scholarly journals A Novel Multi-Criteria Decision-Making Model: Interval Rough SAW Method for Sustainable Supplier Selection

Information ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 292 ◽  
Author(s):  
Željko Stević ◽  
Elmina Durmić ◽  
Mladen Gajić ◽  
Dragan Pamučar ◽  
Adis Puška
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Rank Correlation ◽  
Multi Criteria Decision Making ◽  
Weighting Method ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient ◽  
Sustainable Supplier Selection ◽  
Simple Additive Weighting ◽  
The Stability

Sustainability in a supply chain is a demand on the one hand and a challenge on the other. It is necessary to balance between these dimensions in order to fulfill the purpose of the supply chain. Therefore, in the first phase—i.e., in procurement—it is necessary to take into account its sustainability. In this paper, a sustainable supplier was selected respecting all three aspects of sustainability. The evaluation was carried out on the basis of a total of 21 criteria arranged into two levels and three groups. A new Interval Rough SAW (simple additive weighting) method, which represents a contribution to the treatment of problems belonging to the multi-criteria decision-making (MCDM), was developed. The integration of interval rough numbers with the SAW method was completed. In addition, the full consistency method (FUCOM) was applied to determine the weights of the criteria. The integrated FUCOM-Interval Rough SAW model enables treatment of multi-criteria problems while reducing subjectivity to the lowest possible level and eliminating uncertainties and ambiguities. The results obtained were determined throughout a sensitivity analysis consisting of a change in the weight of the criteria and the influence of dynamic matrices on the change in ranks. In addition, Spearman’s rank correlation coefficient (SCC) was calculated to confirm the stability of the previously obtained results.

scholarly journals Optimizing Material Selection Using a Hybridized Multi-attribute Decision Making Model

2021 ◽  
Vol 16 ◽  
pp. 404-421
Author(s):  
Eslam Mohammed Abdelkader ◽  
Abobakr Al-Sakkaf ◽  
Ghasan Alfalah
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Material Selection ◽  
Rank Correlation ◽  
Multi Criteria Decision Making ◽  
Numerical Examples ◽  
Selection Problems ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient ◽  
Selection Of

Material selection is a very entangled and decisive stage in the design and development of products. There are large numbers of on hand and newly developed materials available in the market. In addition, inability to select the correct materials adversely affects the reputation and profitability of the company. Thus, designers need to study and trace the performance of available materials with appropriate functionalities. Thus, this research aims at establishing an efficient and systematic platform for the optimum selection of materials while accommodating the designated conflicting performance requirements. The developed model encompasses designing a hybrid decision support system in an attempt to circumvent the shortcomings of single multi-criteria decision making-based (MCDM) models. First, the objective relative importance weights of attributes are interpreted capitalizing on Shannon entropy algorithm. Then, an integrated model that encompasses the utilization of six different types of multi-criteria decision making algorithms is designed to create a reliable selection of material alternatives. The utilized MCDM algorithms comprise weighted product method (WPM), simple additive weighting (SAW), additive ratio assessment (ARAS), new combinative distance-based assessment (CODAS), complex proportional assessment (COPRAS) and technique for order of preference by similarity to ideal solution (TOPSIS). Afterwards, COPELAND algorithm is exploited to generate a consensus and distinct ranking of material alternatives. Eventually, Spearman’s rank correlation analysis is used to evaluate the rankings obtained from the MCDM algorithms. Five numerical examples in diverse fields of material selection are tackled to examine the features and efficiency of the developed integrated model. Results illustrated that the developed model was able to solve the five material selection problems efficiently. On the other hand, no individual MCDM algorithm was able to solve all the assigned material selection problems. For instance, CODAS and TOPSIS only succeeded in solving one and two material selection problems, respectively. It was also inferred that notable differences and perturbations are encountered between the rankings of MCDM algorithms in the first, third, fourth and fifth numerical examples, which necessitates the implementation of COPELAND algorithm. It was also revealed that the highest correlation lied between COPRAS and WPM with an average Spearman’s rank correlation coefficient of 92.67%. On the other hand, the correlation between TOPSIS and CODAS attained the lowest rank with an average Spearman’s rank correlation coefficient of 18.95%. Results also demonstrated that COPRAS accomplished the highest Spearman’s rank correlation coefficient with 59.54%. Hence, it is the most efficient MCDM algorithm among the five algorithms which can serve as a reference for solving material selection problems. It can be also deduced that CODAS and TOPSIS are not advised to be implemented in solving similar material selection problems.

scholarly journals Ordering of innovation projects by multi-criteria decision-making methods – a comparison

2021 ◽  
Vol 67 (3) ◽  
pp. 84-94
Author(s):  
Martin Mizla ◽  
◽  
Denisa Šefčíková ◽  
Jozef Gajdoš ◽  
◽  
...  
Keyword(s):  
Decision Making ◽  
Quantitative Methods ◽  
Rank Correlation ◽  
Multi Criteria Decision Making ◽  
Data Set ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient ◽  
Innovation Projects ◽  
Mutual Comparison ◽  
It Decision Making

In the case of the integration process, economic and social differences between economic units represent a barrier. There are reasonable and active efforts of many administrative bodies to transfer the existing inequalities to equalities. In practical life, it is often necessary to order different objects and take a decision based on it. Decision-making can be intuitive or, conversely, based on various quantitative methods. The paper discusses some quantitative methods of multi-criteria decision-making (MCDM), namely Analytical Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Weighted Linear Combination (WLC); and their use for innovation projects. Autonomous orders of objects (projects) are performed on the same basic data set by the above-mentioned methods, and they are compared with each other. The Spearman’s rank correlation coefficient was used for mutual comparison. The test results showed that the investigated methods do not provide results with a close dependence, which means that the order of objects (projects) created depends on the method used.

scholarly journals Evaluation Method for Green Ecological Airports in China Based on Combination Weighting

2018 ◽  
Vol 30 (4) ◽  
pp. 419-428
Author(s):  
Danwen Bao ◽  
Xiaoling Zhang ◽  
Jiayu Gu
Keyword(s):  
Evaluation Method ◽  
Rank Correlation ◽  
Resource Conservation ◽  
Evaluation Index System ◽  
Weighting Method ◽  
Environmental Friendliness ◽  
International Airport ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient ◽  
The Status

To scientifically and accurately evaluate the status of the development of green airports in China, evaluation methods of green, ecological airports are established in this paper. To address the shortcomings in subjective and objective weighting methods, we propose a combination weighting method based on Spearman’s rank correlation coefficient and evaluation grades based on interval approximation. At the same time, by taking into account resource conservation, environmental friendliness, operation efficiency, and people-oriented service, we propose an evaluation index system and an interval number for each index. Lastly, the theory is applied to five large airports in different regions of China. Analysis of the evaluation results shows that Shanghai Pudong International Airport (PVG) and Guangzhou Baiyun International Airport (CAN) have the highest scores for the resource conservation and environmental friendliness indexes, thus indicating that the development of a green ecological airport is closely related to its passenger transportation scale and economic strength. All considered airports showed the need for upgrading public  service facilities and constructing intelligent equipment. The method proposed in this paper is reasonable  and reliable; therefore, it can provide guidance for the evaluation and construction of green, ecological  airports.

scholarly journals A New Hybrid MCDM Model: Sustainable Supplier Selection in a Construction Company

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 353 ◽  
Author(s):  
Bojan Matić ◽  
Stanislav Jovanović ◽  
Dillip Kumar Das ◽  
Edmundas Kazimieras Zavadskas ◽  
Željko Stević ◽  
...  
Keyword(s):  
Decision Making ◽  
Sustainable Development ◽  
Supply Chain ◽  
Second Phase ◽  
Sustainable Supply Chain ◽  
Construction Company ◽  
Sustainable Supplier Selection ◽  
Product Assessment ◽  
Simple Additive Weighting ◽  
Selection Of

Sustainable development is one of the most important preconditions for preserving resources and balanced functioning of a complete supply chain in different areas. Taking into account the complexity of sustainable development and a supply chain, different decisions have to be made day-to-day, requiring the consideration of different parameters. One of the most important decisions in a sustainable supply chain is the selection of a sustainable supplier and, often the applied methodology is multi-criteria decision-making (MCDM). In this paper, a new hybrid MCDM model for evaluating and selecting suppliers in a sustainable supply chain for a construction company has been developed. The evaluation and selection of suppliers have been carried out on the basis of 21 criteria that belong to all aspects of sustainability. The determination of the weight values of criteria has been performed applying the full consistency method (FUCOM), while a new rough complex proportional assessment (COPRAS) method has been developed to evaluate the alternatives. The rough Dombi aggregator has been used for averaging in group decision-making while evaluating the significance of criteria and assessing the alternatives. The obtained results have been checked and confirmed using a sensitivity analysis that implies a four-phase procedure. In the first phase, the change of criteria weight was performed, while, in the second phase, rough additive ratio assessment (ARAS), rough weighted aggregated sum product assessment (WASPAS), rough simple additive weighting (SAW), and rough multi-attributive border approximation area comparison (MABAC) have been applied. The third phase involves changing the parameter ρ in the modeling of rough Dombi aggregator, and the fourth phase includes the calculation of Spearman’s correlation coefficient (SCC) that shows a high correlation of ranks.

scholarly journals IMPLEMENTASI MULTI CRITERIA DECISION MAKING MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) PADA SISTEM PENDUKUNG KEPUTUSAN PROMOSI KENAIKAN JABATAN

2020 ◽  
Vol 12 (1) ◽  
pp. 47
Author(s):  
Eddy Kurniawan ◽  
Achmad Miftakhul Ilmi ◽  
Nufan Balafif
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Distribution Center ◽  
Assessment Process ◽  
Multi Criteria Decision Making ◽  
Weighting Method ◽  
Computer Based ◽  
Simple Additive Weighting ◽  
Alternative Decision ◽  
Employee Data

Telkomsel Distribution Center (TDC) Jombang has problems in promoting employees to fill the Supervisor (SPV) and Branch Manager (BM) positions. TDC Jombang has several assessment criteria for employees to be able to fill SPV and BM positions. But in the assessment process, each criterion still tends to be subjective. In making decisions based on several criteria, a Multi-Criteria Decision Making (MCDM) approach can be used by applying the method that is considered most appropriate to produce the best alternative decision recommendations. This study aims to provide the best solution by implementing the Multi-Criteria Decision Making approach using the SAW (Simple Additive Weighting) method which will be programmed in a computer-based decision support system (SPK). The SAW method was chosen because it can weigh the values on each attribute and rank to get the best alternative recommendations. The data used are Jombang TDC employee data. From this study, it was obtained that the use of the SAW method programmed in the SPK succeeded in presenting information comparing the value of preferences between candidates. Candidates with the highest preference value are the most recommended alternatives to choose

scholarly journals A New Extension to a Multi-Criteria Decision-Making Model for Sustainable Supplier Selection under an Intuitionistic Fuzzy Environment

2019 ◽  
Vol 11 (19) ◽  
pp. 5413 ◽  
Author(s):  
Patchara Phochanikorn ◽  
Chunqiao Tan
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supplier Selection ◽  
Multi Criteria Decision Making ◽  
Sustainable Supply Chain ◽  
Suggested Approach ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Sustainable Supplier Selection ◽  
Decision Making Model

The increase of environmental pollution has led to the rise of sustainable awareness in recent years. This trend has motivated various industries to recognize the importance of implementing sustainable supply chain practices to seek economic, environmental and social advantages. From a sustainability perspective, selecting a suitable supplier is the main component of modern enterprises. It is also a challenging problem since several criteria concerning supplier selection are interdependent with a complex character. Therefore, the contribution of this paper is a new extension to multi-criteria decision-making model (MCDM) under an intuitionistic fuzzy environment for sustainable supplier selection (SSS) based on sustainable supply chain management SSCM practices. It consists of intuitionistic fuzzy set theory (IFS) with a decision making trial and evaluation laboratory (DEMATEL) combined with an analytic network process (ANP) to identify uncertainties and interdependencies among criteria as well as analyzing the criteria weights. We modified Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to evaluate and rank the desired level of sustainable supplier performance. The suggested approach is conducted by a case study from the Thailand palm oil industry. Results show that the proposed model not only can find the most suitable sustainable supplier, but also the enterprises can aid their suppliers in improving sustainability by using the proposed method and can improve enterprises’ socio-environmental performance, which is key to achieving sustainable development.

Multi-Criteria Decision Making for Ranking Decision Making Units

2018 ◽  
Vol 6 (1) ◽  
pp. 17-36
Author(s):  
Mohammad Azadfallah
Keyword(s):  
Decision Making ◽  
Traditional Method ◽  
Multiple Criteria Decision Making ◽  
Rank Correlation ◽  
Ranking Method ◽  
Spearman’S Rank Correlation ◽  
Ranking Models ◽  
Spearman’S Rank Correlation Coefficient ◽  
One Step ◽  
Decision Making Units

There is no doubt the Data Envelopment Analysis (DEA) is a powerful method for the efficiency evaluation of Decision Making Units (DMUs) with multiple inputs and outputs. Despite its usefulness, DEA has some notable limitations. A significant drawback with this approach is that inability to fully rank the DMUs. In the extant literature, different methods for this purpose have been suggested. While, in the traditional method the first step for the DEA approach is used, and results of this step are input for the DEA ranking method in the second step. To reduce the computational complexity of the traditional method, a new Multiple Criteria Decision Making (MCDM) approach is proposed in this article. In the proposed approaches, one step can achieve full ranking for all DMUs. The results show that although out of 20 DMUs are first in the final ranking ordered by the DEA, the author proposed methods can consider full ranking. Agreement of the proposed methods with the existing approaches are measured by the Spearman's rank correlation coefficient technique. The findings of this study reveal that TOPSIS, Neo-TOPSIS, and AHP ranking results are consistent with the DEA ranking method. Therefore, these proposed methods appear as the possible alternatives to the DEA and DEA ranking models.

scholarly journals Sistem Pendukung Keputusan Dalam Memetakan Wilayah Risiko Banjir Menggunakan Fuzzy Multi Criteria Decision Making

d'CARTESIAN ◽  
2014 ◽  
Vol 3 (2) ◽  
pp. 24
Author(s):  
Glorya Ontah ◽  
Winsy Weku ◽  
Altien Rindengan
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Weighting Method ◽  
Order Preference ◽  
Simple Additive Weighting

Abstrak Banjir yang melanda di berbagai wilayah Indonesia merupakan suatu fenomena logis karena negara ini berada di daerah tropis dengan intensitas curah hujan yang sangat tinggi. Penelitian bertujuan untuk memetakan daerah berisiko banjir di Kota Manado. Pemetaan wilayah berisiko banjir di Kota Manado memerlukan beberapa pendapat atau masukan dari berbagai pihak. Atribut yang digunakan yaitu kemiringan lahan (%), ketinggian wilayah (%), DAS (km), luas pemukiman/wilayah tutupan lahan (%) dan curah hujan (mm). Penentuan wilayah banjir di Kota Manado menggunakan Fuzzy Multi Criteria Decision Making (MCDM) dengan dua (2) metode yaitu Simple Additive Weighting Method (SAW) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Hasil dengan menggunakan metode SAW dan SAW Fuzzy menunjukkan bahwa wilayah paling berisiko banjir yaitu Kecamatan Wenang. Hasil dengan menggunakan metode TOPSIS dan TOPSIS Fuzzy menunjukkan bahwa wilayah paling berisiko banjir yaitu Kecamatan Bunaken. Wenang sebagai wilayah banjir disebabkan lahan yang berada di dataran landai, ketinggian wilayah di bawah 240 meter, memiliki aliran sungai, intensitas curah hujan tinggi, dan besarnya tutupan lahan mencapai 94,59%. Bunaken menjadi wilayah banjir karena Bunaken memiliki aliran sungai terpanjang di Kota Manado yaitu 17,9 km. Kata kunci: Fuzzy, Kota Manado, MCDM, SAW, TOPSIS, Wilayah Banjir.

The vital-immaterial-mediocre multi-criteria decision-making method

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shervin Zakeri ◽  
Fatih Ecer ◽  
Dimitri Konstantas ◽  
Naoufel Cheikhrouhou
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Validity And Reliability ◽  
Managerial Decision ◽  
Analytic Hierarchy ◽  
Weighting Method ◽  
Content Type ◽  
Complex Process ◽  
Sustainable Supplier Selection ◽  
Managerial Implications

PurposeThis paper proposes a new multi-criteria decision-making method, called the vital-immaterial-mediocre method (VIMM), to determine the weight of multiple conflicting and subjective criteria in a decision-making problem.Design/methodology/approachThe novel method utilizes pairwise comparisons, vector-based procedures and a scoring approach to determine weights of criteria. The VIMM compares alternatives by the three crucial components, namely the vital, immaterial and mediocre criteria. The vital criterion has the largest effect on the final results, followed by the mediocre criterion and then the immaterial criterion, which is the least impactful on the prioritization of alternatives. VIMM is developed in two forms where the first scenario is designed to solve one-goal decision-making problems, while the second scenario embraces multiple goals.FindingsTo validate the method’s performance and applicability, VIMM is applied to a problem of sustainable supplier selection. Comparisons between VIMM, analytic hierarchy process (AHP) and best-worst method (BWM) reveal that VIMM significantly requires fewer comparisons. Moreover, VIMM works well with both fractional and integer numbers in its comparison procedures.Research limitations/implicationsAs an implication for research, we have added the development of the VIMM under fuzzy and grey environments as the direction for optimization of the method.Practical implicationsAs managerial implications, VIMM not only provides less complex process for the evaluation of the criteria in the managerial decision-making process, but it also generates consistent results, which make VIMM a reliable tool to apply to a large number of potential decision-making problems.Originality/valueAs a novel subjective weighting method, there exist five major values that VIMM brings over AHP and BWM methods: VIMM requires fewer comparisons compared with AHP and BWM; it is not sensitive to the number of criteria; as a goal-oriented method, it exclusively takes the decision-making goals into account; it keeps the validity and reliability of the Decision-Makers’ (DMs’) opinions and works well with integer and fractional numbers.

scholarly journals EVALUATION OF CLASSIFICATION ALGORITHMS USING MCDM AND RANK CORRELATION

2012 ◽  
Vol 11 (01) ◽  
pp. 197-225 ◽  
Author(s):  
GANG KOU ◽  
YANQUN LU ◽  
YI PENG ◽  
YONG SHI
Keyword(s):  
Decision Making ◽  
Experimental Study ◽  
Binary Classification ◽  
Multiple Criteria Decision Making ◽  
Rank Correlation ◽  
Performance Criteria ◽  
Classification Algorithms ◽  
Algorithm Selection ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient

Classification algorithm selection is an important issue in many disciplines. Since it normally involves more than one criterion, the task of algorithm selection can be modeled as multiple criteria decision making (MCDM) problems. Different MCDM methods evaluate classifiers from different aspects and thus they may produce divergent rankings of classifiers. The goal of this paper is to propose an approach to resolve disagreements among MCDM methods based on Spearman's rank correlation coefficient. Five MCDM methods are examined using 17 classification algorithms and 10 performance criteria over 11 public-domain binary classification datasets in the experimental study. The rankings of classifiers are quite different at first. After applying the proposed approach, the differences among MCDM rankings are largely reduced. The experimental results prove that the proposed approach can resolve conflicting MCDM rankings and reach an agreement among different MCDM methods.

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