scholarly journals EVALUATING LOGISTICS VILLAGES IN TURKEY USING HYBRID IMPROVED FUZZY SWARA (IMF SWARA) AND FUZZY MABAC TECHNIQUES

2021 ◽  
Vol 27 (6) ◽  
pp. 1582-1612
Author(s):  
Sarfaraz Hashemkhani Zolfani ◽  
Ömer Faruk Görçün ◽  
Hande Küçükönder
Keyword(s):  
Decision Making ◽  
Evaluation System ◽  
Decision Makers ◽  
Optimal Decision ◽  
Ratio Analysis ◽  
Evaluation Tool ◽  
Proposed Model ◽  
Criteria Weights ◽  
And Performance ◽  
The Right

Positioning in the right location for organizing logistics activities is a determinative factor in the aspect of costs, effectivity, productivity, and performance of these operations carried out by logistics firms. The proper logistics village selection is a crucial, complicated, and time-consuming process for decision-makers who have to make the right and optimal decision on this issue. Decision-makers need a methodological frame with a practical algorithm that can be implemented quickly to solve these decision-making problems. Within this scope, the current paper aims to present an evaluation tool, which provides more reasonable and reliable results for decision-makers to solve the logistics village selection problem that is very complicated and has uncertain conditions based on fuzzy approaches. In this study, we propose the Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA), a modified and extended version of the traditional fuzzy Step-Wise Weight Assessment Ratio Analysis (F-SWARA) to identify the criteria weights. Also, we suggest applying the fuzzy Multi-Attributive Border Approximation area Comparison (F-MABAC) technique to determine the preference ratings of the alternatives. This combination has many valuable contributions. For example, it proposes to use a more reliable and consistent evaluation scale based on fuzzy sets. Hence, decision-makers can perform more reliable and reasonable pairwise comparisons by considering this evaluation scale. Besides, it presents a multi-attribute evaluation system based on the identified criteria weights. From this perspective, the proposed model is implemented to evaluate eight different logistics village alternatives with respect to nine selection criteria. According to the analysis results, while A8 is the most appropriate option, C1 Gross National Product (GNP) is the most significant criterion. A comprehensive sensitivity analysis was performed to test the robustness and validation of the proposed model, and the results of the analysis approve the validity and applicability of the proposed model. As a result, the suggested integrated MCDM framework can be applied as a valuable and practical decision-making tool to develop new strategies and improve the logistics operations by decision-makers.

Decision making based on intuitionistic fuzzy preference relations with additive approximate consistency

2020 ◽  
Vol 39 (3) ◽  
pp. 4041-4058
Author(s):  
Fang Liu ◽  
Xu Tan ◽  
Hui Yang ◽  
Hui Zhao
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Real Interval ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Proposed Model ◽  
Fuzzy Preference Relations ◽  
Novel Concept ◽  
Fuzzy Weights ◽  
Fuzzy Preference

Intuitionistic fuzzy preference relations (IFPRs) have the natural ability to reflect the positive, the negative and the non-determinative judgements of decision makers. A decision making model is proposed by considering the inherent property of IFPRs in this study, where the main novelty comes with the introduction of the concept of additive approximate consistency. First, the consistency definitions of IFPRs are reviewed and the underlying ideas are analyzed. Second, by considering the allocation of the non-determinacy degree of decision makers’ opinions, the novel concept of approximate consistency for IFPRs is proposed. Then the additive approximate consistency of IFPRs is defined and the properties are studied. Third, the priorities of alternatives are derived from IFPRs with additive approximate consistency by considering the effects of the permutations of alternatives and the allocation of the non-determinacy degree. The rankings of alternatives based on real, interval and intuitionistic fuzzy weights are investigated, respectively. Finally, some comparisons are reported by carrying out numerical examples to show the novelty and advantage of the proposed model. It is found that the proposed model can offer various decision schemes due to the allocation of the non-determinacy degree of IFPRs.

scholarly journals Optimizing a Reverse Supply Chain Network for Electronic Waste under Risk and Uncertain Factors

2021 ◽  
Vol 11 (4) ◽  
pp. 1946
Author(s):  
Linh Thi Truc Doan ◽  
Yousef Amer ◽  
Sang-Heon Lee ◽  
Phan Nguyen Ky Phuc ◽  
Tham Thi Tran
Keyword(s):  
Supply Chain ◽  
Electronic Waste ◽  
Decision Makers ◽  
Reverse Supply Chain ◽  
Satisfactory Solution ◽  
Level Of Satisfaction ◽  
Proposed Model ◽  
Objective Value ◽  
The Right ◽  
The Impact

Minimizing the impact of electronic waste (e-waste) on the environment through designing an effective reverse supply chain (RSC) is attracting the attention of both industry and academia. To obtain this goal, this study strives to develop an e-waste RSC model where the input parameters are fuzzy and risk factors are considered. The problem is then solved through crisp transformation and decision-makers are given the right to choose solutions based on their satisfaction. The result shows that the proposed model provides a practical and satisfactory solution to compromise between the level of satisfaction of constraints and the objective value. This solution includes strategic and operational decisions such as the optimal locations of facilities (i.e., disassembly, repairing, recycling facilities) and the flow quantities in the RSC.

CAN BAYESIAN METHODS MAKE DATA AND ANALYSES MORE RELEVANT TO DECISION MAKERS?

2001 ◽  
Vol 17 (1) ◽  
pp. 114-122 ◽  
Author(s):  
Steven H. Sheingold
Keyword(s):  
Decision Making ◽  
Bayesian Methods ◽  
Paradigm Shift ◽  
Relevant Information ◽  
Decision Makers ◽  
Evidence Based ◽  
Critical Importance ◽  
Bayesian Approaches ◽  
Bayesian Analyses ◽  
And Performance

Decision making in health care has become increasingly reliant on information technology, evidence-based processes, and performance measurement. It is therefore a time at which it is of critical importance to make data and analyses more relevant to decision makers. Those who support Bayesian approaches contend that their analyses provide more relevant information for decision making than do classical or “frequentist” methods, and that a paradigm shift to the former is long overdue. While formal Bayesian analyses may eventually play an important role in decision making, there are several obstacles to overcome if these methods are to gain acceptance in an environment dominated by frequentist approaches. Supporters of Bayesian statistics must find more accommodating approaches to making their case, especially in finding ways to make these methods more transparent and accessible. Moreover, they must better understand the decision-making environment they hope to influence. This paper discusses these issues and provides some suggestions for overcoming some of these barriers to greater acceptance.

Performance measurement and resource sharing among business sub-units in the presence of non-discretionary factors

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rita Shakouri ◽  
Maziar Salahi
Keyword(s):  
Resource Sharing ◽  
Content Type ◽  
Development Level ◽  
Proposed Model ◽  
Decision Making Unit ◽  
Efficiency Estimation ◽  
Overall Efficiency ◽  
And Performance ◽  
The Right ◽  
The Impact

Purpose This paper aims to apply a new approach for resource sharing and efficiency estimation of subunits in the presence of non-discretionary factors and partial impacts among inputs and outputs in the data envelopment analysis (DEA) framework. Design/methodology/approach First, inspired by the Imanirad et al.’s model (2013), the authors consider that each decision-making unit (DMU) may consist of several subunits, that each of which can be affected by non-discretionary inputs. After that, the Banker and Morey’s model (1996) is used for modeling non-discretionary factors. For measuring performance of several subunits, which can be considered as DMUs, the aggregate efficiency is suggested. At last, the overall efficiency is computed and compared with each other. Findings One of the important features of proposed model is that each output in this model applies discretionary input according to its need; therefore, the result of this study will make it easier for the managers to make better decisions. Also, it indicates that significant predictions of the development of the overall efficiency of DMUs can be based on observing the development level of subunits because of the influence of non-discretionary input. Therefore, the proposed model provides a more reasonable and encompassing measure of performance in participating non-discretionary and discretionary inputs to better efficiency. An application of the proposed model for gaining efficiency of 17 road patrols is provided. Research limitations/implications More non-discretionary and discretionary inputs can be taken into consideration for a better analysis. This study provides us with a framework for performance measures along with useful managerial insights. Focusing upon the right scope of operations may help out the management in improving their overall efficiency and performance. In the recent highway maintenance management systems, the environmental differences exist among patrols and other geotechnical services under the climate diverse. Further, in some cases, there might exist more than one non-discretionary factor that can have different effects on the subunits’ performance. Practical implications The purpose of this paper was to measure the performance of a set of the roadway maintenance crews and to analyze the impact of non-discretionary inputs on the efficiency of the roadway maintenance. The application of the proposed model, on the one hand, showed that each output in this model uses discretionary input according to its requirement, and on the other hand, the result showed that meaningful predictions of the development of the overall efficiency of DMUs can be based on observing the development level of subunits because of the impact of non-discretionary input. Originality/value Providing information on resource sharing by taking into account non-discretionary factors for each subunit can help managers to make better decisions to increase the efficiency.

scholarly journals MULTI CRITERIA DECISION MAKING – RANKING AND PROMOTING EMPLOYEES

2019 ◽  
Vol 31 (5) ◽  
pp. 1235-1241
Author(s):  
Marina Badarovska Mishevska
Keyword(s):  
Decision Making ◽  
Decision Problem ◽  
Decision Makers ◽  
Decision Making Process ◽  
Specific Situation ◽  
Mathematical Tool ◽  
Analytic Hierarchy ◽  
The Right ◽  
Term Performance ◽  
Hierarchy Process

The analytic hierarchy process (AHP) is a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology. The method was developed by Thomas L. Saaty in the 1970s and has been extensively studied and refined since then. It has particular application in group decision making and is used around the world in a wide variety of decision situation. Rather than prescribing a "correct" decision, the AHP helps decision makers choose one that best suits their goal and their understanding of the problem. The technique provides a comprehensive and rational framework for structuring a decision problem, for representing and quantifying its elements, for relating those elements to overall goals, and for evaluating alternative solutions. Decision making is the choice of one alternative, from two or more, to which the course of the activity is directed and the problem is solved. The decision-making process is a rational attempt by the manager to achieve the goals of the organizational unit. The decision-making process can be thought of as a "brain and nervous system" of an enterprise. Decisions are made when a person wants things to be different in the future. Given each specific situation, making the right decisions is probably one of the most difficult challenges for managers. Managers in day-to-day work deliver programmed and unprogrammed decisions that solve simple or complex problems. Simple decisions have an impact on the short-term performance of the enterprise, and complex decisions have an impact on the long-term future and success of the enterprise. Users of the AHP first decompose their decision problem into a hierarchy of more easily comprehended sub-problems, each of which can be analyzed independently. Once the hierarchy is built, the decision makers systematically evaluate its various elements by comparing them to each other two at a time, with respect to their impact on an element above them in the hierarchy. The AHP converts these evaluations to numerical values that can be processed and compared over the entire range of the problem. In this article, it is explained the application of the AHP method in order to evaluate and promote employees in the enterprise "X" with several criteria. The obtained results enable the manager to evaluate the employees in an objective way and make an objective decision for their promotion. Its application for selecting the best among employees, in their assessment and promotion, allows managers to use a specific and mathematical tool to support the decision. This tool not only supports and qualifies decisions, it also allows managers to justify their choice, as well as to simulate possible results.

scholarly journals A BI-OBJECTIVE SCORE-VARIANCE BASED LINEAR ASSIGNMENT METHOD FOR GROUP DECISION MAKING WITH HESITANT FUZZY LINGUISTIC TERM SETS

2018 ◽  
Vol 24 (3) ◽  
pp. 1125-1148 ◽  
Author(s):  
Seyed Hossein RAZAVI HAJIAGHA ◽  
Meisam SHAHBAZI ◽  
Hannan AMOOZAD MAHDIRAJI ◽  
Hossein PANAHIAN
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Assignment Method ◽  
Linguistic Term ◽  
Criteria Weights ◽  
Individual Evaluation ◽  
Fuzzy Linguistic ◽  
Linear Assignment

Decision makers usually prefer to express their preferences by linguistic variables. Classic fuzzy sets allowed expressing these preferences using a single linguistic value. Considering inevitable hesitancy of decision makers, hesitant fuzzy linguistic term sets allowed them to express individual evaluation using several linguistic values. Therefore, these sets improve the ability of humans to determine believes using their own language. Considering this feature, in this paper a method upon linear assignment method is proposed to solve group decision making problems using this kind of information, when criteria weights are known or unknown. The performance of the proposed method is illustrated in a numerical example and the results are compared with other methods to delineate the models efficiency. Following a logical and well-known mathematical logic along with simplicity of execution are the main advantages of the proposed method.

Constructing a Hierarchy and Simulation Model to Assess Digital Recorder Sensor System

2012 ◽  
Vol 263-266 ◽  
pp. 857-860
Author(s):  
Kuang Jung Tseng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Safety Evaluation ◽  
Decision Makers ◽  
Sensor System ◽  
Model Following ◽  
Proposed Model ◽  
Digital Recorder ◽  
Decision Making Model

This work presents group decision making model, following a university safety evaluation to demonstrate the effectiveness of the proposed model. Importantly, the proposed model can assist university decision makers to buy the feasibility of digital recorder sensor system, making it highly applicable for academic and commercial purposes.

A Multi-Criteria Intuitionistic Fuzzy Group Decision Making Method for Supplier Selection with VIKOR Method

2012 ◽  
pp. 967-983
Author(s):  
Razieh Roostaee ◽  
Mohammad Izadikhah ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy-Malkhalifeh
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Decision Makers ◽  
Uncertain Information ◽  
Vikor Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
The Right

Supplier selection, the process of finding the right suppliers who are able to provide the buyer with the right quality products and/or services at the right price, at the right time and in the right quantities, is one of the most critical activities for establishing an effective supply chain, and is typically a multi-criteria group decision problem. In many practical situations, there usually exists incomplete and uncertain information, and the decision makers cannot easily express their judgments on the candidates with exact and crisp values. Therefore, in this paper an extended VIKOR method for group decision making with intuitionistic fuzzy numbers is proposed to solve the supplier selection problem under incomplete and uncertain information environment. In other researches in this area, the weights of each decision makers and in many of them the weights of criteria are pre-determined, but these weights have been calculated in this paper by using the decision matrix of each decision maker. Also, normalized Hamming distance is proposed to calculate the distance between intuitionistic fuzzy numbers. Finally, a numerical example for supplier selection is given to clarify the main results developed in this paper.

An Application of the Integrated IBA-TOPSIS Model in Supplier Selection

2015 ◽  
Vol 7 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Ksenija Mandić ◽  
Boris Delibašić ◽  
Dragan Radojević
Keyword(s):  
Decision Making ◽  
Boolean Algebra ◽  
Supplier Selection ◽  
Selection Process ◽  
Real Life ◽  
Decision Makers ◽  
Proposed Model ◽  
Qualitative Variables ◽  
Hidden Knowledge ◽  
Multi Attribute Decision Making

The supplier selection process attracted a lot of attention in the business management literature. This process takes into consideration several quantitative and qualitative variables and is usually modeled as a multi-attribute decision making (MADM) problem. A recognized shortcoming in the literature of classical MADM methods is that they don't permit the identification of interdependencies among attributes. Therefore, the aim of this study is to propose a model for selecting suppliers of telecommunications equipment that includes the interaction between attributes. This interaction can model the hidden knowledge needed for efficient decision-making. To model interdependencies among attributes the authors use a recently proposed consistent fuzzy logic, i.e. interpolative Boolean algebra (IBA). For alternatives ranking they use the classical MADM method TOPSIS. The proposed model was evaluated on a real-life application. The conclusion is that decision makers were able to integrate their reasoning into the MADM model using interpolative Boolean algebra.

scholarly journals Establishing a Sustainable Sports Tourism Evaluation Framework with a Hybrid Multi-Criteria Decision-Making Model to Explore Potential Sports Tourism Attractions in Taiwan

2020 ◽  
Vol 12 (4) ◽  
pp. 1673 ◽  
Author(s):  
Jen-Jen Yang ◽  
Huai-Wei Lo ◽  
Chen-Shen Chao ◽  
Chih-Chien Shen ◽  
Chin-Cheng Yang
Keyword(s):  
Decision Making ◽  
Evaluation Framework ◽  
Government Support ◽  
Multi Criteria Decision Making ◽  
Practical Applications ◽  
Proposed Model ◽  
Sports Tourism ◽  
Criteria Weights ◽  
Tourism Attractions ◽  
Multiple Experts

In recent years, the awareness of sustainable tourism has risen around the world. Many tourism industries combine sports to attract more customers to facilitate the development of the economy and the promotion of local culture. However, it is an important task to establish a comprehensive tourism evaluation framework for sustainable sports tourism. This study proposes a Multi-Criteria Decision-Making (MCDM) model to discuss the above issues, using the Bayesian Best Worst Method (Bayesian BWM) to integrate multiple experts’ judgments to generate the group optimal criteria weights. Next, the modified Visekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) technique is combined with the concept of aspiration level to determine the performance of sports attractions and their priority ranks. In addition, this study adds a perspective of institutional sustainability to emphasize the importance of government support and local marketing. The effectiveness and robustness of the proposed model is demonstrated through potential sports tourism attractions in Taiwan. A sensitivity analysis and models comparison were also performed in this study. The results show that the proposed model is feasible for practical applications and that it effectively provides some management implications to support decision-makers in formulating improvement strategies.

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