RFOS - Repository of Faculty of Organizational Sciences Univ. of Belgrade
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Floating photovoltaic site selection using fuzzy rough numbers based LAAW and RAFSI model
No full textThis study presents a quantitative methodology for Floating Photovoltaic (FPV) power plant site selection in Turkey using Geographical Information Systems (GIS) and fuzzy sets, which is one of the Multi-Criteria Decision Making (MCDM) methods. In this study, we propose a new hybrid framework which combines fuzzy rough number (FRN) based decision making model including LAAW (Logarithmic Additive Assessment of the Weight coefficients) and RAFSI (Ranking of Alternatives through Functional mapping of criterion subintervals into a Single Interval). The fuzzy rough number is applied for handling the uncertainty and inaccuracy of experts' opinions in the evaluation process. Firstly, FRN based LAAW method is used to determine the weighting co-efficients of the criteria. Secondly, FRN based RAFSI method is used to rank the alternatives. The proposed decision making model is applied to determine feasible site for Floating Photovoltaic (FPV) system in Southern part of Turkey. Out of the five alternative sites, Manavgat -Antalya is concluded to be the most suitable site, and the second-best alternative is Goksun-Karaman. The results show the rationality and applicability of the pro-posed model
Modification of the DIBR and MABAC Methods by Applying Rough Numbers and Its Application in Making Decisions
No full textThis study considers the problem of selecting an anti-tank missile system (ATMS). The mentioned problem is solved by applying a hybrid multi-criteria decision-making model (MCDM) based on two methods: the DIBR (Defining Interrelationships Between Ranked criteria) and the MABAC (Multi-Attributive Border Approximation area Comparison) methods. The methods are modified by applying rough numbers, which present a very suitable area for considering uncertainty following decision-making processes. The DIBR method is a young method with a simple mathematical apparatus which is based on defining the relation between ranked criteria, that is, adjacent criteria, reducing the number of comparisons. This method defines weight coefficients of criteria, based on the opinion of experts. The MABAC method is used to select the best alternative from the set of the offered ones, based on the distance of the criteria function of every observed alternative from the border approximate area. The paper has two main innovations. With the presented decision-making support model, the ATMS selection problem is raised to a higher level, which is based on a proven mathematical apparatus. In terms of methodology, the main innovation is successful application of the rough DIBR method, which has not been treated in this way in the literature so far. Additionally, an analysis of the literature related to the research problem as well as to the methods used is carried out. After the application of the model, the sensitivity analysis of the output results of the presented model to the change of the weight coefficients of criteria is performed, as well as the comparison of the results of the presented model with other methods. Finally, the proposed model is concluded to be stable and multi-criteria decision-making methods can be a reliable tool to help decision makers in the selection process. The presented model has the potential of being applied in other case studies as it has proven to be a good means for considering uncertainty
A fuzzy Einstein-based decision support system for public transportation management at times of pandemic
No full textOptimal decision-making has become increasingly more difficult due to their inherent complexity exacerbated by uncertain and rapidly changing environmental conditions in which they are defined. Hence, with the aim of improving the uncertainty management and facilitating the weighting criteria, this paper introduces an improved fuzzy Einstein Combined Compromise Solution (CoCoSo) method-ology. Such a CoCoSo model improves previous CoCoSo proposals by using nonlinear fuzzy weighted Einstein functions for defining weighted sequences. In addition, it proposes a novel algorithm for determining the criteria weights based on the fuzzy logarithmic function, therefore it allows decision -makers a better perception of the relationship between the criteria, as it considers the relationships between adjacent criteria; high consistency of expert comparisons; and enables the definition of weighting coefficients of a larger set of criteria, without the need to cluster (group) the criteria. Nonlinear fuzzy Einstein functions implemented in the fuzzy Einstein CoCoSo methodology enable the processing of complex and uncertain information. Such characteristics contribute to the rational definition of compromise strategies and enable objective reasoning when solving real-world decision problems. The efficiency, effectiveness, and robustness of the proposed fuzzy Einstein CoCoSo model are illustrated by a case study to create a conceptual framework to evaluate and rank the prioritization of public transportation management at the time of the COVID-19 pandemic. The results reveal its good performance in determining the transportation management systems strategy
Analytic description to the fuzzy efficiencies in fuzzy standard Data Envelopment Analysis
No full textIn this paper we show how a parametric discussion on the optimal objective values to two mathematical models involved in a fuzzy standard data envelopment analysis can provide an analytic description to the membership functions of the fuzzy efficiencies of the decision-making units. We recall the mathematical models under discussion from the literature, but we approach them from a novel perspective, thus providing an analytical alternative to the numerical methods used so far in the literature
Prioritized Aggregation Operators for Intuitionistic Fuzzy Information Based on Aczel-Alsina T-Norm and T-Conorm and Their Applications in Group Decision-Making
No full textIn multi-attribute group decision-making (MAGDM) problems, prioritization is sometimes important. Several techniques and methods have been introduced in fuzzy systems to use prioritization. The main purpose of this paper is to propose prioritized aggregation operators (AOs) for intuitionistic fuzzy (IF) information. These AOs are symmetric in nature and are based on the novel Aczel-Alsina t-norm and t-conorm. Herein, we propose IF-prioritized Aczel-Alsina averaging (IFPAAA) and IF-prioritized Aczel-Alsina geometric (IFPAAG) operators. It is shown that these AOs satisfy the basic features of aggregation. Some additional results for these AOs are also investigated. These proposed operators can capture the prioritization phenomenon among the aggregated arguments, and the weights for prioritization are obtained from expert information. Finally, the proposed AOs are used in an MAGDM problem where a doctor is selected for a hospital. A comparison of the proposed prioritized AOs is also established with other well-known AOs to show the significance of the IFPAAA and IFPAAG operators
Advancing Data Exchange Standards for Interoperable Enterprise Networks
No full textRecently, our interoperability research strategy delivered significant results by (1) adopting the ISO-approved Core Components Technical Specification (CCTS) meta-model as a basis for a new data exchange modeling framework and (2) developing Score, which is an innovative open-source, CCTS-based, data exchange standards modeling and life-cycle management tool. This strategy has been arguably very promising, as evidenced both by industry uptake of our research results. Moreover, there are additional possible capabilities that can contribute to even greater interoperability of enterprise systems. However, for the CCTS- or a similar meta-model-based modeling framework, and a newly enabled tool to have a full impact, new challenges need to be addressed. The paper discusses these challenges for the data exchange standards-based systems integrations, identifying the current state-of-the-art solutions and limitations. The paper also proposes future research directions and strategies to enable advanced capabilities by building on both the already successful and accepted technologies as well as new and emerging ones
Selection of unployed aircraft for training of small-range aircraft defense system AHP - topsis optimization methods
No full textThe article solves the problem of more efficient and economical training of combat crews on short range air defense systems. The training so far is based on the use of conventional means, which require engagement of a large number of people, expensive equipment, long-term planning and spending a lot of time and space. The use of unmanned aerial vehicles - drones, greatly saves all these resources. Our mathematical model, using the methods of multicriteria decision-making - Analytical Hierarchical Processes (AHP) and optimization - The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), determines the weighting coefficients and then ranks alternatives or, the ranking for drone selection, which would replace classical means for training and coaching so meeting all parameters and characteristics of the training itself and the training equipment. The methods first prioritize the selection criteria, and then, based on their importance, concretize the solution among the offered alternatives
Can ICT-based process innovation improve logistics services? The case of a Serbian logistics provider
No full textIn this empirical study, the impact of advanced information communication technology (ICT) as a tool to enable process innovation is presented. The aim of the research is to measure the impact of ICT-based process innovation on improving goods transport services through enhancing process efficiency and effectiveness in the sales operations. The research was conducted by collecting primary and secondary data from a Serbian transport company. The results of the research show that the ICT-based innovation action in process improvement and change has a great impact on competitive advantage of the company, both on domestic and international market. However, there are also indications that there is a need for further continuous advancements
On-line Education as a Development Opportunity for Higher Education Institutions
No full textThe COVID-19 pandemic has enforced significant changes in all types of organizations. This paper will examine digitalization in higher education and the effects it has caused. Educational institutions have been pushed to transform their traditional teaching models into hybrid digital systems, where students spend most of their time in online environment. With a goal to examine impressions of key stakeholders (students and teaching staff), research was conducted at the Faculty of Organizational Sciences, University of Belgrade, in order to review results of online teaching methods. Focus was on comparing success that students and teachers had before and during the COVID-19 pandemic. Further on, this paper considers contribution and development opportunities that online education can provide. Those benefits include but are not limited to: enrolling more students, significantly enhancing financial resources, possibility of opening international study programs which would contribute to international cooperation, greater reputation and prestige of these educational institutions
Mapping the startup ecosystem of emerging countries: Methodological challenges and policy implications for Serbia
No full textThe mapping of the Startup Ecosystem has long been a challenge, both for researchers and
policymakers. From a policymaker’s point of view, determining the current state of development,
issues and challenges, all of which influence the directions of governmental actions. On the other
hand, researchers have persisted with the emphasis given on the methodological aspects of choice of indicators depicting the startup ecosystem, weighting scheme underlying the composite indexes of startup ecosystem evaluation, etc. At the confluence of two sides of the same coin, lies the Global Startup Ecosystem Report, and its flagship Rankings 2021 for Top 100 Emerging Ecosystems. The list itself encompasses the hotspots of the early-stage startup ecosystems across the Globe and is founded upon four domains: Performance, Funding, Market Reach and Talent & Experience. The paper will tackle both the methodological aspects of composite index developments by utilizing the potential of multivariate statistical methods while laying the foundation for policy implications which can benefit emerging countries such as Serbia. Finally, future directions of potential improvement of the Global Startup Ecosystem methodology will be elaborated