autonomous vehicles idea is the first thing that comes to mind. Today, it is strongly believed that the autonomous vehicles’ introduction into the traffic will increase the road safety. However, driverless cars are not the solution by itself. The road safety and, accordingly, sustainability will strongly depend on decision making algorithms inbuilt into the control module. Therefore, the goal of our research is to design and test the data mining algorithm based on Entity–Attribute–Value (EAV) model for decision making in the Intelligent System in the fully- or semi-autonomous vehicles. In this article, we describe the methodology to create 3 main modules of the designed Intelligent System: (1) an Object detection module; (2) a Data analysis module; (3) a Knowledge database built on decision rules generated with the help of our data mining algorithm. To build the Decision Table on the base of the real data, we have tested our algorithm on a simple collection of photos from a Polish two-lane road. Generated rules provide comparable classification results to the dynamic programming approach for optimization of decision rules relative to length or support. However, our decision making algorithm thanks to excluding the mistakes made on the object detection stage, works faster than existing ones with the same level of correctness.
Źródło:
Archiwum Motoryzacji; 2021, 94, 4; 27--37
1234-754X
2084-476X
Pojawia się w:
Archiwum Motoryzacji
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Conversion timing of seafarer’s decision-making for unmanned ship navigation
Autorzy:
Zhang, R. L.
Furusho, M.
Powiązania:
https://bibliotekanauki.pl/articles/116734.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
maritime safety
unmanned ship
unmanned ship navigation
on-board decision-making
decision-making algorithm
conversion timing
bayesian risk prediction
seafarers
Opis:
The aim of this study is to construct an unmanned ship swarms monitoring model to improve autonomous decision-making efficiency and safety performance of unmanned ship navigation. A framework is proposed to determine the relationship between on-board decision-making and shore side monitoring, the process of ship data detection, tracking, analysis and loss, and the application of decision-making algorithm, to discuss the different risk responses of specific unmanned ship types under various latent hazard environments, particularly in terms of precise conversion timing in switching over to remote control and full manual monitoring, to ensure safe navigation when the capability of automatic risk response inadequate. This frame-work makes it easier to train data and the adjustment for machine learning based on Bayesian risk prediction. It can be concluded that the automation level can be increased and the workload of shore-based seafarers can be reduced easily.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2017, 11, 3; 463-468
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Control of the workplace environment by physical factors and SMART monitoring
Autorzy:
Kruzhilko, O.
Polukarov, O.
Vambol, S.
Vambol, V.
Khan, N. A.
Maystrenko, V.
Kalinchyk, V. P.
Khan, A. H.
Powiązania:
https://bibliotekanauki.pl/articles/1818508.pdf
Data publikacji:
2020
Wydawca:
Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
Tematy:
environmental physical factors
occupational health
monitoring
occupational health and safety management system
decision-making algorithm
środowiskowe czynniki fizyczne
zdrowie zawodowe
monitorowanie
system zarządzania bezpieczeństwem i higieną pracy
algorytm decyzyjny
Opis:
Purpose: To develop and implementation in practice an algorithm for smart monitoring of workplace environmental physical factors for occupational health and safety (OSH) management. Design/methodology/approach: A brief conceptual analysis of existing approaches to workplace environmental physical factors monitoring was conducted and reasonably suggest a decision-making algorithm to reduce the negative impact of this factors as an element of the OSH management system. Findings: An algorithm has been developed that provides continual improvement of the OSH management system to improve overall labour productivity and which has 3 key positive features: (1) improved data collection, (2) improved data transfer and (3) operational determination of the working conditions class. Research limitations/implications: The implementation of the proposed algorithm for substantiating managerial decisions to reduce the negative impact of workplace physical factors is shown by the example of four workplace environmental physical factors in the products manufacture from glass. Practical implications: If management decisions on the implementation of protective measures are taken in accordance with the proposed monitoring algorithm, these decisions will be timely and justified. This makes it possible to reduce the time of the dangerous effects of physical factors on the health of workers and reduce the level of these factors to improve working conditions. That is, an algorithm is proposed that provides continuous improvement of the OSH management system to increase overall labour productivity. Originality/value: Current monitoring of workplace environmental physical factors values are carried out in accordance with the justified monitoring intervals for each factor that provides the necessary and sufficient amount of data and eliminates the transfer of useless data.
Źródło:
Archives of Materials Science and Engineering; 2020, 103, 1; 18--29
1897-2764
Pojawia się w:
Archives of Materials Science and Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Algorytm postępowania decyzyjnego w działalności innowacyjnej przedsiębiorstw
Algorithm of decision making procedure in enterprises innovative activity
Autorzy:
Sałek, R.
Powiązania:
https://bibliotekanauki.pl/articles/325436.pdf
Data publikacji:
2014
Wydawca:
Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:
algorytmy decyzyjne
modele decyzyjne
innowacyjność
zarządzanie przedsiębiorstwem
decision algorithms
decision-making models
innovativeness
enterprise management
Opis:
Innowacyjność współczesnych przedsiębiorstw w dużym stopniu odzwierciedla ich działalność rynkową, stanowi również wyznacznik ich możliwości rozwojowych. Procesy decyzyjne stanowią fundament dla prawidłowego funkcjonowania każdego przedsiębiorstwa. Ich ustalony i sprawny przebieg często decyduje o sukcesie lub porażce w rozwiązywaniu danego problemu. Zastosowanie odpowiednich narzędzi, które w sposób czytelny wspomagają podejmowanie decyzji, w znaczący sposób może się przyczyniać do tworzenia skutecznej strategii innowacyjności.
Innovativeness of modern enterprises a large extent reflects their market activities, and is also a determinant of their development opportunities. Decision-making processes are the foundation for the proper functioning of any enterprise. Their defined and efficient course often determines between success and failure in solving a given problem. Application of appropriate tools, which clearly support the decision-making in a meaningful way, could contribute for creating a successful innovation strategy.
Źródło:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska; 2014, 68; 243-253
1641-3466
Pojawia się w:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On an algorithm for decision-making for the optimization of disease prediction at the primary health care level using neural network clustering
Autorzy:
Selskyy, Petro
Vakulenko, Dmytro
Televiak, Anatolii
Veresiuk, Taras
Powiązania:
https://bibliotekanauki.pl/articles/551653.pdf
Data publikacji:
2018
Wydawca:
Stowarzyszenie Przyjaciół Medycyny Rodzinnej i Lekarzy Rodzinnych
Tematy:
primary health care
ypertension
algorithms
eural networks (computer) cluster analysis.
Źródło:
Family Medicine & Primary Care Review; 2018, 2; 171-175
1734-3402
Pojawia się w:
Family Medicine & Primary Care Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Decyzje w sytuacjach konfliktów moralnych
Decisions in Moral Conflict Situations
Autorzy:
Banajski, Ryszard
Powiązania:
https://bibliotekanauki.pl/articles/469142.pdf
Data publikacji:
2006
Wydawca:
Polska Akademia Nauk. Instytut Filozofii i Socjologii PAN
Tematy:
moral conflict
hypothesis on conflict background of morality
technology of ethics
algorithm of decision making in conflict situations
Opis:
Analyzing the character of moral conflict and a hypothesis on the conflict background of morality, the author refers to J. Pawlica’s ideas on the technology of ethics as a new branch of ethics, dealing with ethical decisions (apart from descriptive and normative ethics) as well as K. Szaniawski’s proposal to solve moral conflicts by means of appropriate tools of the decision theory. The article results in an attempt to formulate the algorithm of decision making in moral conflict situations.
Źródło:
Prakseologia; 2006, 146; 113-122
0079-4872
Pojawia się w:
Prakseologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Decision Accuracy for the Relevant-Irrelevant Screening Test: Influence of an Algorithm on Human Decision-Making
Autorzy:
Krapohl, Donald J.
Goodson, Walt
Powiązania:
https://bibliotekanauki.pl/articles/523329.pdf
Data publikacji:
2015-12-01
Wydawca:
Krakowska Akademia im. Andrzeja Frycza Modrzewskiego
Tematy:
Relevant-Irrelevant Screening Test
Relevant-Irrelevant Test
Accuracy of R-I list
Screening
decision-making
Źródło:
European Polygraph; 2015, 9, 4; 189-208
1898-5238
2380-0550
Pojawia się w:
European Polygraph
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A machine learning method for soil conditioning automated decision-making of EPBM : hybrid GBDT and Random Forest Algorithm
Autorzy:
Lin, Lin
Guo, Hao
Lv, Yancheng
Liu, Jie
Tong, Changsheng
Yang, Shuqin
Powiązania:
https://bibliotekanauki.pl/articles/2087007.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
soil conditioning
automated decision-making
hybrid algorithm
geological parameters
drive parameters
feature selection
Opis:
There lacks an automated decision-making method for soil conditioning of EPBM with high accuracy and efficiency that is applicable to changeable geological conditions and takes drive parameters into consideration. A hybrid method of Gradient Boosting Decision Tree (GBDT) and random forest algorithm to make decisions on soil conditioning using foam is proposed in this paper to realize automated decision-making. Relevant parameters include decision parameters (geological parameters and drive parameters) and target parameters (dosage of foam). GBDT, an efficient algorithm based on decision tree, is used to determine the weights of geological parameters, forming 3 parameters sets. Then 3 decision-making models are established using random forest, an algorithm with high accuracy based on decision tree. The optimal model is obtained by Bayesian optimization. It proves that the model has obvious advantages in accuracy compared with other methods. The model can realize real-time decision-making with high accuracy under changeable geological conditions and reduce the experiment cost.
Źródło:
Eksploatacja i Niezawodność; 2022, 24, 2; 237--247
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Decision-making enhancement in a big data environment : application of the K-means algorithm to mixed data
Autorzy:
Koren, Oded
Hallin, Carina Antonia
Perel, Nir
Bendet, Dror
Powiązania:
https://bibliotekanauki.pl/articles/91712.pdf
Data publikacji:
2019
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
big data
mixed data
hadoop
K-means
decision making
Opis:
Big data research has become an important discipline in information systems research. However, the flood of data being generated on the Internet is increasingly unstructured and non-numeric in the form of images and texts. Thus, research indicates that there is an increasing need to develop more efficient algorithms for treating mixed data in big data for effective decision making. In this paper, we apply the classical K-means algorithm to both numeric and categorical attributes in big data platforms. We first present an algorithm that handles the problem of mixed data. We then use big data platforms to implement the algorithm, demonstrating its functionalities by applying the algorithm in a detailed case study. This provides us with a solid basis for performing more targeted profiling for decision making and research using big data. Consequently, the decision makers will be able to treat mixed data, numerical and categorical data, to explain and predict phenomena in the big data ecosystem. Our research includes a detailed end-to-end case study that presents an implementation of the suggested procedure. This demonstrates its capabilities and the advantages that allow it to improve the decision-making process by targeting organizations’ business requirements to a specific cluster[s]/profiles[s] based on the enhancement outcomes.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2019, 9, 4; 293-302
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Stochastic programming model for production planning with stochastic aggregate demand and spreadsheet-based solution heuristics
Autorzy:
Saadouli, Nasreddine
Powiązania:
https://bibliotekanauki.pl/articles/2100358.pdf
Data publikacji:
2021
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
production planning
stochastic programming
efficient algorithm
decision-making
Opis:
By discretising the stochastic demand, a deterministic nonlinear programming formulation is developed. Then, a hybrid simulation-optimisation heuristic that capitalises on the nature of the problem is designed. The outcome is an evaluation problem that is efficiently solved using a spreadsheet model. The main contribution of the paper is providing production managers with a tractable formulation of the production planning problem in a stochastic environment and an efficient solution scheme. A key benefit of this approach is that it provides quick near-optimal solutions without requiring in-depth knowledge or significant investments in optimisation techniques and software.
Źródło:
Operations Research and Decisions; 2021, 31, 4; 117--127
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Management and decisions in the structures of human activities
Autorzy:
Galanc, T.
Kołwzan, W.
Pieronek, J.
Skowronek-Grądziel, A.
Powiązania:
https://bibliotekanauki.pl/articles/406575.pdf
Data publikacji:
2017
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
management
decision-making
structure
algorithm
scientific language
Opis:
This article has been devoted to the key dimensions of decision-making. The main goal of the authors was to point out the role and effect of invariants of nature, logic and conceptual systems of science and management, which are extremely important in decision-making processes. The research hypothesis has been tested that the complexity of decision-making and management are determined by the state of reality (Nature). This hypothesis is related to the fact that in science there is currently no uniform methodology associated with decision-making, just as science is not methodologically uniform. One can even doubt whether it is possible to describe the essential dimensions of decisions undertaken by Man, as discussed in this article. These problems are not a novelty to science, since they have been analysed by many scientists in the past. The authors of the article present the complexity and diversity of concepts defining systems of decision-making and management, based on selected fields of knowledge which are generally relevant to this issue, in particular fields associated with ontology and epistemology. Therefore, the text refers broadly to investigating the reality of basic areas of human knowledge and the overlapping relationships between them. This applies to the so-called circle of the sciences proposed and examined by the psychologist J. Piaget. An additional aim of the authors was to create a text presenting contemporary human knowledge about the reality which surrounds us. To understand reality means to be in relative equilibrium with it.
Źródło:
Operations Research and Decisions; 2017, 27, 4; 45-69
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Travel management optimization based on air pollution condition using Markov decision process and genetic algorithm (case study: Shiraz city)
Autorzy:
Bagheri, Mohammad
Ghafourian, Hossein
Kashefiolasl, Morteza
Pour, Mohammad Taghi Sadati
Rabbani, Mohammad
Powiązania:
https://bibliotekanauki.pl/articles/223520.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
air pollution
dynamic optimization
genetic algorithm
Markov decision-making process
zarządzanie transportem
optymalizacja
zanieczyszczenie powietrza
algorytm genetyczny
proces decyzyjny Markowa
Opis:
Currently, air pollution and energy consumption are the main issues in the transportation area in large urban cities. In these cities, most people choose their transportation mode according to corresponding utility including traveller's and trip’s characteristics. Also, there is no effective solution in terms of population growth, urban space, and transportation demands, so it is essential to optimize systematically travel demands in the real network of roads in urban areas, especially in congested areas. Travel Demand Management (TDM) is one of the well-known ways to solve these problems. TDM defined as a strategy that aims to maximize the efficiency of the urban transport system by granting certain privileges for public transportation modes, Enforcement on the private car traffic prohibition in specific places or times, increase in the cost of using certain facilities like parking in congested areas. Network pricing is one of the most effective methods of managing transportation demands for reducing traffic and controlling air pollution especially in the crowded parts of downtown. A little paper may exist that optimize urban transportations in busy parts of cities with combined Markov decision making processes with reward and evolutionary-based algorithms and simultaneously considering customers’ and trip’s characteristics. Therefore, we present a new network traffic management for urban cities that optimizes a multi-objective function that related to the expected value of the Markov decision system’s reward using the Genetic Algorithm. The planned Shiraz city is taken as a benchmark for evaluating the performance of the proposed approach. At first, an analysis is also performed on the impact of the toll levels on the variation of the user and operator cost components, respectively. After choosing suitable values for the network parameters, simulation of the Markov decision process and GA is dynamically performed, then the optimal decision for the Markov decision process in terms of total reward is obtained. The results illustrate that the proposed cordon pricing has significant improvement in performance for all seasons including spring, autumn, and winter.
Źródło:
Archives of Transport; 2020, 53, 1; 89-102
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimising rig design for sailing yachts with Evolutionary Multi-objective Algorithm
Autorzy:
Pawłusik, Mikołaj
Szłapczyński, Rafał
Karczewski, Artur
Powiązania:
https://bibliotekanauki.pl/articles/1573832.pdf
Data publikacji:
2020
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
sailing yacht rig optimization
Bermuda sloop
Multi-Objective Evolutionary Algorithms (MOEA)
Multi Criteria Decision Making (MCDM)
Opis:
The paper presents a framework for optimising a sailing yacht rig using Multi-objective Evolutionary Algorithms and for filtering obtained solutions by means of a Multi-criteria Decision Making method. A Bermuda sloop with discontinuous rig is taken under consideration as a model rig configuration. It has been decomposed into its elements and described by a set of control parameters to form a responsive model which can be used for optimisation purposes. Considering the contradictory nature of real optimisation objectives, a multi-objective approach has been chosen to address this issue. Once the optimisation process is over, a Multi-criteria Decision Making method based on a w-dominance relation is applied for filtering out the most interesting solutions from the obtained Pareto set. The proposed method has been implemented, and selected results are provided and discussed.
Źródło:
Polish Maritime Research; 2020, 4; 36-49
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The possibilities of utilising postoptimal analysis for the decision-making on the trends and concentration of coal sales
Możliwości wykorzystania analizy postoptymalnej do podejmowania decyzji o kierunkach i koncentracji zbytu węgla
Autorzy:
Fuksa, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/1841485.pdf
Data publikacji:
2020
Wydawca:
Polskie Towarzystwo Przeróbki Kopalin
Tematy:
optimization
post-optimal analysis
Simplex algorithm
optymalizacja
analiza postoptymalna
algorytm Simpleks
Opis:
When developing optimal coal production and sales plans for coal mines, one is often faced with the necessity to modify them, which implies the rationality of such plans. This is achieved through postoptimal analysis, which allows coal mines’ production plans, formal¬ly optimal, to be modified. The article presents the possibilities of utilising postoptimal analysis developed as part of a method for the rationalisation of production decisions with regard to the management of a coal company. The algorithms resulting from this analysis, accompanied by examples of their practical application, illustrate the possibility of presenting the economic effects of adjustments, if any, quantitatively, which also includes adapting the coal production and sales plans to actual demand, both in terms of quantity and quality. The provided examples of adjustments to the optimal plan concern the “producer-recipient” relationship and the concentration of coal sales.
Przy opracowywaniu optymalnych programów produkcji i sprzedaży węgla dla kopalń występuje niejednokrotnie konieczność ich mo¬dyfikacji, co implikuje racjonalność planów produkcji i sprzedaży węgla. Realizuje się to dzięki analizie postoptymalnej, pozwalającej na modyfikację formalnie optymalnych planów produkcyjnych kopalń. W artykule zaprezentowano możliwości analizy postopty¬malnej opracowanej w ramach metody racjonalizacji decyzji produkcyjnych dla potrzeb zarządzania spółką węglową. Opracowane w ramach tej analizy algorytmy poparte przykładami praktycznego ich wykorzystania ilustrują możliwości ilościowego ujmowania skutków ekonomicznych ewentualnych korekt, w tym dostosowania planów produkcji i sprzedaży węgla do realnych zmian zapo¬trzebowania, zarówno w sensie ilościowym jak i jakościowym. Podane przykłady korekt planu optymalnego dotyczą powiązania producent-odbiorca oraz koncentracji zbytu węgla.
Źródło:
Inżynieria Mineralna; 2020, 2, 2; 21-26
1640-4920
Pojawia się w:
Inżynieria Mineralna
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Strategia marketingowa – idea, algorytm i znaczenie w procesie decyzyjnym zakładu ubezpieczeń
Marketing Strategy – an Idea, Algorithm and Importance in the Insurance Company’s Decision-Making Process
Autorzy:
Fulneczek, Roman
Powiązania:
https://bibliotekanauki.pl/articles/440047.pdf
Data publikacji:
2014
Wydawca:
Akademia Finansów i Biznesu Vistula
Tematy:
marketing
strategia marketingowa
marketing innowacyjny
rynek ubezpieczeń
usługi ubezpieczeniowe
produkt ubezpieczeniowy
marketing strategy
innovative marketing
insurance market
insurance services
insurance product
Opis:
Strategia marketingowa przesądza o powodzeniu lub jego braku w firmie ubezpieczeniowej. Celem rozważań jest próba określenia, jak ważną rolę w działalności ubezpieczeniowej odgrywa strategia marketingowa. Artykuł poświęcony są zagadnieniom teoretycznym, metodologicznym oraz analizie uwarunkowań prowadzenia działalności ubezpieczeniowej. Omówione zostały podstawowe zagadnienia strategii marketingowej, a więc idea, algorytm i znaczenie w procesie decyzyjnym firm ubezpieczeniowych. Przedstawiono podstawowe zagadnienia pojęciowe i definicje marketingu i marketingu usług. Przyjęto algorytm oparty na czterech polach konstrukcji strategii marketingowej, do których zaliczono: – określenie, gdzie jesteśmy jako firma ubezpieczeniowa, – określenie, dokąd zmierzamy, – zdefiniowanie posiadanych zasobów, – dokonanie wyboru i podjęcie decyzji. Opracowanie oparte jest na studium literatury z zakresu marketingu i zarządzania, jak również na własnych doświadczeniach zawodowych zarządczych autora w firmach ubezpieczeniowych.
The marketing strategy decides a success or a failure in the insurance company. An aim of considerations is an attempt to determine how important role in insurance activities is played by the marketing strategy. The article is devoted to theoretical, methodological issues and to an analysis of determinants of carrying out insurance activities. There were discussed the basic issues of the marketing strategy, i.e. the idea, algorithm and importance in the insurance companies’ decision-making process. The author presented the basic notions and definitions of marketing and service marketing. He adopted the algorithm based on the four fields of marketing strategy construction, which include: – determining where we are as an insurance company, – determining where we go, – defining the assets held, – making a choice and decision. The elaboration is based on the study of literature in the field of marketing and management, as well as on the author’s own professional managerial experience in insurance companies.
Źródło:
Kwartalnik Naukowy Uczelni Vistula; 2014, 1(39); 93-106
2084-4689
Pojawia się w:
Kwartalnik Naukowy Uczelni Vistula
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method of decision making in multi-objective optimal placement and sizing of distributed generators in the smart grid
Autorzy:
Khoshayand, Hossein Ali
Wattanapongsakorn, Naruemon
Mahdavian, Mehdi
Ganji, Ehsan
Powiązania:
https://bibliotekanauki.pl/articles/2202555.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
backward-forward load distribution
fuzzy logic
iterative search algorithm
multi-objective optimization
shortest distance from the origin
weighted sum
Opis:
One of the most important aims of the sizing and allocation of distributed generators (DGs) in power systems is to achieve the highest feasible efficiency and performance by using the least number of DGs. Considering the use of two DGs in comparison to a single DG significantly increases the degree of freedom in designing the power system. In this paper, the optimal placement and sizing of two DGs in the standard IEEE 33-bus network have been investigated with three objective functions which are the reduction of network losses, the improvement of voltage profiles, and cost reduction. In this way, by using the backward-forward load distribution, the load distribution is performed on the 33-bus network with the power summation method to obtain the total system losses and the average bus voltage. Then, using the iterative search algorithm and considering problem constraints, placement and sizing are done for two DGs to obtain all the possible answers and next, among these answers three answers are extracted as the best answers through three methods of fuzzy logic, the weighted sum, and the shortest distance from the origin. Also, using the multi-objective non-dominated sorting genetic algorithm II (NSGA-II) and setting the algorithm parameters, thirty-six Pareto fronts are obtained and from each Pareto front, with the help of three methods of fuzzy logic, weighted sum, and the shortest distance from the origin, three answers are extracted as the best answers. Finally, the answer which shows the least difference among the responses of the iterative search algorithm is selected as the best answer. The simulation results verify the performance and efficiency of the proposed method.
Źródło:
Archives of Electrical Engineering; 2023, 72, 1; 253--271
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial intelligence-based decision-making algorithms, Internet of Things sensing networks, and sustainable cyber-physical management systems in big data-driven cognitive manufacturing
Autorzy:
Lazaroiu, George
Androniceanu, Armenia
Grecu, Iulia
Grecu, Gheorghe
Neguriță, Octav
Powiązania:
https://bibliotekanauki.pl/articles/19322650.pdf
Data publikacji:
2022
Wydawca:
Instytut Badań Gospodarczych
Tematy:
cognitive manufacturing
Artificial Intelligence of Things
cyber-physical system
big data-driven deep learning
real-time scheduling algorithm
smart device
sustainable product lifecycle management
Opis:
Research background: With increasing evidence of cognitive technologies progressively integrating themselves at all levels of the manufacturing enterprises, there is an instrumental need for comprehending how cognitive manufacturing systems can provide increased value and precision in complex operational processes. Purpose of the article: In this research, prior findings were cumulated proving that cognitive manufacturing integrates artificial intelligence-based decision-making algorithms, real-time big data analytics, sustainable industrial value creation, and digitized mass production. Methods: Throughout April and June 2022, by employing Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines, a quantitative literature review of ProQuest, Scopus, and the Web of Science databases was performed, with search terms including "cognitive Industrial Internet of Things", "cognitive automation", "cognitive manufacturing systems", "cognitively-enhanced machine", "cognitive technology-driven automation", "cognitive computing technologies", and "cognitive technologies". The Systematic Review Data Repository (SRDR) was leveraged, a software program for the collecting, processing, and analysis of data for our research. The quality of the selected scholarly sources was evaluated by harnessing the Mixed Method Appraisal Tool (MMAT). AMSTAR (Assessing the Methodological Quality of Systematic Reviews) deployed artificial intelligence and intelligent workflows, and Dedoose was used for mixed methods research. VOSviewer layout algorithms and Dimensions bibliometric mapping served as data visualization tools. Findings & value added: Cognitive manufacturing systems is developed on sustainable product lifecycle management, Internet of Things-based real-time production logistics, and deep learning-assisted smart process planning, optimizing value creation capabilities and artificial intelligence-based decision-making algorithms. Subsequent interest should be oriented to how predictive maintenance can assist in cognitive manufacturing by use of artificial intelligence-based decision-making algorithms, real-time big data analytics, sustainable industrial value creation, and digitized mass production.
Źródło:
Oeconomia Copernicana; 2022, 13, 4; 1047-1080
2083-1277
Pojawia się w:
Oeconomia Copernicana
Dostawca treści:
Biblioteka Nauki
Artykuł
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