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.

scholarly journals AN INTEGRATED MULTI-CRITERIA DECISION-MAKING FRAMEWORK FOR SUSTAINABLE SUPPLIER SELECTION UNDER PICTURE FUZZY ENVIRONMENT

2020 ◽  
Vol 26 (3) ◽  
pp. 573-598 ◽  
Author(s):  
Juan-juan Peng ◽  
Chao Tian ◽  
Wen-yu Zhang ◽  
Shuai Zhang ◽  
Jian-qiang Wang
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Evaluation Criteria ◽  
Multi Criteria Decision Making ◽  
Sustainable Supply Chain ◽  
Vikor Method ◽  
Minimization Principle ◽  
Fuzzy Environment ◽  
Sustainable Supplier Selection ◽  
Exponential Entropy

Sustainable supplier selection (SSS) is an important part of sustainable supply chain management (SSCM). In this paper, an integrated multi-criteria decision-making (MCDM) framework, based on the picture fuzzy exponential entropy, and the VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method, is proposed to manage SSS problems. Firstly, the evaluation criteria of SSS, including economic, environmental and social, is established. This can be evaluated in the form of the actual data or linguistic terms provided by suppliers and experts respectively in an actual decision-making process. Then, according to the translated scales, all the evaluation information can be converted into picture fuzzy numbers (PFNs). Secondly, the picture fuzzy exponential entropy is defined. Moreover, based on the entropy’s minimization principle, the defined picture fuzzy exponential entropy is used to determine the weight of the SSS’s criteria. Thirdly, the extended VIKOR method, which combines the grey correlation coefficient, is utilized to select a suitable supplier. This method avoids the shortcomings of the traditional VIKOR method in data mining and solves the conflict between SSS criteria. Finally, the feasibility and effectiveness of the proposed integrated decision framework are verified by an experiment, as well as a sensitivity analysis and comparative analysis.

scholarly journals Supplier Selection Application Based on a Fuzzy Multiple Criteria Decision Making Methodology

2012 ◽  
Vol 3 (8) ◽  
pp. 7-18
Author(s):  
Hüseyin Selçuk KILIÇ
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supplier Selection ◽  
Selection Process ◽  
Multiple Criteria Decision Making ◽  
Working Environment ◽  
Multi Criteria Decision Making ◽  
Chain Management ◽  
Fuzzy Environment ◽  
Selection Methodology

Due to the increasing competitiveness in every sector of business life, being effective in every process of the organizations has been required. At this point, one of the most important processes is supplier selection process within the concept of supply chain management. If a systematic supplier selection methodology is performed, it will be possible to select the most suitable supplier and provide efficiency with respect to time, quality and cost. With this study, depending on the vague structure of the real working environment, an extensively used multi criteria decision making methodology TOPSIS is used within fuzzy environment. The proposed technique is applied in a real case and the most suitable suppliers are determined and ranked.

scholarly journals A Rough Multi-Criteria Decision-Making Approach for Sustainable Supplier Selection under Vague Environment

2018 ◽  
Vol 10 (8) ◽  
pp. 2622 ◽  
Author(s):  
Huiyun Lu ◽  
Shaojun Jiang ◽  
Wenyan Song ◽  
Xinguo Ming
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Rough Set ◽  
Supplier Selection ◽  
Rough Set Theory ◽  
Multi Criteria Decision Making ◽  
Sustainable Supply Chain ◽  
Sustainable Supplier Selection ◽  
Decision Making Problem ◽  
Priori Information

With the growing awareness of environmental and social issues, sustainable supply chain management (SSCM) has received considerable attention both in academia and industry. Supplier selection plays an important role in the successful implementation of sustainable supply chain management, because it can influence the performance of SSCM. Sustainable supplier selection is a typical multi-criteria decision-making problem involving subjectivity and vagueness. Although some previous researches of supplier selection use fuzzy approaches to deal with vague information, it has been criticized for requiring much priori information and inflexibility in manipulating vagueness. Moreover, the previous methods often omit the environmental and social evaluation criteria in the supplier selection. To manipulate these problems, a new approach based on the rough set theory and ELECTRE (ELimination Et Choix Traduisant la REalité) is developed in this paper. The novel approach integrates the strength of rough set theory in handling vagueness without much priori information and the merit of ELECTRE in modeling multi-criteria decision-making problem. Finally, a case study of sustainable supplier selection for solar air-conditioner manufacturer is provided to demonstrate the application and potential of the approach.

New Einstein Hybrid Aggregation Operators for Intuitionistic Fuzzy Sets and Applications in Multi-Criteria Decision-Making

2019 ◽  
pp. 252-283
Author(s):  
Bhagawati Prasad Joshi ◽  
Abhay Kumar
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Decision Maker ◽  
Intuitionistic Fuzzy Sets ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Decision Making Processes

The fusion of multidimensional intuitionistic fuzzy information plays an important part in decision making processes under an intuitionistic fuzzy environment. In this chapter, it is observed that existing intuitionistic fuzzy Einstein hybrid aggregation operators do not follow the idempotency and boundedness. This leads to sometimes illogical and even absurd results to the decision maker. Hence, some new intuitionistic fuzzy Einstein hybrid aggregation operators such as the new intuitionistic fuzzy Einstein hybrid weighted averaging (IFEHWA) and the new intuitionistic fuzzy Einstein hybrid weighted geometric (IFEHWG) were developed. The new IFEHWA and IFEHWG operators can weigh the arguments as well as their ordered positions the same as the intuitionistic fuzzy Einstein hybrid aggregation operators do. Further, it is validated that the defined operators are idempotent, bounded, monotonic and commutative. Then, based on the developed approach, a multi-criteria decision-making (MCDM) procedure is given. Finally, a numerical example is conducted to demonstrate the proposed method effectively.

A multi-objective optimization model for sustainable supply chain network with using genetic algorithm

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Ehtesham Rasi ◽  
Mehdi Sohanian
Keyword(s):  
Supply Chain ◽  
Performance Indicators ◽  
Supplier Selection ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Sustainability Performance ◽  
Multi Objective ◽  
Sustainable Supplier Selection

Purpose The purpose of this paper is to design and optimize economic and environmental dimensions in a sustainable supply chain (SSC) network. This paper developed a mixed-integer linear programing (MILP) model to incorporate economical and environmental data for multi-objective optimization of the SSC network. Design/methodology/approach The overall objective of the present study is to use high-quality raw materials, at the same time the lowest amount of pollution emission and the highest profitability is achieved. The model in the problem is solved using two algorithms, namely, multi-objective genetic and multi-objective particle swarm. In this research, to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system. Findings The differences found between the genetic algorithms (GAs) and the MILP approaches can be explained by handling the constraints and their various logics. The solutions are contrasted with the original crisp model based on either MILP or GA, offering more robustness to the proposed approach. Practical implications The model is applied to Mega Motor company to optimize the sustainability performance of the supply chain i.e. economic (cost), social (time) and environmental (pollution of raw material). The research method has two approaches, namely, applied and mathematical modeling. Originality/value There is limited research designing and optimizing the SSC network. This study is among the first to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system.

scholarly journals Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment

2021 ◽  
Author(s):  
Srikant Gupta ◽  
Ahteshamul Haq ◽  
Irfan Ali ◽  
Biswajit Sarkar
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Real Life ◽  
Decision Makers ◽  
Supply Chain Network ◽  
Multi Objective ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Hierarchical Decision

AbstractDetermining the methods for fulfilling the continuously increasing customer expectations and maintaining competitiveness in the market while limiting controllable expenses is challenging. Our study thus identifies inefficiencies in the supply chain network (SCN). The initial goal is to obtain the best allocation order for products from various sources with different destinations in an optimal manner. This study considers two types of decision-makers (DMs) operating at two separate groups of SCN, that is, a bi-level decision-making process. The first-level DM moves first and determines the amounts of the quantity transported to distributors, and the second-level DM then rationally chooses their amounts. First-level decision-makers (FLDMs) aimed at minimizing the total costs of transportation, while second-level decision-makers (SLDM) attempt to simultaneously minimize the total delivery time of the SCN and balance the allocation order between various sources and destinations. This investigation implements fuzzy goal programming (FGP) to solve the multi-objective of SCN in an intuitionistic fuzzy environment. The FGP concept was used to define the fuzzy goals, build linear and nonlinear membership functions, and achieve the compromise solution. A real-life case study was used to illustrate the proposed work. The obtained result shows the optimal quantities transported from the various sources to the various destinations that could enable managers to detect the optimum quantity of the product when hierarchical decision-making involving two levels. A case study then illustrates the application of the proposed work.

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