Integration of Analytic Hierarchy Process and Multi Attributive Border Approximation Area Comparison for the Hybrid Vehicle Selection Problem in Intuitionistic Fuzzy Environment
The Autonomous Vehicle (AV) industry is constantly growing, thus analysing its perspectives is essential. However, for this analysis a sophisticated approach is necessary which considers the ambiguity of decision-makers, and different objectives and criteria related to stakeholders. In this paper a new model is proposed based on Decomposed Fuzzy Sets and the Best-Worst Method to deal with possible non-reciprocity of pairwise comparisons and different preferences of stakeholders in the AV industry. The main advantage of the model is that it is capable of considering optimistic and pessimistic attitudes along with the different objectives and criteria of the involved groups. The results show that users require short travel time, while operators, manufacturers and legislators expect mainly the increase of revenues from the AV implementation. Among the most important criteria, our analysis indicates the need of regulatory and safety issues are the most essential obstacles of expanding the AV industry. The new model can also be applied for evaluating the perspectives of other emerging technologies and industrial sectors.
Pub. online:26 Feb 2025Type:Research ArticleOpen Access
Journal:Informatica
Volume 36, Issue 1 (2025), pp. 33–63
Abstract
Sustainable practices are essential for long-term societal development, minimizing environmental impacts while promoting the efficient use of resources. Multi-criteria decision-making (MCDM) approaches can play a vital role in assessing and prioritizing sustainability solutions by considering diverse economic, social, and environmental factors. This study proposes a multi-criteria group decision-making approach based on the Objective Pairwise Adjusted Ratio Analysis (OPARA) method in a fuzzy environment and presents its application for the assessment of sustainable agriculture solutions. In the proposed approach, the evaluation criteria weights are determined by combining subjective weights from experts and objective weights obtained from the MEREC (Method Based on the Removal Effects of Criteria) method. The Relative Preference Relation (RPR) approach is employed for ranking fuzzy numbers and final evaluation. Sensitivity analysis and comparison with other methods are conducted to assess the robustness and validity of the proposed approach. The results demonstrate the effectiveness of the proposed approach in evaluating solutions. Based on the final evaluation from the case study, the most important criteria are “Availability and quality of water”, “Focus on immediate economic returns”, and “Financial incentives and access to credit”, while the most suitable solutions for advancing sustainable agriculture are “Financial and credit support”, “Education and enhancement of farmers’ knowledge”, and “Enhancement of research and development”.
Pub. online:28 Feb 2023Type:Research ArticleOpen Access
Journal:Informatica
Volume 34, Issue 2 (2023), pp. 415–448
Abstract
Multiple Criteria Decision-Making (MCDM) is one of the most reliable and applicable decision-making tools to address real-life complex and multi-dimensional problems in accordance with the concepts of sustainable development and circular economy. Although there have been several literature reviews on several MCDM methods, there is a research gap in conducting a literature review on the Multi-Attributive Border Approximation area Comparison (MABAC) as a useful technique to deal with intelligent decision-making systems. This study attempts to present a comprehensive literature review of 117 articles on recent developments and applications of MABAC. Future outlook is provided considering challenges and current trends.
Journal:Informatica
Volume 32, Issue 4 (2021), pp. 661–686
Abstract
Consensus creation is a complex challenge in decision making for conflicting or quasi-conflicting evaluator groups. The problem is even more difficult to solve, if one or more respondents are non-expert and provide uncertain or hesitant responses in a survey. This paper presents a methodological approach, the Interval-valued Spherical Fuzzy Analytic Hierarchy Process, with the objective to handle both types of problems simultaneously; considering hesitant scoring and synthesizing different stakeholder group opinions by a mathematical procedure. Interval-valued spherical fuzzy sets are superior to the other extensions with a more flexible characterization of membership function. Interval-valued spherical fuzzy sets are employed for incorporating decision makers’ judgements about the membership functions of a fuzzy set into the model with an interval instead of a single point. In the paper, Interval-valued spherical fuzzy AHP method has been applied to public transportation problem. Public transport development is an appropriate case study to introduce the new model and analyse the results due to the involvement of three classically conflicting stakeholder groups: passengers, non-passenger citizens and the representatives of the local municipality. Data from a real-world survey conducted recently in the Turkish big city, Mersin, help in understanding the new concept. As comparison, all likenesses and differences of the outputs have been pointed out in the reflection with the picture fuzzy AHP computation of the same data. The results are demonstrated and analysed in detail and the step-by-step description of the procedure might foment other applications of the model.
Journal:Informatica
Volume 23, Issue 3 (2012), pp. 461–485
Abstract
Three main approaches presently dominate preferences derivation or evaluation process in decision analysis (selecting, ranking or sorting options, alternatives, actions or decisions): value type approach (a value function or an utility measure is derived for each alternative to represent its adequacy with decision goal); outranking methods (a pair comparison of alternatives are carried up under each attribute or criteria to derive a pre-order on the alternatives set); and decision rules approach (a set of decision rules are derived by a learning process from a decision table with possible missing data). All these approaches suppose to have a single decision objective to satisfy and all alternatives characterized by a common set of attributes or criteria. In this paper we adopt an approach that highlights bipolar nature of attributes with regards to objectives that we consider to be inherent to any decision analysis problem. We, therefore, introduce supporting and rejecting notions to describ attributes and objectives relationships leading to an evaluation model in terms of two measures or indices (selectability and rejectability) for each alternative in the framework of satisficing game theory. Supporting or rejecting degree of an attribute with regard to an objective is assessed using known techniques such as analytic hierarchy process (AHP). This model allows alternatives to be characterized by heteregeneous attributes and incomparability between alternatives in terms of Pareto-equilibria.