جستجوی مقالات مرتبط با کلیدواژه "ranking" در نشریات گروه "ریاضی"

One of the common concerns of investors is determining the suitable field for investment. Due to the attractiveness of online sales in various fields such as clothing, newcomers and even existing companies tend usually to sell online. In this research, the rank of the suitability of an investment for online sales in different fields of clothing in Shiraz City was determined using the data envelopment analysis method. In the beginning, we form an expert team. Also, we recognized ten fields of clothing as investment alternatives for online sales (DMUs). Then, we defined suitable inputs and outputs by reviewing the literature and obtaining the opinions of expert team members. Also, we determine an epsilon-based input-oriented BCC model as a suitable DEA model for DMU ranking. Then, we obtained the input and output values from the expert team members and considered the average values as the inputs and outputs of the DEA models. Formulating and solving epsilon-based input-oriented BCC models showed that three DMUs were inefficient, and the other seven DMUs were efficient. Therefore, the rank of these three DMUs was determined. Next, to determine the rank of the other seven DMUs, we formed and solved the Andersen-Peterson epsilon-based input-oriented BCC models. The results of solving the DEA models showed that the fields of "Designing, producing, and selling of wedding dresses", "Designing, producing, and selling suits and formal dresses", and "Designing, producing, or selling local clothing" have the first to third ranks, respectively.

Deprivation and elimination of deprivation from different regions of the country to achieve sustainable development is one of the important issues in Iran. Therefore, the country's budget structure needs to be reformed. The purpose of this research is to evaluate the special view of the Islamic Consultative Assembly towards deprived areas in the amendment of the plan for eliminating deprivation, Note 14 of the budget law of the year 1401, using Data Envelopment Analysis (DEA) method. Since the decision-making units are the provinces of Iran, we have used the output-oriented CCR model to determine the efficiency of design modification, and then we have ranked it with the MAJ model. We have also determined important indicators in the allocation of credit to eliminate deprivation in provinces by using the AHP approach. Therefore, it is suggested that the note of this table should be deleted based on the text presented in a double-urgency plan agreed upon by main factions of the Parliament, and its credit should be distributed according to valid deprivation indicators. As well as this, we suggest that the requirements of each region should be met based on the latest statistics and relevant information.

Finding units with the most productive scale size (MPSS) is very important. The use of MPSS in ranking is thus the main idea in this paper. We propose an algorithm in DEA that ranks all extreme and non-extreme efficient DMUs in a number of steps. In this method, units with the most productive scale size are identified in each step and are then ranked. We finally show the application of the method using a numerical example.

With the growing trend in globalization and market competitiveness, process and resource optimization and the production of highly efficient products have become among the concerns of corporate managers. This research aims to evaluate and rank different polyethylene product grades produced at the Jam Petrochemical Complex using the Fuzzy Data Envelopment Analysis (FDEA) based upon fuzzy arithmetic [1]. The input-oriented fuzzy BCC model was suitable and applied to obtain the fuzzy efficiencies of different grades of polyethylene produced at the Jam Petrochemical Complex (13 DMUs) based on identified input and output indicators (Two inputs and three outputs). Then, a preference-degree approach is applied to compare and rank fuzzy DMU efficiencies. Based on the results, products HD52518, HD52505UV, and HM9450F were ranked first to third, respectively. The results highlight significant disparities in efficiency among the grades, providing a basis for targeted improvements.

It is important to have an intuitionistic fuzzy set that allows each set element to have a membership value, a non-membership value, and a hesitancy value. This is because each element of the set can possess all three values. We will focus on one type of continuous intuitionistic fuzzy number, called trapezoidal intuitionistic fuzzy numbers, because they are more flexible in representing information about membership and non-membership functions and are continuous. This research aims to introduce a parametric ranking and distance measure to compare and obtain the distinction value between intuitionistic trapezoidal fuzzy numbers. Parametric measures offer more flexibility than deterministic measurement tools in modeling real-world problems by considering a suitable variety of responses based on different levels of parameters. After presenting the structure and effective indicators of the proposed tool, we have detailed its features and basic principles. Moreover, based on this measure, a hybrid process is designed for multi-criteria group decision-making (MCGDM) problems with trapezoidal intuitionistic fuzzy data. A numerical example is also examined to elucidate the implementation process of this integrated methodology. Additionally, comparative analysis with some related methods confirms the adequate performance of the new parametric measure in combined methods with similar subjects.

Construction projects are frequently associated with a high incidence of cost overruns. To address this issue, the present study adopts a descriptive and survey-based approach to identify and rank the factors that contribute to construction costs. The study's statistical population comprises ten expert specialists, and the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) with Analytical Network Process (ANP) (DANP) technique is utilized to evaluate the research factors. Additionally, the fuzzy DANP and Delphi methods are employed to rank the essential dimensions and criteria of the research. The study's findings reveal that environmental factors are the primary cause of construction cost overruns, followed by managerial factors and legal and administrative factors, respectively. Dynamic conditions often result in unpredictable challenges for environmental factors, making them a critical driver of construction cost overruns. Therefore, environmental factors play a significant role in contributing to construction cost overruns.

Tourism is a worthy catalyst for development in emerging economies and supports growth in most developing countries. Consequently, countries continuously strive to enhance tourism competitiveness to magnetize worldwide tourists. However, due to significant environmental changes and intense competition, tourism organizations are compelled to adopt new strategies. A literature review demonstrates a broad spectrum of possible and available strategies for countries to choose from, necessitating the prioritization of strategies appropriate to the host country's situation and conditions. In this study, we implemented the Antifragility Analysis Algorithm (AAA) to address the research problem (identifying and prioritizing tourism strategies in the western region of Mazandaran province, Iran). We also collected experts' verbal judgments using Neutrosophic Sets (NSs), which can effectively address ambiguity and uncertainty. Initially, with the help of experts in the field, we identified eleven available strategies. Then, we identified five influential environmental indicators and possible states for each, defining thirteen alternative scenarios (one current scenario and twelve future scenarios). Subsequently, the performance of strategies in each indicator state was estimated using NSs. Then, considering the future scenarios, the antifragility scores of the strategies were determined. The results indicate all listed strategies are antifragile, meaning that adopting and implementing each could yield more significant benefits than the current situation. According to the findings, market research, infrastructure development, community engagement, diversification, and monitoring strategies should be implemented in the initial stage. Following them, destination branding, halal tourism, and crisis management strategies should be implemented in the next stage, and the remaining strategies can be executed in the final stage.

Supply Chain Management (SCM) is an integrated system of planning and control of materials and information, including suppliers, manufacturers, distributors, retailers, and customers. Chain performance measurement is an important issue in SCM. Also, given that the information plays a key role in improving supply chain performance, the kind and amount of information sharing should be investigated. In this paper, the effect of information sharing on supply chain performance will be evaluated. In this way, 17 different scenarios of information sharing are defined and ranked using the cross-efficiency method. Finally, values ​​for different scenarios using simulations and Rockwell Software Arena V5 are reported. The obtained results show that the proposed model is quite valid and efficient and can be easily applied to real-world cases.

Ranking fuzzy numbers have become of growing importance in recent years, especially as decision-making is increasingly performed under greater uncertainty. In this paper, we extend the concept of magnitude to rank fuzzy numbers to a more general definition to increase in flexibility and generality. More precisely, we propose a multidimensional approach to rank fuzzy numbers considering alternative magnitude definitions with three novel features: multidimensionality, normalization, and a ranking based on a parametric distance function. A multidimensional magnitude definition allows us to consider multiple attributes to represent and rank fuzzy numbers. Normalization prevents meaningless comparison among attributes due to scaling problems, and the use of the parametric Minkowski distance function becomes a more general and flexible ranking approach. The main contribution of our multidimensional approach is the representation of a fuzzy number as a point in a $n$-dimensional normalized space of attributes in which the distance to the origin is the magnitude value. We illustrate our methodology and provide further insights into different normalization approaches and parameters through several numerical examples. Finally, we describe an application of our ranking approach to a multicriteria decision-making problem within an economic context in which the main goal is to rank a set of credit applicants considering different financial ratios used as evaluation criteria.

Ranking fuzzy numbers(FNs) was a critical issue in fuzzy computing field. Generally, triangular FNs, trapezoidal FNs, and even interval-valued FNs(IVFNs) were often expressed in ranking. However, ranking intuitionistic FNs(IFNs) were less mentioned due to the complicated components in membership functions. Herein, we will develop fuzzy binary relation that is an extended fuzzy preference relation(EFPR) to express the preference degree of two IFNs, and then the relation is improved to be a relative preference relation(RPR) used to rank a set of IFNs. Since EFPR on IFNs is a total ordering relation, RPR will be also a total ordering relation. Based on belonging and non-belonging components of membership functions in IFNs, using EFPR being also fuzzy preference relation(FPR) is suitable to compare FNs on pairwise, but time complexity on fuzzy operation of comparison computing is complicated. Hence, RPR is developed to avoid comparing on pairwise. Through yielding RPR values for a set of IFNs, IFNs are effectively and efficiently ranked to utilize related decision-making problems.

In this paper, we use the Plackett-Luce model for detecting some referees judge arbitrariness with inaccuracy or without paying enough attention which is called semi-referees. We will investigate our method by simulation and sample of real data.

When we use the CCR model in the input-oriented with fuzzy data for ranking with the help of cross-efficiency, there is a possibility that the model will find a different optimal answer. This means that the ranking is not unique, that is, a decision-making unit may be assigned several ranks. Here, the judgment regarding the ranking faces a problem. To solve this problem, a secondary objective is determined for weight selection. According to that secondary objective, a suitable weight is selected from among the optimal solutions. In this article, the secondary goal of the concept of symmetrizing the weights plays a fundamental role in solving the mentioned problem. The model selects weights that are symmetrical, the act of choosing symmetrical weights causes many weights that are not useful to be removed from the set. The decision-making unit that selects symmetrical weights for all indicators, has a better performance than the decision-making unit that does not use symmetrical weights and covers its weak points with low weight and highlights its strong points with high weight. The model along with the mentioned secondary objective is used to evaluate decision-making units with fuzzy input and output, by choosing the optimal weight, a cross-efficiency table is formed. By using the cross-efficiency table, the efficiency of each unit is determined and ranked compared to other units. Units are done.

To face uncertainty in the real world, the two value logic has gradually replaced the fuzzy logic. In some real world problems, accurate determination of membership value is difficult and decision- making is associated with uncertainty and hesitation. This new perspective manages the uncertainty caused by hesitation. Generalized trapezoidal hesitant fuzzy numbers (GTHFN), whose membership degree is expressed by several trapezoidal fuzzy number, is best suited to solve the decision-making problem in real life than real numbers. In this paper, we refer to a new concept called 'generalized trapezoidal hesitant fuzzy numbers' and its combination with data envelopment analysis. Using this information, we consider the deviation and the score values as input and output of the data envelopment analysis model in two stages respectively; then we used the result to construct a paired comparison matrix and eventually we prioritize the receivers decision making units. To use some concepts in the proposed decision making method, we first present some definitions of concepts such as the score and deviation functions from the generalized trapezoidal hesitant fuzzy numbers. Finally, a numerical example is presented for the proposed method to confirm its applicability, and the ranking result is compared with the methods of AP, TOPSIS with GTHF number and the weighted geometric operator in [7].

Data Envelopment Analysis (DEA) is a broad range of mathematical models for measuring the relative efficiency of a set of homogeneous decision units with similar inputs and outputs. Multiple models of data envelopment analysis render a set of weights for input and output variables of each decision unit to calculate the relative efficiency of those units based on them. The calculation of different weights for the same indices in a set of homogeneous decision units is not realistic. Therefore, the Common Set of Weights (CSW) method was used to solve this problem and the Bootstrap method was used to determine which common set of weights would minimize the number of efficient units. The rank of a unit can provide useful information to decision-makers on the optimal activities of decision units. The priority order of units defines the superiority of a unit in terms of efficiency and effectiveness over others. Calculating unit efficiency for data envelopment analysis models can be a good criterion for ranking one unit. However, the main problem arises when several efficient units all rank first. This study aimed at proposing a model for ranking efficient units using the Bootstrap method to determine the common set of weights in data envelopment analysis by finding a possible confidence interval for the weights using the Bootstrap method. This led to the estimation of a set of possible common weights for the data envelopment analysis. Efficient units were then identified and ranked based on these weights..

Classic Data Envelopment Analysis assumes that the values of inputs and outputs are exactly determined. However, in most real-life problems, the exact values of some of the inputs and outputs are imprecise. One of such imprecise data is ordinal data. In this paper, a new model is presented for measuring the efficiency evaluation of decision making units with ordinal data. The general idea of this model is assigning real values to ordinal data with new approach. Furthermore, another new model for ranking efficient units is presented with the main idea of changes in controlled efficiency. Then, the results of proposed model are compared with Cooper model. Therefore, the efficiency scores obtained from proposed model are more realistic and reasonable than the results obtained from the Cooper's model.

The weights generated by the common weights approach provide a common criterion for ranking the decision-making units (DMUs) in data envelopment analysis (DEA). Existing common weights models in DEA are either very complicated or unable to produce a full ranking for DMUs. This paper proposes a new compromise solution model to seek a common set of weights for full ranking for DMUs. The maximum inefficiency scores calculated from the standard DEA model are regarded as the anti-ideal solution for the DMUs to avoid. A common set of weights that produces the vector of inefficiency scores for the DMUs furthest to the anti-ideal solution is sought. The discrimination power of the new model is tested using two numerical examples and its potential application for fully ranking DMUs is illustrated.

Ranking of fire stations is one of the most important issues in urban planning and crisis management. Because ranking increases the speed of service in crises. In the real world, the value of some attributes is non-controllable, so planners and decision makers can't change the values in the ranking process and it must be considered in the ranking. The aim of this study is ranking of fire stations candidates in district ten of Tehran municipality and for this, has used non-radial DEA model. The decision matrix consists of eleven alternatives and twelve attributes. The attributes are controllable (that the decision makers able to change values) and non-controllable (that the decision makers unable to change the values). The results show that station 5 is prioritized among the stations and has higher non-controllable attribute values in decision matrix than the others, and it validates the results.