scholarly journals An Integrated Single-Valued Neutrosophic Combined Compromise Solution Methodology for Renewable Energy Resource Selection Problem

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4594
Author(s):  
Pratibha Rani ◽  
Jabir Ali ◽  
Raghunathan Krishankumar ◽  
Arunodaya Raj Mishra ◽  
Fausto Cavallaro ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Selection Process ◽  
Energy Resource ◽  
Strategic Decision ◽  
Selection Problem ◽  
Illustrative Case ◽  
Compromise Solution ◽  
Neutrosophic Sets ◽  
Technical Requirements ◽  
Criteria Weights

Optimal renewable energy source (RES) selection needs a strategic decision for reducing environmental pollutions, use of conventional resources, and improving economic development. In the process of RESs evaluation, several aspects like environmental, economic, social, and technical requirements play an important role. In addition, diverse factors affect the appropriate RES selection problem which adheres to uncertain and imprecise data. Thus, this selection process can be considered as a complex uncertain multi-criteria decision making (MCDM) problem. This study aims to introduce a novel integrated methodology based on Step-wise Weight Assessment Ratio Analysis (SWARA) and Combined Compromise Solution (CoCoSo) methods within single-valued neutrosophic sets (SVNSs) context, wherein the decision-makers and criteria weights are completely unknown. In the proposed approach, the criteria weights are determined by the SWARA method, and the most suitable RES alternative is determined by an improved CoCoSo method under the SVN context. Further, an illustrative case study of RES selection is considered to demonstrate the thorough execution process of the proposed method. Moreover, a comparison with existing methods is discussed to analyze the validity of the obtained result. This study performs sensitivity analysis with a various set of criteria weights to reveal the robustness of the developed approach. The strength of the proposed method is its practical applicability and ability to provide solutions under uncertain, imperfect, indeterminate, and inconsistent information.

scholarly journals A Hesitant Fuzzy Combined Compromise Solution Framework-Based on Discrimination Measure for Ranking Sustainable Third-Party Reverse Logistic Providers

2021 ◽  
Vol 13 (4) ◽  
pp. 2064
Author(s):  
Arunodaya Raj Mishra ◽  
Pratibha Rani ◽  
Raghunathan Krishankumar ◽  
Edmundas Kazimieras Zavadskas ◽  
Fausto Cavallaro ◽  
...  
Keyword(s):  
Reverse Logistics ◽  
Hybrid Approach ◽  
Third Party ◽  
Illustrative Case ◽  
Primary Concern ◽  
Compromise Solution ◽  
Fuzzy Environment ◽  
Criteria Weights ◽  
Reverse Logistic ◽  
Illustrative Case Study

Customers’ pressure, social responsibility, and government regulations have motivated the enterprises to consider the reverse logistics (RL) in their operations. Recently, companies frequently outsource their RL practices to third-party reverse logistics providers (3PRLPs) to concentrate on their primary concern and diminish costs. However, to select the suitable 3PRLP candidate requires a multi-criteria decision making (MCDM) process involving uncertainty owing to the presence of many associated aspects. In order to choose the most appropriate sustainable 3PRLP (S3PRLP), we introduce a hybrid approach based on the classical Combined Compromise Solution (CoCoSo) method and propose a discrimination measure within the context of hesitant fuzzy sets (HFSs). This approach offers a new process based on the discrimination measure for evaluating the criteria weights. The efficiency and practicability of the present approach are numerically demonstrated by solving an illustrative case study of S3PRLPs selection under a hesitant fuzzy environment. Moreover, sensitivity and comparative studies are presented to highlight the robustness and strength of the introduced methodology. The result of this work concludes that the introduced methodology can recommend a more feasible performance when facing with determinate and inconsistent knowledge and qualitative data.

scholarly journals SOLVING CONSTRUCTION PROJECT SELECTION PROBLEM BY A NEW UNCERTAIN WEIGHTING AND RANKING BASED ON COMPROMISE SOLUTION WITH LINEAR ASSIGNMENT APPROACH

2019 ◽  
Vol 25 (3) ◽  
pp. 241-251 ◽  
Author(s):  
Reza Davoudabadi ◽  
Seyed Meysam Mousavi ◽  
Jonas Šaparauskas ◽  
Hossein Gitinavard
Keyword(s):  
Fuzzy Sets ◽  
Alternative Assessment ◽  
Construction Project ◽  
Project Selection ◽  
Selection Problem ◽  
Uncertain Information ◽  
Compromise Solution ◽  
Additional Information ◽  
Criteria Weights ◽  
Linear Assignment

Selecting a suitable construction project is a significant issue for contractors to decrease their costs. In real cases, the imprecise and uncertain information lead to decisions made based on vagueness. Fuzzy sets theory could help decision makers (DMs) to address incomplete information. However, this article develops a new integrated multi-criteria group decision-making model based on compromise solution and linear assignment approaches with interval-valued intuitionistic fuzzy sets (IVIFSs). IVIFSs by presenting a membership and non-membership degree for each candidate based on appraisement criteria could decrease the vagueness of selection decisions. The proposed algorithm involves a new decision process under uncertain conditions to determine the importance of criteria and DMs, separately. In this regard, no subjective or additional information is needed for this process; only the input information required is an alternative assessment matric. In this approach, weights of criteria and DMs are specified based on novel indexes to increase the reliability of obtained results. In this respect, the criteria’ weights are computed regarding entropy concepts. The basis for calculating the weight of each DM is the distance between each DM and an average of the DMs’ community. Furthermore, the linear assignment model is extended to rank the candidates. A case study about the construction project selection problem (CPSP) is illustrated to indicate the application of proposed model.

scholarly journals The material selection of the heating plates used in the vulcanization process obtained using different MCDM methods

2021 ◽  
Vol 46 (1) ◽  
pp. 19-25
Author(s):  
Jelena Mihajlović ◽  
Goran Petrović ◽  
Dušan Ćirić ◽  
Miloš Madić
Keyword(s):  
Material Selection ◽  
Selection Process ◽  
Selection Problem ◽  
Decision Making Problem ◽  
Order Preference ◽  
Criteria Weights ◽  
Optimal Material ◽  
Criteria Importance ◽  
Topsis Technique ◽  
Vulcanization Process

The material selection problem is one of the most important steps in the development process of a part of any subassembly assembly, machine, product, etc. The material selection process needs a systematic and time-consuming approach to choose the optimal material to satisfy the product’s requirements. That is to say, many confronting criteria and possible material types (alternatives) available, makes this problem Multi-Criteria Decision-Making problem (MCDM). This paper shows the applicability of the MCDM methodology in the material selection problem for steam heating plates for the vulcanization process used in the inner tube manufacturing process. Specifically, the criteria weights are obtained by CRITIC (Criteria Importance Through Intercriteria Correlation), ENTROPY and PIPRECIA (Pivot Pairwise Relative Criteria Importance Assessment) methods, while TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution) method has been implemented in this process for evaluation and ranking of the possible alternatives (material types).

scholarly journals Multi-criteria healthcare waste disposal location selection based on Fermatean fuzzy WASPAS method

2021 ◽  
Author(s):  
Arunodaya Raj Mishra ◽  
Pratibha Rani
Keyword(s):  
Healthcare Providers ◽  
Score Function ◽  
Assessment Method ◽  
Selection Problem ◽  
Entropy Measure ◽  
Illustrative Case ◽  
Location Selection ◽  
Healthcare Waste ◽  
Criteria Weights ◽  
Illustrative Case Study

AbstractMedical services inevitably generate healthcare waste (HCW) that may become hazardous to healthcare staffs, patients, the population, and the atmosphere. In most of the developing countries, HCW disposal management has become one of the fastest-growing challenges for urban municipalities and healthcare providers. Determining the location for HCW disposal centers is a relatively complex process due to the involvement of various alternatives, criteria, and strict government guidelines about the disposal of HCW. The objective of the paper is to introduce the WASPAS (weighted aggregated sum product assessment) method with Fermatean fuzzy sets (FFSs) for the HCW disposal location selection problem. This method combines the score function, entropy measure, and classical WASPAS approach within FFSs context. Next, a combined procedure using entropy and score function is proposed to estimate the criteria weights. To do this, a novel score function with its desirable properties and some entropy measures are introduced under the FFSs context. Further, an illustrative case study of the HCW disposal location selection problem on FFSs is established, which evidences the practicality and efficacy of the developed approach. Comparative discussion and sensitivity analysis are made to monitor the permanence of the introduced framework. The final results approve that the proposed methodology can effectively handle the ambiguity and inaccuracy in the decision-making procedure of HCW disposal location selection.

scholarly journals Influence of the Share of Renewable Energy Sources on the Level of Energy Security in EECCA Countries

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 903 ◽  
Author(s):  
Ivan Trifonov ◽  
Dmitry Trukhan ◽  
Yury Koshlich ◽  
Valeriy Prasolov ◽  
Beata Ślusarczyk
Keyword(s):  
Renewable Energy ◽  
Energy Security ◽  
Structural Characteristics ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Energy Sources ◽  
Structural Content ◽  
High Degree

In this study we aimed to determine the extent to which changes in the share of renewable energy sources, their structural complex, and the level of energy security in Eastern Europe, Caucasus and Central Asia (EECCA) countries in the medium- and long-term are interconnected. The study was performed through modeling and determination of the structural characteristics of energy security in the countries. The methodology of the approach to modeling was based on solving the problem of nonlinear optimization by selecting a certain scenario. For the study, the data of EECCA countries were used. The ability of EECCA countries to benefit from long-term indirect and induced advantages of the transformation period depends on the extent to which their domestic supply chains facilitate the deployment of energy transformation and induced economic activity. This study provides an opportunity to assess the degree of influence of renewable energy sources on the level of energy security of countries in the context of energy resource diversification. The high degree of influence of renewable energy sources on energy security in the EECCA countries has been proven in the implementation of the developed scenarios for its increase. Energy security is growing. At the same time, its level depends not only on an increase in the share of renewable sources but also on the structure of energy resources complex of countries, and the development of various renewable energy sources. Therefore, today the EECCA countries are forced not only to increase the share of renewable energy sources but also to attach strategic importance to the structural content of their energy complex.

scholarly journals Comparative Analysis of Hybrid Fuzzy MCGDM Methodologies for Optimal Robot Selection Process

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 839
Author(s):  
Tabasam Rashid ◽  
Asif Ali ◽  
Juan Guirao ◽  
Adrián Valverde
Keyword(s):  
Selection Process ◽  
Industrial Robot ◽  
Vital Role ◽  
Decision Makers ◽  
Fuzzy Information ◽  
Criteria Weights ◽  
Topsis Technique ◽  
Fuzzy Weights ◽  
Robot Selection ◽  
Interval Valued

The generalized interval-valued trapezoidal fuzzy best-worst method (GITrF-BWM) provides more reliable and more consistent criteria weights for multiple criteria group decision making (MCGDM) problems. In this study, GITrF-BWM is integrated with the extended TOPSIS (technique for order preference by similarity to the ideal solution) and extended VIKOR (visekriterijumska optimizacija i kompromisno resenje) methods for the selection of the optimal industrial robot using fuzzy information. For a criteria-based selection process, assigning weights play a vital role and significantly affect the decision. Assigning weights based on direct opinions of decision makers can be biased, so weight deriving models, such as GITrF-BWM, overcome this discrepancy. In previous studies, generalized interval-valued trapezoidal fuzzy weights were not derived by using any MCGDM method for the robot selection process. For this study, both subjective and objective criteria are considered. The preferences of decision makers are provided with the help of linguistic terms that are then converted into fuzzy information. The stability and reliability of the methods were tested by performing sensitivity analysis, which showed that the ranking results of both the methodologies are not symmetrical, and the integration of GITrF-BWM with the extended TOPSIS method provides stable and reliable results as compared to the integration of GITrF-BWM with the extended VIKOR method. Hence, the proposed methodology provides robust optimal industrial robot selection.

scholarly journals A Dispatching-Fuzzy AHP-TOPSIS Model for Scheduling Flexible Job-Shop Systems in Industry 4.0 Context

2021 ◽  
Vol 11 (11) ◽  
pp. 5107
Author(s):  
Miguel Ortíz-Barrios ◽  
Antonella Petrillo ◽  
Fabio De Felice ◽  
Natalia Jaramillo-Rueda ◽  
Genett Jiménez-Delgado ◽  
...  
Keyword(s):  
Job Shop ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Flexible Job Shop ◽  
Criteria Weights ◽  
Dispatching Algorithm ◽  
Scheduling Method ◽  
Hard Problems ◽  
Fourth Step

Scheduling flexible job-shop systems (FJSS) has become a major challenge for different smart factories due to the high complexity involved in NP-hard problems and the constant need to satisfy customers in real time. A key aspect to be addressed in this particular aim is the adoption of a multi-criteria approach incorporating the current dynamics of smart FJSS. Thus, this paper proposes an integrated and enhanced method of a dispatching algorithm based on fuzzy AHP (FAHP) and TOPSIS. Initially, the two first steps of the dispatching algorithm (identification of eligible operations and machine selection) were implemented. The FAHP and TOPSIS methods were then integrated to underpin the multi-criteria operation selection process. In particular, FAHP was used to calculate the criteria weights under uncertainty, and TOPSIS was later applied to rank the eligible operations. As the fourth step of dispatching the algorithm, the operation with the highest priority was scheduled together with its initial and final time. A case study from the smart apparel industry was employed to validate the effectiveness of the proposed approach. The results evidenced that our approach outperformed the current company’s scheduling method by a median lateness of 3.86 days while prioritizing high-throughput products for earlier delivery.

Wind Turbine Aerodynamic Braking System Analysis Using Chord Wise Spacing

2015 ◽  
Vol 787 ◽  
pp. 217-221 ◽  
Author(s):  
B. Navin Kumar ◽  
K.M. Parammasivam
Keyword(s):  
Renewable Energy ◽  
Wind Turbine ◽  
Wind Velocity ◽  
Turbine Blade ◽  
Wind Turbines ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Braking System ◽  
Extreme Wind ◽  
Wind Potential

Wind energy is one of the most significant renewable energy sources in the world. It is the only promising renewable energy resource that only can satisfy the nation’s energy requirements over the growing demand for electricity. Wind turbines have been installed all over the wind potential areas to generate electricity. The wind turbines are designed to operate at a rated wind velocity. When the wind turbines are exposed to extreme wind velocities such as storm or hurricane, the wind turbine rotates at a higher speed that affects the structural stability of the entire system and may topple the system. Mechanical braking systems and Aerodynamic braking systems have been currently used to control the over speeding of the wind turbine at extreme wind velocity. As a novel approach, it is attempted to control the over speeding of the wind turbine by aerodynamic braking system by providing the chord wise spacing (opening). The turbine blade with chord wise spacing alters the pressure distribution over the turbine blade that brings down the rotational speed of the wind turbine within the allowable limit. In this approach, the over speeding of the wind turbine blades are effectively controlled without affecting the power production. In this paper the different parameters of the chord wise spacing such as position of the spacing, shape of the spacing, width of the spacing and impact on power generation are analyzed and the spacing parameters are experimentally optimized.

Research on Material Selection with Multi-Attribute Decision Method and G1 Method

2014 ◽  
Vol 952 ◽  
pp. 20-24 ◽  
Author(s):  
Xue Jun Xie
Keyword(s):  
Material Selection ◽  
Selection Process ◽  
Selection Problem ◽  
Topsis Method ◽  
Attribute Weight ◽  
Multi Attribute Decision Making ◽  
Judgment Matrix ◽  
Optimal Material ◽  
Selection Of ◽  
Better Than

The selection of an optimal material is an important aspect of design for mechanical, electrical, thermal, chemical or other application. Many factors (attributes) need to be considered in material selection process, and thus material selection problem is a multi-attribute decision making (MADM) problem. This paper proposes a new MADM method for material selection problem. G1 method does not need to test consistency of the judgment matrix. Thus it is better than AHP. In this paper, firstly, we use the G1 method to determine the attribute weight. Then TOPSIS method is used to calculate the closeness of the candidate materials with respect positive solution. A practical material selection case is used to demonstrate the effectiveness and feasibility of the proposed method.

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