scholarly journals Novel Multi-Criteria Intuitionistic Fuzzy SWARA–COPRAS Approach for Sustainability Evaluation of the Bioenergy Production Process

2020 ◽  
Vol 12 (10) ◽  
pp. 4155 ◽  
Author(s):  
Arunodaya Raj Mishra ◽  
Pratibha Rani ◽  
Kiran Pandey ◽  
Abbas Mardani ◽  
Justas Streimikis ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Production Technology ◽  
Real Life ◽  
Integrated Approach ◽  
Integrated Framework ◽  
Bioenergy Production ◽  
Intuitionistic Fuzzy ◽  
Important Concern ◽  
Criteria Weights ◽  
Selection Of

Bioenergy is a kind of renewable energy that can potentially contribute to a broad spectrum of economic, environmental, and societal objectives and aid sustainable development. The assessment, management, and monitoring of the diverse bioenergy production technology alternatives are complex in nature and deliver different benefits due to the lack of precise and comprehensive data. Selection of an optimal bioenergy production technology (BPT) alternative is considered a complex multi-criteria decision-making (MCDM) problem that involves many incompatible tangible and intangible as well as qualitative and quantitative criteria. The procedure of defining and evaluating the weights of the criteria is an important concern for decision experts because the assessment and the final selection of the BPT alternative are carried out on the basis of the defined set of criteria. Intuitionistic fuzzy sets (IFSs) have received considerable attention due to their ability to handle the imprecision and vagueness that can arise in real-life situations. Thus, this study presents an integrated approach, based on stepwise weight assessment ratio analysis (SWARA) and complex proportional assessment (COPRAS) approaches, for the selection of BPT alternatives. In the integrated framework, criteria weights are determined by the SWARA procedure, and the ranking of BPT alternatives is decided by the COPRAS method using IFSs. The criteria weights evaluated by this approach involve the imprecision of experts’ opinions, which makes them more comprehensible. To express the efficiency and applicability of the integrated framework, a BPT selection problem is presented using IFSs. In addition, this study involved sensitivity analysis with respect to various sets of criteria weights to reveal the strength of the developed approach. The sensitivity analysis outcomes indicate that the agricultural and municipal waste of biogas (S3) consistently secures the highest rank, despite how the criteria weights vary. Finally, a comparative study is discussed to analyze the validity of the obtained result. The findings of this study confirm that the proposed framework is more useful than and consistent with previously developed methods using the IFSs environment.

scholarly journals Normalized Weighted Bonferroni Harmonic Mean-Based Intuitionistic Fuzzy Operators and Their Application to the Sustainable Selection of Search and Rescue Robots

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 218 ◽  
Author(s):  
Jinming Zhou ◽  
Tomas Baležentis ◽  
Dalia Streimikiene
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Real Life ◽  
Aggregation Operators ◽  
Harmonic Mean ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Selection Of

In this paper, Normalized Weighted Bonferroni Mean (NWBM) and Normalized Weighted Bonferroni Harmonic Mean (NWBHM) aggregation operators are proposed. Besides, we check the properties thereof, which include idempotency, monotonicity, commutativity, and boundedness. As the intuitionistic fuzzy numbers are used as a basis for the decision making to effectively handle the real-life uncertainty, we extend the NWBM and NWBHM operators into the intuitionistic fuzzy environment. By further modifying the NWBHM, we propose additional aggregation operators, namely the Intuitionistic Fuzzy Normalized Weighted Bonferroni Harmonic Mean (IFNWBHM) and the Intuitionistic Fuzzy Ordered Normalized Weighted Bonferroni Harmonic Mean (IFNONWBHM). The paper winds up with an empirical example of multi-attribute group decision making (MAGDM) based on triangular intuitionistic fuzzy numbers. To serve this end, we apply the IFNWBHM aggregation operator.

scholarly journals Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement—Intuitionistic Fuzzy Sets and Genetic Algorithm Approach

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1531
Author(s):  
Ranka Gojković ◽  
Goran Đurić ◽  
Danijela Tadić ◽  
Snežana Nestić ◽  
Aleksandar Aleksić
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Manufacturing Process ◽  
Small And Medium Enterprises ◽  
Real Life ◽  
Process Industry ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Process Reliability ◽  
Selection Of

The aim of this research is to propose a hybrid decision-making model for evaluation and selection of quality methods whose application leads to improved reliability of manufacturing in the process industry. Evaluation of failures and determination of their priorities are based on failure mode and effect analysis (FMEA), which is a widely used framework in practice combining with triangular intuitionistic fuzzy numbers (TIFNs). The all-existing uncertainties in the relative importance of the risk factors (RFs), their values, applicability of the quality methods, as well as implementation costs are described by pre-defined linguistic terms which are modeled by the TIFNs. The selection of quality methods is stated as the rubber knapsack problem which is decomposed into subproblems with a certain number of solution elements. The solution of this problem is found by using genetic algorithm (GA). The model is verified through the case study with the real-life data originating from a significant number of organizations from one region. It is shown that the proposed model is highly suitable as a decision-making tool for improving the manufacturing process reliability in small and medium enterprises (SMEs) of process industry.

scholarly journals Complex intuitionistic fuzzy soft SWARA - COPRAS approach: An application of ERP software selection

2022 ◽  
Vol 7 (4) ◽  
pp. 5895-5909
Author(s):  
Harish Garg ◽  
◽  
J. Vimala ◽  
S. Rajareega ◽  
D. Preethi ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Ratio Analysis ◽  
Software Selection ◽  
Intuitionistic Fuzzy ◽  
Criteria Weights ◽  
Ranking Of Alternatives ◽  
Erp Software ◽  
Ideal Technique ◽  
Copras Method

<abstract><p>In this manuscript, we propose an integrated framework based on COmplex PRoportional ASsessment and Step-wise Weight Assessment Ratio Analysis approach within the complex intuitionistic fuzzy soft (CIFS) context. This context is an ideal technique with complex fuzzy foundation that means to denote multi-dimensional data in a concise. In this framework, criteria weights are evaluated by the SWARA technique, and the ranking of alternatives is determined by the COPRAS method using CIFSs. Further, to illustrate the applicability of the presented technique, an empirical case study of ERP software selection problem is taken. A comparative study and sensitivity analysis is presented to verify the strength of the presented methodology.</p></abstract>

Sensitivity Analysis and Selection of Check Index of Signal Intersection Simulation Model Based on VISSIM

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Mengda Zhang ◽  
Chenjing Zhou ◽  
Tian-tian Zhang ◽  
Yan Han
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Optimal Process ◽  
Parameter Calibration ◽  
Index Set ◽  
The Core ◽  
Core Module ◽  
Simulation Parameter ◽  
Simulation Parameters ◽  
Selection Of

Selecting check index quantitatively is the core of the calibration of micro traffic simulation parameters at signal intersection. Five indexes in the node (intersection) module of VISSIM were selected as the check index set. Twelve simulation parameters in the core module were selected as the simulation parameters set. Optimal process of parameter calibration was proposed and model of the intersection of Huangcun west street and Xinghua street in Beijing was built in VISSIM to verify it. The sensitivity analysis between each check index and simulation parameter in their own set was conducted respectively. Sensitive parameter sets of different check indices were obtained and compared. The results show that different indexes have different size of set, and average vehicle delay's is maximum, so it's necessary to select index quantitatively. The results can provide references for scientific selection of the check indexes and improve the study efficiency of parameter calibration.

scholarly journals Sustainability in the Business Sector: A Fuzzy Multicriteria Decision-Making Model for Financial Leasing Company Selection of the Vietnamese SMEs

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110360
Author(s):  
Fengsheng Chien ◽  
Chia-Nan Wang ◽  
Ka Yin Chau ◽  
Van Thanh Nguyen ◽  
Viet Tinh Nguyen
Keyword(s):  
Decision Making ◽  
Interest Rates ◽  
Small And Medium Enterprises ◽  
Multicriteria Decision Making ◽  
Primary Concern ◽  
Multicriteria Decision ◽  
Financial Leasing ◽  
Criteria Weights ◽  
Leasing Company ◽  
Selection Of

The uses and management of capital is extremely important to the operation of any businesses. However, not all businesses have available capital, so the use of loans in many different forms is always an effective solution in managing corporate finance. Accompanying with businesses, many financial leasing companies have implemented products and programs to lend money to businesses with low interest rates. So, choosing the best financial leasing company is a primary concern of businesses. To increase competitiveness, financial leasing companies often offer preferential conditions to attract businesses. Choosing the best financial leasing service to leasing is important and necessary to those businesses. Thus, the selection of a financial leasing company by small and medium enterprises benefits from the application of Multicriteria Decision-Making (MCDM) methods which allows the decision maker to consider various qualitative and quantitative criteria. In this article, the author applied Fuzzy Analytical Network Process (FANP) to calculate the related criteria weights of the financial leasing company selection problem of businesses. Then, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank the potential decision-making units. This research establishes one complete and efficient model for financial leasing company selection using FANP and TOPSIS methods. The proposed model is then applied into a real-world case study to demonstrate its feasibility.

scholarly journals Robust neutrosophic programming approach for solving intuitionistic fuzzy multiobjective optimization problems

2021 ◽  
Author(s):  
Firoz Ahmad
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Practical Implication ◽  
Real Life ◽  
Future Research ◽  
Programming Approach ◽  
Solution Approach ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiobjective Optimization Problems

AbstractThis study presents the modeling of the multiobjective optimization problem in an intuitionistic fuzzy environment. The uncertain parameters are depicted as intuitionistic fuzzy numbers, and the crisp version is obtained using the ranking function method. Also, we have developed a novel interactive neutrosophic programming approach to solve multiobjective optimization problems. The proposed method involves neutral thoughts while making decisions. Furthermore, various sorts of membership functions are also depicted for the marginal evaluation of each objective simultaneously. The different numerical examples are presented to show the performances of the proposed solution approach. A case study of the cloud computing pricing problem is also addressed to reveal the real-life applications. The practical implication of the current study is also discussed efficiently. Finally, conclusions and future research scope are suggested based on the proposed work.

scholarly journals ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1456
Author(s):  
Stefka Fidanova ◽  
Krassimir Todorov Atanassov
Keyword(s):  
Decision Making ◽  
Knapsack Problem ◽  
Propositional Logic ◽  
Optimization Problems ◽  
Real Life ◽  
Combinatorial Optimization Problems ◽  
Intuitionistic Fuzzy ◽  
Life Problems ◽  
Multiple Constraint

Some of industrial and real life problems are difficult to be solved by traditional methods, because they need exponential number of calculations. As an example, we can mention decision-making problems. They can be defined as optimization problems. Ant Colony Optimization (ACO) is between the best methods, that solves combinatorial optimization problems. The method mimics behavior of the ants in the nature, when they look for a food. One of the algorithm parameters is called pheromone, and it is updated every iteration according quality of the achieved solutions. The intuitionistic fuzzy (propositional) logic was introduced as an extension of Zadeh’s fuzzy logic. In it, each proposition is estimated by two values: degree of validity and degree of non-validity. In this paper, we propose two variants of intuitionistic fuzzy pheromone updating. We apply our ideas on Multiple-Constraint Knapsack Problem (MKP) and compare achieved results with traditional ACO.

scholarly journals Hybridization of ring theory-based evolutionary algorithm and particle swarm optimization to solve class imbalance problem

2021 ◽  
Author(s):  
Sayan Surya Shaw ◽  
Shameem Ahmed ◽  
Samir Malakar ◽  
Laura Garcia-Hernandez ◽  
Ajith Abraham ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Real Life ◽  
Class Imbalance ◽  
Ring Theory ◽  
Class Imbalance Problem ◽  
Minority Class ◽  
Swarm Optimization ◽  
Imbalance Problem ◽  
Representative Samples ◽  
Selection Of

AbstractMany real-life datasets are imbalanced in nature, which implies that the number of samples present in one class (minority class) is exceptionally less compared to the number of samples found in the other class (majority class). Hence, if we directly fit these datasets to a standard classifier for training, then it often overlooks the minority class samples while estimating class separating hyperplane(s) and as a result of that it missclassifies the minority class samples. To solve this problem, over the years, many researchers have followed different approaches. However the selection of the true representative samples from the majority class is still considered as an open research problem. A better solution for this problem would be helpful in many applications like fraud detection, disease prediction and text classification. Also, the recent studies show that it needs not only analyzing disproportion between classes, but also other difficulties rooted in the nature of different data and thereby it needs more flexible, self-adaptable, computationally efficient and real-time method for selection of majority class samples without loosing much of important data from it. Keeping this fact in mind, we have proposed a hybrid model constituting Particle Swarm Optimization (PSO), a popular swarm intelligence-based meta-heuristic algorithm, and Ring Theory (RT)-based Evolutionary Algorithm (RTEA), a recently proposed physics-based meta-heuristic algorithm. We have named the algorithm as RT-based PSO or in short RTPSO. RTPSO can select the most representative samples from the majority class as it takes advantage of the efficient exploration and the exploitation phases of its parent algorithms for strengthening the search process. We have used AdaBoost classifier to observe the final classification results of our model. The effectiveness of our proposed method has been evaluated on 15 standard real-life datasets having low to extreme imbalance ratio. The performance of the RTPSO has been compared with PSO, RTEA and other standard undersampling methods. The obtained results demonstrate the superiority of RTPSO over state-of-the-art class imbalance problem-solvers considered here for comparison. The source code of this work is available in https://github.com/Sayansurya/RTPSO_Class_imbalance.

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