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1

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

Feng Sijing

Ecological Chemistry and Engineering. S

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2024

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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.

2

Autonomous shipping – a stochastic model of the process describing the safety of MASS operation

Burciu Zbigniew, Abramowicz-Gerigk Teresa

Zeszyty Naukowe Politechniki Morskiej w Szczecinie

|

2023

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nr 76 (148)

57--64

EN

The main interest in introducing maritime autonomous surface ships (MASS) is centered on communication, autonomous navigation, and collision avoidance systems. This paper presents a more comprehensive approach, accounting for selected issues relating to navigation safety, ship operation, maritime rescue, and decision support systems for the MASS remote managing operator. The technical solutions for improving the safety of MASS operation are described, and the decision support system (DSS) for the MASS operator, based on the stochastic model of the process describing the safety of MASS operation, is proposed. The presented analysis can be used to build a computer program and an integrated decision support system that increases the safety and reliability of the MASS operator’s decision-making process.

3

Developing a Decision Support System for Supply Chain Component

Andry Johanes Fernandes, Nurprihatin Filscha, Liliana Lydia

Management and Production Engineering Review

|

2023

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Vol. 14, No. 2

124--133

EN

Increased competition has led businesses to compete with each other in streamlining supply chain processes, especially in the manufacturing sector. Supply Chain Management (SCM) determines the success of industrial business processes because it regulates product flow regarding integration, performance, and information. However, several problems have emerged in the supply chain process, such as a lack of coordination in the production queue, difficulties in forecasting trending products, and suboptimal production capacity. To address these issues, the role of information technology is crucial for implementing a Decision Support System (DSS). This study aims to develop a DSS to improve the supply chain processes. The research method used is Extreme Programming (XP) with a qualitative approach through a questionnaire. The research process involves collecting data, defining boundaries and problems, and designing, coding, and testing the system. As a final step, evaluation is carried out by distributing surveys to obtain valid satisfaction results. This research produces a DSS that has applicability in marketing, accounting, and production processes. The application of DSS in the furniture manufacturing industry can help manage the movement of resources, optimize strategic networks, and assist decision-making in the supply chain process.

4

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

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

Cybersecurity and Law

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2023

|

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.

5

Supply Chain Disruptions Mitigation Plan Using Six Sigma Method for Sustainable Technology Infrastructure

Andry Johanes Fernandes, Nurprihatin Filscha, Liliana Lydia

Management and Production Engineering Review

|

2022

|

Vol. 13, No. 4

88--97

EN

Supply Chain Management (SCM) is a very important part of the industrial world, especially in the manufacturing sector. The development of the business world affects the complexity of the supply chain due to the lack of logistics infrastructure, quality of materials and components, and much more. Supply chain disruption risk mapping needs to be done due to high uncertainty, which is overcome by implementing a decision support system. Based on the background of the problem, supply chain disruption mapping uses the help of the Six Sigma method, which consists of 5 stages: Define, Measure, Analyze, Improve, and Control (DMAIC). The measurement of disturbance also uses the Failure Mode and Effect Analysis (FMEA) approach to prioritize risk. Risks that have a high assessment and cause failure need to be prioritized for improvement. This study aims to map supply chain disruptions in the current manufacturing industry based on the barriers, resistances, and causes detected for making a decision support system prototype. By implementing a decision support system in the supply chain process, it is hoped that the manufacturing industry can minimize potential losses from existing risks.

6

Concept and implementation of the Polish innovative agro-hydro-meteorological monitoring (AgHMM) in INOMEL Project

Kanecka-Geszke Ewa, Bąk Bogdan, Bolewski Tymoteusz, Kaca Edmund

Journal of Water and Land Development

|

2021

|

no. 51

256--264

EN

The paper presents the concept and deployment of the agro-hydro-meteorological monitoring system (abbrev. AgHMM) created for the purposes of operational planning of regulated drainage and irrigation on the scale of a drainage/irrigation system (INOMEL project). Monitoring system involved regular daily (weekly readings) measurements of agrometeorological and hydrological parameters in water courses at melioration object during vegetation seasons. The measurement results enable an assessment of the meteorological conditions, moisture changes in the 0-60 cm soil profile, fluctuations of groundwater levels at quarters and testing points, also water levels in ditches and at dam structures, and water flow in water courses. These data were supplemended by 7-day meteorological forecast parameter predictions, served as input data for a model of operational planning of drainage and subirrigation at the six melioration systems in Poland. In addition, it was carried out irregular remote sensing observations of plant condition, water consumption by plants and soil moisture levels using imagery taken by unmanned aerial vehicles and Sentinel’s satellites. All the collected data was used for support operational activities aimed at maintaining optimal soil moisture for plant growth and should to provide farmers with high and stable yields. An example of the practical operations using the AgHMM system in 2019 is shown on the basis of the subirrigation object at permanent grasslands located in central Poland called “Czarny Rów B1”.

7

Mathematical methods of signal analysis applied in medical diagnostic

Ciecierski Konrad A.

International Journal of Applied Mathematics and Computer Science

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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

Application of Artificial Neural Networks in the Analysis of Mechanisms Destroying Forging Tools

Hawryluk M., Mrzygłód B., Gronostajski Z., Głowacki M., Olejarczyk-Wożeńska I.

Archives of Metallurgy and Materials

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2020

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Vol. 65, iss. 1

193--200

EN

This article discusses the results of studies using the developed artificial neural networks in the analysis of the occurrence of the four main mechanisms destroying the selected forging tools subjected to five different surface treatment variants (nitrided layer, pad welded layer and three hybrid layers, i.e. AlCrTiSiN, Cr/CrN and Cr/AlCrTiN). Knowledge of the forging tool durability, needed in the process of artificial neural network training, was included in the set of training data (about 800 records) derived from long-term comprehensive research carried out under industrial conditions. Based on this set, neural networks with different architectures were developed and the results concerning the intensity of the occurrence of thermal-mechanical fatigue, abrasive wear, mechanical fatigue and plastic deformation were generated for each type of the applied treatment relative to the number of forgings, pressure, friction path and temperature.

10

Development of decision support system based on feature matrix for cyber threat assessment

Kartbayev Timur, Akhmetov Bakhytzhan, Doszhanova Aliya, Lakhno Valery, Malikova Feruza, Tolybayev Sharapatdin

International Journal of Electronics and Telecommunications

|

2019

|

Vol. 65, No. 4

545--550

EN

The article herein presents the method and algorithms for forming the feature space for the base of intellectualized system knowledge for the support system in the cyber threats and anomalies tasks. The system being elaborated might be used both autonomously by cyber threat services analysts and jointly with information protection complex systems. It is shown, that advised algorithms allow supplementing dynamically the knowledge base upon appearing the new threats, which permits to cut the time of their recognition and analysis, in particular, for cases of hard-to-explain features and reduce the false responses in threat recognizing systems, anomalies and attacks at informatization objects. It is stated herein, that collectively with the outcomes of previous authors investigations, the offered algorithms of forming the feature space for identifying cyber threats within decisions making support system are more effective. It is reached at the expense of the fact, that, comparing to existing decisions, the described decisions in the article, allow separate considering the task of threat recognition in the frame of the known classes, and if necessary supplementing feature space for the new threat types. It is demonstrated, that new threats features often initially are not identified within the frame of existing base of threat classes knowledge in the decision support system. As well the methods and advised algorithms allow fulfilling the time-efficient cyber threats classification for a definite informatization object.

11

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

|

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.

12

Spiking Neural Network Based on Cusp Catastrophe Theory

Huderek Damian, Szczęsny Szymon, Rato Raul

Foundations of Computing and Decision Sciences

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2019

|

Vol. 44, No. 3

273--284

EN

This paper addresses the problem of effective processing using third generation neural networks. The article features two new models of spiking neurons based on the cusp catastrophe theory. The effectiveness of the models is demonstrated with an example of a network composed of three neurons solving the problem of linear inseparability of the XOR function. The proposed solutions are dedicated to hardware implementation using the Edge computing strategy. The paper presents simulation results and outlines further research direction in the field of practical applications and implementations using nanometer CMOS technologies and the current processing mode.

13

Support of Decision-Making under Risk by a Risk-Averse Decision-Maker

Łodziński Andrzej

Decision Making in Manufacturing and Services

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2019

|

Vol. 13, no. 1-2

73--83

EN

The paper presents a method of supporting decision-making under risk by a risk- -averse decision-maker. Decision-making under risk occurs when the outcome of the system is ambiguous and depends on the state of the environment. The problem is considered as a multi-criteria optimization. The decision support method consists of interactive conduct of the process of decision-making. The decision is made by means of solving a problem with controlling parameters, which determine the aspirations of the decision-maker and evaluating the obtained solutions. The decision-maker sets parameters for which a solution is determined. Subsequently, he or she assesses the obtained solution, accepting or rejecting it. In the latter case, the decision-maker sets new values for the parameters and the problem is solved again. The present paper presents a discrete example of support for decision making under risk.

14

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

|

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.

15

Analiza istotności cech znamion skórnych dla celów diagnostyki czerniaka złośliwego

Mikołajczyk A., Grochowski M.

Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej

|

2018

|

Nr 60

67--70

PL

Pomimo dynamicznego rozwoju metod uczenia maszynowego i ich wdrażania do praktyki lekarskiej, automatyczna analiza znamion skórnych wciąż jest nierozwiązanym problemem. Poniższy artykuł proponuje zastosowanie algorytmu ewolucyjnego do zaprojektowania, wytrenowania i przetestowania całych populacji klasyfikatorów (sztucznych sieci neuronowych) oraz ich iteracyjnego udoskonalania w każdej kolejnej populacji, w celu osiągnięcia jak najlepszej dokładności klasyfikacji znamion skórnych. Algorytm zwraca optymalny zestaw cech opisujących obraz dermatoskopowy wraz z proponowaną architekturą sieci neuronowej. Uzyskano dokładność równą 85,83%, swoistość równą 79,07% oraz czułość równą 92,60%.

EN

Despite the dynamic development of machine learning methods, automatic analysis of skin lesions is still open issue. The following article proposes the use of an evolutionary algorithm to design, train, and to test a whole population of classifiers (artificial neural networks) and to iteratively improve them in each subsequent population, in order to achieve the best possible accuracy in the classification of skin lesions task. The algorithm returns an optimal set of features describing the dermatoscopic image together with the proposed architecture of the neural network. High classification results were obtained, in particular: accuracy equal to 85.83%, specificity 79.07% and sensitivity 92.60%.

16

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.

17

Rozmyty system wspomagania decyzji na przykładzie próby obrony rzutów karnych

Banasik A., Krakowczyk J., Lawnik M.

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

|

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.

18

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.

19

Fundamental principles of passage planning for autonomous vessels

Wołejsza P., Kulbiej E.

Zeszyty Naukowe Akademii Morskiej w Szczecinie

|

2017

|

nr 52 (124)

90--94

EN

This article aims to depict the fundamentals of passage planning and route management for an autonomous vessels (AV). It presents a derivation of such a voyage passage plan, its step-by-step analysis, and a comparison to its conventional equivalent. This passage plan consists of four major parts: dock and harbour, en route, approach, and mooring stages. The whole activity of passage planning itself may be divided into the following stages: appraisal, planning, execution, and monitoring. The paper concludes with an overview of potential future applications and use of mentioned content.

20

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.