This paper introduces WEIghts COMpromise (WEICOM), a novel aggregation method designed to derive a consensus weight vector in Multi-Criteria Decision Analysis (MCDA) involving multiple expert inputs. WEICOM aims to maximize the average similarity, measured by the Weights Similarity Coefficient 2 (WSC2), between the aggregated vector and a set of initial weight vectors, ensuring a balanced representation of all expert preferences. The method is applied to a real-world case study, assessing energy-related sustainability indicators in agri-food systems. The study evaluates the energy performance of countries based on six key criteria, including CO 2 emissions, on-farm energy use, and waste disposal. In addition, a simulation study is conducted to assess the robustness of WEICOM under varying numbers of criteria and experts, comparing its performance with tradition aggregation methods such as mean, median, and maximin. Results from both empirical and simulation-based analyses demonstra that WEICOM consistently outperforms conventional aggregation techniques, offering a more stable and transparent solution for integrating expert judgments in complex decision-making contexts. This approach provides valuable insights for applications in sustainability assessments, participatory decision-making, and environmental policy evaluations.

European countries’ efforts to achieve goals such as reducing the environmental damage caused by development require an increase in the share of renewable energy sources (RES) in energy-using industries. Such an energy policy makes it possible to reduce the consumption of fossil fuels, which contributes to improving the quality of the environment and reducing the depletion of natural resources. Efficient energy systems providing a secure energy supply should be diversified, i.e., based on a sustainable share of RES in the various branches of the economy. In the assessment of sustainable RES-based energy systems, multi-criteria decision analysis methods (MCDA), which allow simultaneous consideration of multiple aspects arising from the requirement for RES diversification, are proving useful. However, not all methods consider the strong sustainability paradigm including reduced criteria compensation relevant to sustainability assessment. In order to address this research gap, we propose the SSP-SPOTIS (Strong Sustainability Paradigm based Stable Preference Ordering Towards Ideal Solution) method to model the reduction of linear criteria compensation. The SSP-SPOTIS method has several advantages, such as robustness to ranking reversals, a simple algorithm, and the possibility to determine reference solutions individually. The mentioned advantages, combined with consideration of the strong sustainability paradigm, make the proposed approach useful in practical sustainability assessment problems. In this paper, the applicability of SSP-SPOTIS is demonstrated for the problem of assessing the sustainable share of RES in the economies of selected European countries. The results obtained indicate that the most sustainable share of RES is presented by Nordic countries such as Sweden, Norway, Denmark, and Finland. In addition, Estonia, and Austria were also among the well-scored countries.

This paper presents research involving the selection of floating photovoltaics (FPV) system constructions under Polish conditions using a multi-criteria method incorporating criteria compensation reduction following the strong sustainability paradigm.The applied method is called SSP-COPRAS (Strong Sustainability Paradigm based Complex Proportional Assessment).The selection was carried out among four FPV designs and one reference conventional ground-mounted PV (GMPV) system.Data were obtained from the reference research paper.The results proved that the FPV system has a noticeable potential for making it competitive with GMPV, especially when technical criteria and criteria compensation reduction play an important role.However, GMPV's higher ratings, especially in terms of economics, show that FPV would have to reach a higher product maturity to become realistically competitive.

Sustainable transport can contribute to many beneficial changes, such as reducing greenhouse gas emissions and pollutants into the atmosphere, improving the country's energy security, and enhancing energy efficiency.Therefore, it is essential to provide a framework for reliable measurement of sustainable transport, enabling its evaluation in terms of diversity and the significance of renewable energy sources (RES).This paper presents a methodological framework for a multi-criteria assessment of sustainable transportation.The proposed framework is based on three multi-criteria decision analysis (MCDA) methods: SPOTIS (Stable Preference Ordering Towards Ideal Solution), ARAS (Additive Ratio Assessment), and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution).The application of the proposed tool is demonstrated in an illustrative example of the assessment of European countries in terms of the share of alternative fuels in final energy consumption in road transport.The authors used the proposed framework to perform a comparative analysis considering three MCDA methods and two methods for determining the significance of evaluation criteria: equal and entropy weighting methods.The investigation has proven the practical suitability of the proposed tool in the problem of multi-criteria sustainable transport assessment.Furthermore, conducted analysis indicated that Sweden is characterized by the most sustainable transport in terms of significance and share of alternative fuels and RES and their diversification.

Assessment of the sustainability of countries for afordable and clean Energy requires a framework with relevant criteria, simultaneous inclusion of multiple criteria in the evaluation, and consideration of the dynamics of changes in performance over time. A wide variety of multi-criteria decision analysis (MCDA) approaches using different algorithms for multi-criteria aggregation are currently available. These methods are suitable for sustainability assessment because they allow the consideration of multiple criteria, the construction of a hierarchical structure of criteria, and the assignment of significance to criteria weights. However, MCDA methods have the limitation of being able to evaluate a data set for a single moment in time, which is insufficient for the sustainability paradigm. The mentioned limitation of MCDA motivates researchers to develop approaches that adapt MCDA methods to temporal assessment. The purpose of this paper is to present the application of a method called Data vARIability Assessment Technique for Order of Preference by Similarity to Ideal Solution (the DARIA-TOPSIS method) for multi-criteria temporal assessment of European countries for affordable and clean energy. This aspect of sustainability is included in Sustainable Development Goal 7 proposed by United Nations in the 2030 Agenda for Sustainable Development. The DARIA-TOPSIS method combines the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for multi-criteria evaluation with a Gini coefficient-based measure of result variability. The method has identified the best-scored countries in terms of implementing sustainable energy policies focused on affordable and clean energy, including Norway, Iceland, and Sweden.

Reliable assessment of countries’ energy policy implementation across multiple dimensions and sectors requires appropriate tools and methods. Monitoring the situation of countries in terms of renewable energy sources (RES) makes it possible to rank them and assess their progress. Multi-criteria decision analysis methods (MCDA) are valuable in this field because they allow considering multiple conficting criteria and prioritizing according to the preferences given by decision-makers. This work presents the application of two MCDA methods to assess the sustainable use of RES in different sectors in 30 European countries. The applied methods, which are COmbinative Distance-based ASsessment (CODAS) and Weighted Aggregated Sum Product Assessment (WASPAS), include in their algorithms additional adjustable parameters which enable performing sensitivity analysis of the evaluated alternatives. In this way, it is possible to determine the stability of the considered solutions in the rankings. The study identified the best-ranked countries regarding sustainable RES usage, including the Nordic countries such as Sweden, Norway, Iceland, and Finland. In addition to the Nordic countries, Austria is also among the best-scored countries.

Using fuzzy logic in multi-criteria problems allows real-world problems to be modeled with greater accuracy. In addition, it is possible to solve problems in which all data are incomplete. The difficulty may be the choice of an appropriate technique leading to a ranking calculation. Methods fully integrated with fuzzy logic can be used. It is also possible to convert fuzzy data to crisp values and then apply traditional MCDA methods. In this paper, the performance of the TOPSIS method in a crisp and fuzzy environment was analyzed. The approaches of operating fully on uncertain data when calculating preference values were compared with converting data to crisp values using selected membership functions. The research has shown that significant differences and discrepancies in how the alternatives are classified are noticeable in the rankings.

The practical capabilities of decision support systems are beneficial in many complex problems. They aim to equip the decision-maker with knowledge about the preferred choices from the set under consideration. Often, there are minor differences between the alternatives analyzed, making it necessary to determine whether changes in the parameters characterizing them can influence their final position. For this purpose, a sensitivity analysis of the solutions can be used to examine the resistance of the results to changes. In this paper, we address the problem of performing the sensitivity analysis using MCDA methods. Most studies focus on testing the sensitivity of rankings of popular methods. However, their main disadvantage is their susceptibility to the phenomenon of ranking reversal. It may distort the results obtained in a sensitivity analysis. Therefore, it is worth using methods resistant to the ranking reversal phenomenon for this purpose. The SPOTIS and COMET methods were used in a theoretical multi-criteria problem, where the calculated results were then subjected to sensitivity analysis. The study showed that the SPOTIS method tends to be more robust to the computed results.

Objective evaluation in problems considering many, often conflicting criteria is challenging for the decision-maker.This paper presents an approach based on MCDA methods to objectify evaluations in the camera selection problem.The proposed approach includes three MCDA methods, TOPSIS, VIKOR, COMET, and two criterion weighting techniques.Two ranking similarity coefficients were used to compare the resulting rankings of the alternatives: W S and rw.The performed research confirmed the importance of the appropriate selection of multicriteria decision-making methods for the solved problem and the relevance of comparative analysis in method selection and construction of objective rankings of alternatives.

Mobile phones are devices that are nowadays widely used by people. The development of technology has resulted in them being used not only for talking and messaging. They have functionalities that make them similar to personal computers. These devices are used to send and receive e-mails, browse the web, organize time, take pictures, play games, listen to music. There is also a possibility of installing various applications on them. The capabilities of these devices are closely related to their parameters, such as memory card size, internal memory, RAM, camera resolution. Price, which increases with the improvement of the parameters, also is a significant criterion of choice. Therefore, the choice of the most appropriate mobile phone model to match the consumer’s expectations requires the consideration of many criteria. Choosing the best option when making a decision is challenging because many factors influence the final decision. Additionally, they can be very diverse and difficult to take into account as a whole. An excellent solution to this problem is multi-criteria decision analysis (MCDA) methods, which support choosing from a wide variety of criteria. In this paper, four methods from the MCDA group - COMET, PROMETHEE II, VIKOR and TOPSIS - were used to determine the best mobile phone model among a group of alternatives. It is a complicated issue given the number of models available on the market and the number of parameters to consider when comparing. These methods have been successfully applied in the past to solve problems of similar complexity. All alternatives were analyzed using each method. Then the results were compared to each other to evaluate their similarity. Thus, the best mobile phone was selected for every applied method, and an attempt was made to find out the effect of MCDA method selection on the final ranking. The results obtained show that the tool based on MCDA methods is useful, appropriate, and effective in supporting consumer decisions when choosing mobile phones.

Everyday situations each day more often require us to solve sometimes even complex decisional problems. Such conditions may include the problem of choice when purchasing services, products or devices. The ever-increasing assortment of products and services makes it more and more time-consuming for customers to choose the most suitable product for them. Following their intuition or considering only some selection criteria may result in an unsatisfactory choice. Decision making in multi-criteria selection problems needs the consideration of many factors, which are often conflicting. For this purpose, more people reach for multi-criteria decision methods (MCDM). These methods provide an easy way of solving a given problem under certain circumstances. With the increasing popularity of those methods, more are developed each day. This paper presents an approach based on four MCDM methods applied to solve the problem of choosing the most favourable CPU model available on the market regarding price and performance, among other criteria. For this purpose, COMET, TOPSIS, VIKOR and PROMETHEE II methods were performed. Later, a comparative analysis of the rankings obtained using the applied methods was conducted. Rankings provided by used methods were compared using correlation coefficients. The research showed that choosing a specific method is relevant for the results and that real-life problems can be successfully solved using multi-criteria decision methods. The obtained results confirm the suitability of MCDM methods as a decision support tool for consumers’ product selection. Applications based on MCDM allowing customers to perform multi-criteria analysis of a set of products could contribute to increased consumer satisfaction and growth of popularity and competitiveness of online stores providing them.

Multi-criteria methods are used in systems designed to support decision-making or for prediction. One of these methods is the Characteristic Objects Method (COMET), which uses expert knowledge to calculate preference values when creating a rule base. The number of Characteristic Objects (COs) pairs necessary to perform comparisons depends on the model’s structure, the number of criteria and characteristic values. In this paper, it was decided to build a complex MCDM model based on the COMET method, which was used to predict the chances of overtaking during pit stops in Formula 1 races. To improve the performance of the model and reduce the necessary pairwise comparisons of COs, it was decided to split the structure into submodels aggregating criteria with similar characteristics to reduce the complexity of the problem. Additionally, the influence of each criterion on the obtained preference values and the final result was examined. By restructuring the model, it was possible to reduce the number of comparisons while maintaining the designed model’s correct operation.

The methods of multi-criteria decision analysis are widely used for problems of selecting the best solution or ordering their sets. In the vast majority of cases, solving multi-criteria decision-making problems focuses on finding solutions for a given set of alternatives. When, for one or more decisional variants, the values of their attributes change, or a new alternative for assessment appears, the problem occurs. Therefore, in this paper, we focus on identifying the full decision-making model in the issue related to the study case of production line optimization. In this work, the Characteristic Objects METhod (COMET) has been applied. In effect, it identifies the full decision-making model. The decision problem has been identified, taking into account six decision criteria, and its operation has been used in organizing four decision alternatives.

The widespread popularity and spread of ontologies in many areas increasingly requires the successful integration of multiple such ontologies. The ontology integration problem has been investigated during last years and it is still a challenging task. Aligning and merging existing ontologies, which are usually handled manually, is often a big and tedious part of the sharing process. Due to the fact that there are different approaches, tools and strategies that help to avoid mistakes during modeling especially large domains and creating a new single coherent ontology, this article attempts to build a common knowledge repository in the form of an open and publicly available tool. The overall goal of the proposed open knowledge repository is to provide free access to basic data and to compare the features offered. It is worth mentioning that this form of knowledge representation is publicly available and focuses on the possibility of updating and reusing. It is an attempt to structure knowledge that can be successfully extended with additional groups of solutions and parameters. The proposed approach can be easily implemented as a light library and used in any type of OWL/RDF or OWL/XML management application or adapted in a given management information system.

Ontologies are a key element of the Semantic Web. They aim to capture basic knowledge by providing appropriate terms and formal relationships between them, so that they can be used in a machine-processable manner. Accordingly they enable automatic aggregation and practical use as well as unexpected reuse of distributed data sources. Ontologies may come from many different sources, pursuing different goals and quality criteria. However, performed manually ontology construction is a very complex and tedious task, thus many methods proposed offer automatic or semi-automatic way for ontology construction. Many of the methods have their own, specific features. Therefore, this paper proposes an extensive knowledge-based approach covering the domain of ontology learning methods from text. This work aims to collect the knowledge of available approaches for ontology learning and the prominent differences between them, drawing on best practices in ontology engineering. The proposed approach refers to methods and aims to enrich knowledge in the field of ontology learning (OL). In this paper, the author’s ontology contains a set of various types of methods with main techniques used, and the necessary features in the miscellaneous approaches. The proposed an extensive knowledge-based approach uses a reasoning mechanism based on competency questions for individual approaches to determine their ontology learning method profiles. The validation stage has also been carried out. At the same time, it is an extension of the previous study in the form of a repository of knowledge about OL tools. In addition, the combination of both ontologies: tools and methods aim to provide a more efficient OL solution from text.

The problem of optimization assembly lines for rarely repeatable products with low volumes will be addressed in this paper. In this kind of production each product should be treated as a project with different cycle time on each station. Balance of assembly lines processing separate projects is impacted by uncertainty, assembly methods are not fully automated. Daily operations in this kind of activity needed an effective and fast method to support decision making by assembly line managers and production planners. For this purpose Analytical Hierarchy Method (AHP) and TOPSIS methods are used. The empirical study presents four possible optimization configurations for comparison and evaluation using the AHP and TOPSIS methods.

Spreading of information within social media and techniques related to viral marketing take more and more attention from companies focused on targeting audiences within electronic systems.Recent years resulted in extensive research centered around spreading models, selection of initial nodes within networks and identification of campaign characteristics affecting the assumed goals.While social networks are usually based on complex structures and high number of users, the ability to perform detailed analysis of mechanics behind the spreading processes is very limited.The presented study shows an approach for selection of campaign parameters with the use of network samples and theoretical models.Instead of processing simulations on large network, smaller samples and theoretical networks are used.Results showed that knowledge derived from relatively smaller structures is helpful for initialization of spreading processes within the target network of larger size.Apart from agent based modeling, multi-criteria methods were used for evaluation of results from the perspective of costs and performance.

Information spreading processes are main drivers of viral campaigns. They are usually conducted within large scale social networks. Parametrisation of online campaigns is usually related to allocation of budgets, number of seeds and strategies of their selection. It is hard to predict campaign effects. Proposed in this paper approach uses network samples to select appropriate strategy for use within complete network. Results showed how scaling of samples is affecting approximation quality. Multi-criteria analysis of performance allows for strategy selection according to preferences and goals.

This paper provides a comparative study of ICT (information and communication technologies) and SIS (sustainable information society) measurement in Polish households using a MCDA-based approach in aim to advance the information society research and practice by examining and understanding the ICT adoption in households for improving SIS. This study employs a quantitative approach to measure the ICT adoption in Polish households. Survey questionnaires were used and data collected from 679 households were analyzed to identify the levels of ICT adoption. Multi-criteria decision analysis (MCDA) Analytic Hierarchy Process (AHP) method was used for evaluation of the collected data. This study advances the information society research and practice by developing an approach to measure the ICT adoption.

In the article is presented methodological approaches of Vector Measure Construction Method (VMCM) used to analyze complex socio-economic process described by many features (indicators). The outcome of the analysis has the most reliable and acceptable representation of the studied process specific to chosen case. In order to solve complex problems (depending on the situation, case under consideration), methods from multidimensional comparative analysis groups are very useful and most often used. In the article will be presented the general methodological assumptions of VMCM method, the advantages of using it in context of consumer issues and there will be presented application of the method to estimate consumer’s quality of life in different EU countries. It will be presented in dynamic perspective comparing changes over 8 years (since year 2010 to 2017).

Recent years the term of sustainability has received increased meaning in successful management. Consequently, a lot of attention is paid for developing effective means to support this process. The concept of sustainable management is an important focal point for decision-makers in business. To advance sustainable management activities, obviously an adequate and modern approach is needed. Actual research trends confirm that knowledge management gives a way to handle domain knowledge practically and effectively. Thus, the practical application of knowledge-based mechanisms may provide a relevant instrument. This paper addresses the specific kind of problem of domain knowledge handling in sustainable management. In scientific terms, the paper presents an attempt of knowledge handling in the form of domain ontology for sustainable management. Presented case studies show the practical capabilities of proposed approach.

At present, companies need to consider and include so-called ‘green strategies’ in order to retain competitive advantage. The common understanding of functionality of supply chain as well as collaborations among this between suppliers and partners means that companies need to do much more in order to ensure the greener effect. On the other hand, a scattered model of conducting businesses and global competition force companies to consider the necessity for development the activities of proper selection and evaluation of beneficial supply chain partnerships. Due to large amount of literature-based references of green supplier selection and evaluation, knowledge scattering of greener collaboration is noticeable. In addressing this research challenge, capturing knowledge in one place in the form of ontology for enabling selection and evaluation criteria of suppliers is proposed. Within this paper, an attempt to application of ontology-based model for supplier’ selection and evaluation criteria is developed. This model is implemented on base of distinctive set of criteria derived from revised literature, nevertheless the public and common availability of the proposed model suggests to other researches to collaborate in this field by adding, sharing and reusing knowledge of alternative criteria of green supplier’ selection.

The process of sustainable supplier selection is crucial to a company's business continuity.Distortions in poorly chosen suppliers can lead to an impediment or even complete downtime of the company's operations.The paper proposes a new unique approach in which classical MCDA paradigm is extended with aspects of temporal evaluation and various temporal aggregation strategies are provided.The partial MCDA evaluations are performed with three MCDA methods -AHP, TOPSIS and COMET -to allow for hierarchical structuring of the decision problem, creation of a reference model and avoiding rank reversal.The proposed approach is verified on a case study with an actual company and its supplier selection from a group of 30 potential suppliers.

In the recent years, a growing popularity of knowledge management and knowledge conceptualization in the form of ontology is observed. However, one of the most important and up-to-date challenges infolds the quality evaluation of knowledge conceptualization. The prospective mistakes and omissions in ontologies have an influence on the exploitation of the full potential of exchanging data. For this reason, the process of ontology evaluation has a great impact on the higher degree of reuse and a better cooperation over the boundaries of applications and domains. However, this process is quite complex and it requires the specified knowledge about available methods and tools supporting the ontology evaluation process. This paper discusses existing evaluation metrics supporting the ontology evaluation process. Based on this, the author’s proposal of ontology-based approach for evaluation metrics is provided, offering a useful guidance to knowledge handling, conceptualization and representation, and using knowledge engineering.

This paper investigates the problem of the sustainable ammonium nitrate transport.The significance of this problem is increasing, considered the occurrence of the worldwide agricultural production boost.The existing international regulations for the transport of the dangerous chemical substances are not sufficient to obtain a satisfactory solution for the sustainable transport.The main reason for that is the fact that the safety criteria can easily become dominated by the economic factors.In this paper, the authors use the COMET method to identify a decision making model for the selection of the best scenario of sustainable transport.The COMET method is a new multicriteria decision-making technique that is free of the rank reversal phenomenon.The identified model provides information about the global and local significance level of each of the criteria.The proposed approach can be easily expanded by using a greater number of criteria, depending on the particular problem analyzed.The proposed methodology is an efficient and highly accurate solution to make decisions based on experts' knowledge.

Due to high availability of e-commerce websites providing similar services and products, the website usability becomes one of the most critical factors affecting online businesses' success.Therefore, website quality and user experience evaluation is an important research task.There are multiple methodologies for performing the evaluation.The proposed in our earlier studies PEQUAL methodology extends the classical eQual method by taking into account different aspects of preference modeling and aggregation derived from Multi-Criteria Decision Analysis (MCDA).This paper extends the PEQUAL methodology further by incorporating eye tracking based measurement and analysis into the criteria set.The results of the conducted empirical verification of proposed approach are presented.

Detecting and recognizing brake lights is essential to avoid collisions and accidents caused by a vehicle driving behind another vehicle. This refers to traffic risk, among other things, to man-controlled vehicles as well as autonomous cars. There are many systems supporting drivers, which are also applied in autonomous cars. This paper presents a mobile decision-making system warning against traffic risks related to breaking a preceding vehicle. The new approach is two-stage and real-time one. Unlike other approaches, the presented solution, thanks to proper limitation of a searched area, works effectively on a mobile platform with restricted system resources. The results of experiments conducted on real video sequences on roads in various weather conditions showed high effectiveness of the proposed approach.

A key aspect of successively maintaining a store on the market is the analysis of customer typology. By understanding individual segments of consumers, entrepreneurs are able to make big profits. This article proposes the methodological approach of the decision support system for identifying Internet customer typology. The conceptual framework was developed and on this basis a prototype of an online shop for conducting experiments was developed. A group of randomly selected users was isolated, and on the basis of the obtained data their clustering was performed by cluster analysis. The typology of online shop users has been created. Additionally, by introducing a prediction mechanism based on the mathematical model of the Graph Cellular Automaton, the new customer can be quickly adjusted to the defined group of shop customers.

Exchange of digital goods may not be as easy to perform as it seems. We must consider the fact that one or both participants of the exchange may be dishonest and simply try to misbehave and disappear after gaining some kind of advantage over the other participant. Therefore, it is important to design exchange protocols in such a way that no one can cheat. Either all participants receive the electronic goods they expect or all participants receive nothing at all, provided that any of the participating parties abstained from, or aborted the exchange at any time before the end. Protocols which are designed in such a manner are called fair secret exchange protocols. Fairness of a protocol guarantees that no party can misbehave, and even if they manage to do so, they will be caught and prosecuted. In this paper, we suggest a protocol for fair distribution of invoices based on the aforementioned protocols, and we conduct an experiment that evaluates how the security and fairness of the process of sharing an electronic invoice between the issuer and the customer is increased. The proposed protocol’s fairness and performance evaluation results are also presented.

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The MCDA methods are used in order to solve complex decision-making problems which require considering many interrelated criteria. They are also the basis of DSS. Nevertheless, these dependencies between criteria can have an influence on the obtained solution. A class of decision-making problems, in which there are intercriteria dependencies, are decisions in the sustainability area, e.g. selection of a location and a design of an RES-based power station. The article presents a complex model, taking into consideration dependencies between criteria.

The design of web applications includes the use of components that attempt to increase influence on target audience to achieve expected results in the form of interactions. In this area, conflicts between user experience and business goals are observed, especially when primary tasks within a website are negatively affected by intrusive marketing messages. The proposed in this paper approach based on perceptual experiments is related to modeling the structure of interactive objects and building an inference model, with the main purpose being to determine the response from web users using different levels of influence. The obtained results, compared with online responses from an actual campaign, provide the possibility to adopt compromise solutions through designing Internet applications with an expected outcome and minimizing negative responses without interfering with user experience.

Multi-criteria decision analysis (MCDA) methods have become increasingly popular in decision-making.Numerous methods in this field were developed to solve realworld decision problems including various engineering and scientific areas.Unfortunately, the proper use of each method is difficult due to the dispersion of the domain knowledge and lack of knowledge databases in this area.The paper presents research focused on knowledge management aspects in MCDA domain.In order to achieve a high level of practicality on different levels of decision making, the ontology as a form of conceptualization is implemented.

The aim of this article is to present the methodological framework for Decision Support System for the process of selecting the location of renewable energy sources.For this purpose, the paper presents the methodology and MCDA methods sequentially structuralizing and modeling the decision space and exploiting the developed model.The detailed area of research and verification of proposed approach are related to the problem of offshore wind farm localization.Proposed framework defines input information together with methodological background required for decision support processes.

Many methods can be used for the evaluation of website quality.While they can be used for different purposes and require different assessment approaches it is not easy to select proper method adequate to the needs.Presented research is focused on building a repository of knowledge about the methods for the assessing the quality of website.The repository in the form of ontologies covers various methods of quality assessment and makes possible their proper selection.Proposed approach was verified with main methods and the resulting ontology can act as a repository of domain knowledge.