Fuzzy TOPSIS and fuzzy VIKOR in selecting green suppliers for sponge iron and steel manufacturing

A comprehensive assessment to offer optimized remediation method for mercury contamination in Musa Bay by using hybrid Fuzzy AHP-VIKOR approach

Musa Bay, the largest wetland in Iran and one of the most important Hg-polluted media, plays a significant role in the ecosystem of the area and supports many forms of life. Mercury pollution has detrimental effects on the human body and at high levels leads to the loss of microorganisms in marine ecosystems. Hence, a comprehensive assessment for selecting an effective and sustainable remediation method is crucial to restoring the ecosystem promptly. The determination of a proper and practical treatment method not only is a case-based approach, but could be challenging due to its multi-criteria decision-making nature. Considering preferred crucial factors involved in the effectiveness of remedial actions, in this study a questionnaire is designed to assess the opinion of environmental experts, stakeholders, and some occupants of the area on remedial actions based on the importance weights of criteria. Subsequently, practical remediation and management strategies ranked by hybrid FVIKOR as a multi-criteria decision making (MCDM) method. Ranking results show that dredging and stabilization could offer a promising solution for the remediation of the case study. The results of the study demonstrate that the development of MCDM methods along with effective criteria and considering the analysis of the questionnaires, could offer the best remediation strategy for a specific contaminated site.

Picture fuzzy Additive Ratio Assessment Method (ARAS) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method for multi-attribute decision problem and their application

The purpose of this paper is to study the multi-attribute decision-making problem under the fuzzy picture environment. First, a method to compare the pros and cons of picture fuzzy numbers (PFNs) is introduced in this paper. Second, the correlation coefficient and standard deviation (CCSD) method is used to determine the attribute weight information under the picture fuzzy environment regardless of whether the attribute weight information is partially unknown or completely unknown. Third, the ARAS and VIKOR methods are extended to the picture fuzzy environment, and the proposed PFNs comparison rules are also applied in the PFS-ARAS and PFS-VIKOR methods. Fourth, the problem of green supplier selection in a picture-ambiguous environment is solved by the method proposed in this paper. Finally, the method proposed in this paper is compared with some methods and the results are analyzed.

A multi-criteria decision-making framework for electric vehicle supplier selection of government agencies and public bodies in China

Electric vehicle deployment shows promising potentials in promoting cleaner energy utilization and reducing carbon emission. Due to increasing carbon neutral pressure and market competition from transportation sector, government agencies and public bodies (GAPBs) have emphasized the significance of electric vehicle adoption through supplier selection. Consequently, GAPBs must consider a reasonable criteria system and a comprehensive supplier selection framework and rationally select the electric vehicle supplier that matches their practical needs in terms of economic, social, environmental, and technical factors. This paper provides insights into electric vehicle supplier selection (EVSS) from the perspective of GAPBs using an integrated multi-criteria decision-making (MCDM) framework based on best-worst method (BWM) and fuzzy ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Initially, 14 critical factors from economic, social, environmental, and technical dimensions are identified as the criteria by literature review and experts' opinions. Then, a comprehensive decision framework using the integrated MCDM approach is proposed. To validate the applicability and feasibility of the proposed framework, a case study is launched and analyzed. It emerges that bad environmental record, cost, quality, service, and environmental initiatives are the most important criteria in EVSS for GAPBs with the weight values of 0.1995, 0.1172, 0.1219, 0.0708, and 0.2553. The comparative analysis and the sensitivity analysis are performed for verifying the reliability of the proposed framework. The work helps to understand the electric vehicle supplier selection criteria and makes methodological decision-making support for GAPBs.

A goal programming-based fuzzy best-worst method for the viable supplier selection problem: a case study

Since the COVID-19 outbreak has led to drastic changes in the business environment, researchers attempt to introduce new approaches to improve the capability and flexibility of the industries. In this regard, recently, the concept of the viable supply chain, which tried to incorporate the leagile, resiliency, sustainability, and digitalization aspects into the post-pandemic supply chain, has been introduced by researchers. However, the literature shows that there is lack of study that investigated the viable supplier selection problem, as one of the crucial branches of viable supply chain management. Therefore, to cover this gap, the current work aims to develop a decision-making framework to investigated the viable supplier selection problem. In this regard, owing to the crucial role of the oxygen concentrator device during the COVID-19 outbreak, this research selects the mentioned product as a case study. After determining the indicators and alternatives of the research problem, a novel method named goal programming-based fuzzy best-worst method (GP-FBWM) is proposed to compute the indicators' weights. Then, the potential alternatives are prioritized employing the Fuzzy Vlse Kriterijumsk Optimizacija Kompromisno Resenje method. In general, the main contributions and novelties of the present research are to incorporate the elements of the viability concepts in the supplier selection problem for the medical devices industry and to develop an efficient method GP-FBWM to measure the importance of the criteria. Then, the developed method is implemented and the obtained results are analyzed. Finally, managerial and theoretical implications are provided.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00500-022-07572-0.

Deployment of fuzzy TOPSIS-integrated value stream mapping for a fabrication industry: a case study

Purpose

This research aims to identify lean tools and techniques that are needed to be implemented to improve the performance in the fabrication industry. The objective is to find the wastes in manufacturing processes using value stream mapping (VSM) and prioritize the lean tools suitable to enable the attainment of leanness and streamline the processes.

Design/methodology/approach

VSM tool is applied in the industry to construct the current state map, identify improvement proposals and implement in future state. Fuzzy technique for order performance by similarity to ideal solution (TOPSIS), a multi-criteria decision-making technique (MCDM), is used to prioritize the identified improvement proposals. This study observed that mistake-proof processing and layout organization are the two techniques with the top priority that needs further improvement to enhance the leanness of the organization.

Findings

Upon successful implementation, the cycle time is reduced by 14.97%, and total inventory is reduced by 45.67% which leads to the improvement of value addition from 5.88 to 9.21%. Although lean has been adopted for many years, implementation of lean in the fabrication industry has been limited.

Practical implications

This study addresses the challenges in terms of implementing lean in fabrication industries and practical implications of lean tools and techniques and the prioritization of lean concepts against various lean criteria to enable leanness.

Originality/value

The deployment of improvement prioritization tool integrated with VSM in the context of a fabrication industry is the original contribution of the authors.

The fuzzy Weighted Influence Nonlinear Gauge System method extended with D numbers and MICMAC

The Weighted Influence Nonlinear Measurement System (WINGS) method originates from DEMATEL, which has the advantage of analyzing the interweaved determinants and the causal relationships within them. The innovation is mainly reflected in considering both the strength of the influencing factors themselves and the relationship of their mutual influence. To address the problems of ambiguity in assessing information and uncertainty in the judgment of expert group, this paper proposes fuzzy WINGS improved by D numbers (fuzzy D-WINGS). Combining D numbers with Triangular fuzzy numbers can overcome the limitation of mutually exclusive and collectively extensive set. The WINGS method is used to reveal the interdependent causal relationships by recognizing the orientation and strength of the factors. Utilizing the MICMAC method to draw matrix analysis diagrams can further reveal the relationship among them. Finally, a practical case study is conducted to prove the practicability of this fuzzy D-WINGS–MICMAC method.

Regional Leading Industry Selection Based on an Extended Fuzzy VIKOR Approach

To improve the deployment and optimization of the industrial structure, researchers and practitioners have performed a variety of researches in terms of regional leading industry selection based on AO Hirschman, Rostow and Miyohei’s principles. The criteria and methods employed in previous studies are mainly based on the mass industrial development data, leading to the limitation of study on the application in new high-tech district and underdeveloped regions. Due to lack of industrial data and detail industry information, it is difficult to employ the deterministic regional industry selection model. Therefore, an extended fuzzy-VIKOR approach that the expert-based and trapezoidal fuzzy number decision-making techniques, embedded into the VIKOR steps is proposed. It is developed to solve the regional leading industry selection problems concerning industrial, economic, social and environmental dimensions. Finally, a case study for the industrial planning of a high-tech zone is applied to verify the proposed decision-making approach.