scholarly journals TOPSIS Method for Probabilistic Linguistic MAGDM with Entropy Weight and Its Application to Supplier Selection of New Agricultural Machinery Products

Entropy ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. 953 ◽  
Author(s):  
Jianping Lu ◽  
Cun Wei ◽  
Jiang Wu ◽  
Guiwu Wei
Keyword(s):  
Supplier Selection ◽  
Scoring Function ◽  
Ideal Solution ◽  
Agricultural Machinery ◽  
Topsis Method ◽  
Entropy Weight ◽  
Suitable Alternative ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Selection Of

In multiple attribute group decision making (MAGDM) problems, uncertain decision information is well-represented by linguistic term sets (LTSs). These LTSs are easily converted into probabilistic linguistic sets (PLTSs). In this paper, a TOPSIS method is proposed for probabilistic linguistic MAGDM in which the attribute weights are completely unknown, and the decision information is in the form of probabilistic linguistic numbers (PLNs). First, the definition of the scoring function is used to solve the probabilistic linguistic entropy, which is then employed to objectively derive the attribute weights. Second, the optimal alternatives are determined by calculating the shortest distance from the probabilistic linguistic positive ideal solution (PLPIS) and on the other side the farthest distance of the probabilistic linguistic negative ideal solution (PLNIS). This proposed method extends the applications range of the traditional entropy-weighted method. Moreover, it doesn’t need the decision-maker to give the attribute weights in advance. Finally, a numerical example for supplier selection of new agricultural machinery products is used to illustrate the use of the proposed method. The result shows the approach is simple, effective and easy to calculate. The proposed method can contribute to the selection of suitable alternative successfully in other selection problems.

Taxonomy-based multiple attribute group decision making method with probabilistic uncertain linguistic information and its application in supplier selection

2021 ◽  
pp. 1-14
Author(s):  
Yan He ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Medical Instrument ◽  
Uncertain Information ◽  
Suitable Alternative ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Linguistic Term ◽  
Selection Of

The optimal supplier selection in medical instrument industries could be considered a classical MAGDM issue. The probabilistic uncertain linguistic term sets (PULTSs) could depict uncertain information well and the Taxonomy method is appropriate to compare various alternatives according to their merits and utility degree from studied attributes. In such paper, we develop a Taxonomy method for probabilistic uncertain linguistic MAGDM (PUL-MAGDM) with the completely unknown attribute weights. Above all, the score function’s definition is utilized to derive the weights of attribute based upon the CRITIC method. In addition, the probabilistic uncertain linguistic development pattern (PULDP) is improved and the smallest development attribute value from the positive ideal solution under PULTSs is calculated to determine the optimal alternative. In the end, taking the supplier selection in medical instrument industries as an example, we demonstrate the usage of the developed algorithms. Based on this, the comparison of methods is conducted with existing methods, such as PUL-TOPSIS method, the PULWA operator, the PUL-EDAS method and the ULWA operator. The results verify that the decision-making framework is valid and effective for supplier selection. Thus, the advantage of this designed method is that it is simple to understand and easy to compute. The designed method can also contribute to the selection of suitable alternative successfully in other selection issues.

scholarly journals A Hybrid Multi-Criteria Decision-Making Approach Based on ANP-Entropy TOPSIS for Building Materials Supplier Selection

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1597
Author(s):  
Chun-Ho Chen
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Building Materials ◽  
Evaluation Criteria ◽  
Analytic Network Process ◽  
Topsis Method ◽  
Entropy Weight ◽  
Suitable Alternative ◽  
Multi Criteria Evaluation ◽  
Network Process

This article will tell you how to combine “entropy” in the model to reduce the bias of multi-criteria evaluation. Subjective weights are usually determined by decision makers based on their professional background, experience and knowledge, and other factors. The objective weight is obtained by constructing an evaluation matrix of the information based on the actual information of the evaluation criteria of the scheme, and obtained through multi-step calculations. Different decision-making methods are based on different weight types. Considering only one of the two weights often leads to biased results. In addition, in order to establish an effective supply chain, buyers must find suitable merchants among suppliers that provide quality products and/or services. Based on the above factors, it is difficult to choose a suitable alternative. The main contribution of this paper is to combine analytic network process (ANP), entropy weight and the technique for order preference by similarity to an ideal solution (TOPSIS) to construct a suitable multi-criteria decision (MCDM) model. By means of ANP-entropy weights to extend the TOPSIS method, ANP-entropy weights are used to replace subjective weights. A supplier selection decision-making model based on ANP-entropy TOPSIS is proposed. At last, the sensitivity analysis shows that, taking the selection of building materials suppliers as an example, the hybrid ANP-entropy TOPSIS method can effectively select suitable suppliers.

QUALIFLEX method for MAGDM with probabilistic uncertain linguistic information and its application to green supplier selection

2020 ◽  
Vol 39 (5) ◽  
pp. 6819-6831
Author(s):  
Fan Lei ◽  
Guiwu Wei ◽  
Jiang Wu ◽  
Cun Wei ◽  
Yanfeng Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Linguistic Information ◽  
Suitable Alternative ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Selection Of

Probabilistic uncertain linguistic sets (PULTSs) have extensively been employed in multiple attribute group decision making (MAGDM)problem. The QUALIFLEX method, which is relatively a novel MAGDM technique, aims to obtain the optimal alternative. This paper proposes the probabilistic uncertain linguistic QUALIFLEX (PUL-QUALIFLEX) method with CRITIC method. To show the effectiveness of the designed method, an application is given for green supplier selection and the derived results are compared with some existing methods. Thus, the advantage of this proposed method is that it is simple to understand and easy to compute. The proposed method can also contribute to the selection of suitable alternative successfully in other selection issues.

scholarly journals Evaluation and selection of transportation service provider by TOPSIS method with entropy weight

2021 ◽  
pp. 50-50
Author(s):  
Xu Wu ◽  
Cheng Zhang ◽  
Luojun Yang
Keyword(s):  
Service Provider ◽  
Entropy Method ◽  
Ideal Solution ◽  
Topsis Method ◽  
Entropy Weight ◽  
Transportation Service ◽  
Improved Technique ◽  
Criterion Method ◽  
Selection Of

In this paper, an improved technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to select the optimal transportation service provider among several alternatives according to a multi-criterion method. An entropy method is embedded to determine the weights of different criteria and it is effective to avoid the subjectivity and arbitrary of choosing the weights. A case study demonstrates the proposed method is reasonable and valid for practical problems.

scholarly journals Sustainable Performance Evaluation: Evidence from Listed Chinese Mining Corporations

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 349
Author(s):  
Yuan Ma ◽  
Jingzhi Men ◽  
Mingyu Li ◽  
Xiaoyan Li
Keyword(s):  
Sustainable Development ◽  
Evaluation System ◽  
Industrial Development ◽  
Ideal Solution ◽  
Topsis Method ◽  
Entropy Weight ◽  
Four Dimensions ◽  
Sustainable Performance ◽  
Research Gap ◽  
Development Evaluation

Rapid industrial development has caused a series of environmental problems, which is not conducive to sustainable development of society as a whole. It is necessary to build a sustainable development evaluation system. Most of the existing literature has evaluated corporate sustainable performance from the economy, environment and society on the basis of triple bottom lines. Considering the research gap and the practice need, an evaluation system is established from four dimensions, referred to as economy, society, environment and responsibility management, and 29 indicators are designed to measure these four dimensions. Twenty seven listed Chinese mining corporations are selected as research samples, and the entropy-weight-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is applied to calculate indicators’ weights. Results show that the four dimensions of sustainable performance weights from high to low are society, environment, economy, and management process.

scholarly journals Supplier selection using different metric functions

2015 ◽  
Vol 25 (3) ◽  
pp. 413-423 ◽  
Author(s):  
S.E. Omosigho ◽  
Dickson Omorogbe
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Topsis ◽  
Ideal Solution ◽  
Order Preference ◽  
Metric Functions ◽  
Metric Function ◽  
Topsis Technique ◽  
Intuitionistic Fuzzy Topsis ◽  
Selection Of

Supplier selection is an important component of supply chain management in today?s global competitive environment. Hence, the evaluation and selection of suppliers have received considerable attention in the literature. Many attributes of suppliers, other than cost, are considered in the evaluation and selection process. Therefore, the process of evaluation and selection of suppliers is a multi-criteria decision making process. The methodology adopted to solve the supplier selection problem is intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution). Generally, TOPSIS is based on the concept of minimum distance from the positive ideal solution and maximum distance from the negative ideal solution. We examine the deficiencies of using only one metric function in TOPSIS and propose the use of spherical metric function in addition to the commonly used metric functions. For empirical supplier selection problems, more than one metric function should be used.

Selection of resilient suppliers in manufacturing industries post-COVID-19: implications for economic and social sustainability in emerging economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abhijit Majumdar ◽  
Jeevaraj S ◽  
Mathiyazhagan Kaliyan ◽  
Rohit Agrawal
Keyword(s):  
Decision Making ◽  
Incomplete Information ◽  
Emerging Economies ◽  
Supplier Selection ◽  
Fuzzy Decision Making ◽  
Ideal Solution ◽  
Fuzzy Decision ◽  
Content Type ◽  
Intuitionistic Fuzzy ◽  
Selection Of

PurposeSelection of resilient suppliers has attracted the attention of researchers in the past one decade. The devastating effect of COVID-19 in emerging economies has provided great impetus to the selection of resilient suppliers. Under volatile and uncertain business scenarios, supplier selection is often done under imprecise and incomplete information, making the traditional decision-making methods ineffective. The purpose of this paper is to demonstrate the application of a fuzzy decision-making method for resilient supplier selection.Design/methodology/approachA group of three decision makers was considered for evaluating various alternatives (suppliers) based on their performance under different primary, sustainability and resilience criteria. Experts' opinion about each criterion and alternative was captured in linguistic terms and was modelled using fuzzy numbers. Then, an algorithm for solving resilient supplier selection problem based on the trapezoidal intuitionistic fuzzy technique for order preference by similarity to ideal solution (TrIFTOPSIS) was introduced and demonstrated through a case study.FindingsA closeness coefficient was used to rank the suppliers based on their distances from intuitionistic fuzzy positive-ideal solution and intuitionistic fuzzy negative-ideal solution. Finally, the proposed fuzzy decision making model was applied to a real problem of supplier selection in the clothing industry.Originality/valueThe presented TrIFTOPSIS model provides an effective route to prioritise and select resilient suppliers under imprecise and incomplete information. This is the first application of intuitionistic fuzzy multi-criteria decision-making for resilient supplier selection.

scholarly journals Selection of the best location for solar plants in Turkey

2017 ◽  
Vol 26 (4) ◽  
pp. 52 ◽  
Author(s):  
Adnan Sozen ◽  
Amin Mirzapour ◽  
M. Tarik Çakir
Keyword(s):  
Data Envelopment Analysis ◽  
Solar Energy ◽  
Data Envelopment ◽  
Ideal Solution ◽  
Optimum Location ◽  
Topsis Method ◽  
Dea Efficiency ◽  
Solar Intensity ◽  
Location Identification ◽  
Selection Of

The unique properties of solar energy have led to increasing demands in various countries. In order to use solar energy effectively, environmental and geographical circumstances related to solar intensity must be considered. Different factors may affect the selection of suitable locations for solar plants. These factors must be considered concurrently for optimum location identification. This article presents an approach for the location of solar plants by data envelopment analysis (DEA). Efficiency scores over a twelve month period were evaluated by using a modified similarity to ideal solution (TOPSIS) method. This approach was applied to 30 different cities in different regions of Turkey.

scholarly journals Penerapan Metode Topsis Untuk Pemilihan Vendor Terbaik

2021 ◽  
Vol 11 (2) ◽  
pp. 19-30
Author(s):  
Derman Janner Lubis ◽  
Nur Amalina Anindita
Keyword(s):  
Calculation Method ◽  
Research Method ◽  
Ideal Solution ◽  
Topsis Method ◽  
Decision Matrix ◽  
Relative Closeness ◽  
The Matrix ◽  
Order Preference ◽  
Topsis Technique ◽  
Selection Of

The selection of vendors to work on a project is an activity that must be carried out effectively and precisely so that the project is carried out in accordance with business needs and does not suffer losses. To get the best vendor ranking, you can use the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) calculation method. TOPSIS method is a method that generates rankings by calculating the distance between the best solution and the worst solution. The steps to calculate using TOPSIS are identification of alternatives and their values, create a decision matrix, normalize the matrix, calculate the normalization matrix, look for positive and negative solutions, calculate the distance between positive and negative solutions, and calculate relative closeness and sort preferences. In this study using 8 criteria and 5 alternative vendors. Research method using research and development. This method will produce a prototype. The results of the calculation of TOPSIS obtained vendor c who gets the highest score and vendor b with the lowest rank

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