Efficient decision-making in fruit production involves evaluating multiple criteria, such as yield, fruit quality, and resistance, to rank available alternatives. Multi-Criteria Decision-Making (MCDM) methods provide a structured and objective framework for such tasks. This paper presents a web-based application named FRUITrank, designed to implement the MARCOS MCDM method for ranking and selection of plum varieties. The application uses a predefined set of criteria, whose weights were determined externally by using other MCDM methods. By leveraging a simple and intuitive interface, the application aims to overcome barriers to the practical adoption of MCDM methods among researchers and fruit producers, such as mathematical complexity and lack of accessible tools. The application was tested using a set of 11 criteria relevant to plum production, demonstrating its capability to deliver reliable and transparent rankings. This paper builds upon prior research in MCDM applications for agriculture, offering a practical solution for producers and researchers to enhance decision-making processes. Future improvements to the developed tool may include automated criteria weight calculation and broader applicability across various agricultural contexts.

A novel method for solving the multiple-attribute decision-making problem is proposed using the complex Diophantine interval-valued Pythagorean normal set (CDIVPNS). This study aims to discuss aggregating operations and how they are interpreted. We discuss the concept of CDIVPN weighted averaging (CDIVPNWA), CDIVPN weighted geometric (CDIVPNWG), generalized CDIVPN weighted averaging (CGDIVPNWA) and generalized CGDIVPN weighted geometric (CGDIVPNWG). This study aimed to examine several aggregation operators using complex Diophantine interval-valued Pythagorean normal sets. We calculated the weighted average and geometric distance based on an aggregating model. We demonstrate that complex Diophantine interval-valued Pythagorean normal sets satisfy algebraic structures such as associative, distributive, idempotent, bounded, commutative and monotonic properties. In this study, we discuss the mathematical properties of the score and accuracy values. We provide an example of how enhanced score and accuracy values are used in the real world. Machine tool technology and computer science play essential roles in robots. To evaluate robotic systems, four factors must be considered such as tasks, precision, speed and completion of the work. Consequently, it is evident that the models are significantly influenced by the natural number \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\nabla$$\end{document}. To further demonstrate the effectiveness of the suggested approach, flowchart based multi-criteria decision-making is provided and applied to a numerical example. Additionally, a comparative study has been carried out to demonstrate the better results that the proposed approach provides when compared to current approaches.

We introduce the concept of Diophantine spherical vague set approach to multiple-attribute decision-making. The Spherical vague set is a novel expansion of the vague set and interval valued spherical fuzzy set. Three new concepts have been introduce such as Diophantine spherical vague weighted averaging operator, Diophantine spherical vague weighted geometric operator, generalized Diophantine spherical vague weighted averaging operator and generalized Diophantine spherical vague weighted geometric operator. We provide a numerical example to show how Euclidean distance and Hamming distance interact. Applications of the Diophantine spherical vague number include idempotency, boundedness, commutativity and monotonicity in algebraic operations. They can determine the optimal option and are more well-known and reasonable. Our goal was to identify the optimal choice by comparing expert opinions with the criteria. As a result, the model’s output was more accurate as well as in the range of the natural number . The weighted averaging distance and weighted geometric distance operators are distance measure that is based on aggregating model. By comparing the models under discussion with those suggested in the literature, we hoped to show their worth and reliability. It is possible to find a better solution more quickly, simply, and practically. Our objective was to compare the expert evaluations with the criteria and determine which option was the most suitable. Because they yield more precise solutions, these models are more accurate and more related to models with . To show the superiority and the validity of the proposed aggregation operations, we compared it with the existing method and concluded from the comparison and sensitivity analysis that our proposed technique is more effective and reliable. This investigation yielded some intriguing results.

The aim of this work was to rank and select the most favorable of six sweet cherry cultivars using the web-oriented FRUITrank application, which incorporates the MARCOS (the Measurement of Alternatives and Ranking according to Compromise Solution) multi-criteria decision-making algorithm. During the ranking, 10 criteria were taken into account, one of which relates to the harvest start time, three to the physical characteristics of the fruit (including the pedicel), four to the chemical properties of the fruit, and one to the organoleptic characteristics. Alternative A3 (Kordia cultivar) was ranked as the best, the Izabela cultivar (A4) as second place, while Summit (A5) was placed at the bottom of the ranking. Considering the fact that the complexity of algorithms of various MCDM (Multi-Criteria Decision Making) methods often limits their application, based on the results obtained, it can be concluded that the mentioned and similar digital solutions solve the mentioned problem, i.e., enable wider application of MCDM techniques both in fruit production and in agriculture in general.

: With the increasing complexity of hotel selection, traditional decision-making models often struggle to account for uncertainty and interrelated criteria. Multi-criteria decision-making (MCDM) techniques, particularly those based on fuzzy logic, provide a robust framework for handling such challenges. This paper presents a novel approach to MCDM within the framework of Circular Intuitionistic Fuzzy Sets (C-IFS) by combining three distinct methodologies: Weighted Aggregated Sum Product Assessment (WASPAS), an Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN), and the CRITIC method (Criteria Importance Through Inter-criteria Correlation). To address the dynamic nature of traveler preferences in hotel selection, the study employs a comprehensive set of criteria encompassing aspects such as location proximity, amenities, pricing, customer reviews, environmental impact, safety, booking flexibility, and cultural experiences. The CRITIC method is used to determine the importance of each criterion by assessing intercriteria correlations. AROMAN is employed for the systematic evaluation of alternatives, considering their additive relationships and providing a weighted assessment. WASPAS further analyzes the results obtained from AROMAN, incorporating both positive and negative aspects for a comprehensive evaluation. The integration of C-IFS enhances the model’s ability to manage uncertainty and imprecision in the decision-making process. Through a case study, we demonstrate the effectiveness of this integrated approach, offering decision-makers valuable insights for selecting the most suitable hotel option in alignment with the diverse preferences of contemporary travelers. This research contributes to the evolving field of decision science by showcasing the practical applicability of these methodologies within a C-IFS framework for complex decision scenarios.

ABSTRACT

Sensitivity analyses are frequently performed to determine the robustness of MCDM methods, of which there are more than 200 types. In the past, rankings were compared to each other rather than to an external ranking. Thus, the direction and meaning of sensitivity can become unclear and complex. In addition, sensitivity analysis is usually performed only based on weight coefficients, but the effect of the normalization type is neglected. In this study, the most appropriate data conversion technique was investigated through an innovative sensitivity procedure to select the e-Small Van, which is an environmentally friendly logistics and transportation vehicle. Seven different normalization types based on the PROBID method (and two additional alternative MCDM methods) were used as parameters, resulting in 105 different MCDM rankings. According to the findings, MCDM rankings, which have low sensitivity, were also the performing methods that produced the highest correlation with price. What is striking is that careless choice of normalization type can be so effective as to manipulate the results. Although the most appropriate technique may vary depending on the data type, the fixed gold standard we recommend offers a flexible solution for all applications. A suitable data converter will result in the choice of a reliable electric vehicle.

The project phase is where the life-cycle of a building starts. The best decisions are made during the design or pre-project step. In terms of both economic resources and time, changes to specific design decisions made at this step are inexpensive compared to subsequent steps of architectural planning, not to mention the course of the construction's operation itself. The choices made during the design phase determine to a large extent whether the architectural design decisions of a building are achieved, whether the building and site can be used appropriately, and whether the project is economically viable. With BIM, building spatial planning is possible. As a result, architects can evaluate the proposed structure, its impact on the ecology, and the ecology's impact on the structure more comprehensively and at an earlier stage. This research proposes an energy modeling approach for the BIM-based spatial planning phase of a construction. The proposed method will result in an energy model for specific sites and building resolutions when utilized to create a spatial modelling for a construction. The energy model can then be used for new architectural creations. In this study, 36 different alternative scenarios were designed in terms of the rate of construction height to construction spacing, orientation factor, and form factor. With the help of BIM and GBS softwares, the energy consumption values of the alternative scenarios in cooling and heating load conditions were compared, and the alternative scenario with the minimum energy consumption was tried to be determined with spatial planning parameters.Ključne riječi

The increase in traffic caused by new development affects the change in traffic conditions on the surrounding roads, and shopping centres are significant traffic generators. The development of local travel generation rates and their characteristics for individual land uses from the aspect of traffic demand is a reliable way to plan traffic in order to come up with preventive solutions to traffic problems, that is, prevention of possible negative consequences on traffic conditions in the street network occurring due to the construction of shopping centres. One of the main aims of this paper is to develop a model for objective assessment of the generated traffic demand for significant changes in land use, such as the construction of shopping centres in medium-sized towns. All these would be steps in the right direction for the promotion of reliable traffic planning and adoption of TIA for every new development before a decision regarding the change in land purpose has been made. This kind of process still has not been established systematically in either Bosnia and Herzegovina and the Republic of Serbia, or in surrounding countries. This paper focuses on the formulation of a model for determining the volume of traffic generated by shopping centres in medium-sized towns in two countries of the Southeast Europe region. The survey was conducted in eight different locations (cities) where there are shopping centres with common facilities. The analysis showed that the number of visitors and vehicles attracted by the shopping centre zone can be determined by a model based on a linear regression analysis. The analysis included exploring several different factors of trip generation in shopping centres, including the relationship between trip generation and combinations of several independent variables. The verification of the model was conducted in real conditions of the traffic flow generated by a shopping centre which was not the analysis subject when forming the forecasting model. In this way, the validity of the proposed model is credibly assessed. The developed model can be applied in the procedures of planning the construction of shopping centres in medium-sized cities in the Republic of Serbia and Bosnia and Herzegovina, and wider, in the region of Southeast Europe, in order to estimate the volume of generated traffic demand, that is, its impact on the conditions of traffic on the surrounding traffic network.