Evaluation and selection strategy for green supply chain using interval-valued q-rung orthopair fuzzy combinative distance-based assessment

Environment, Development and Sustainability - Environmental deterioration and global warming has created a substantial impact on international companies to incorporate eco-friendly, green supply...     

Eco-material selection using fuzzy TOPSIS method

In the classical multiple attribute decision-making or MADM methods, the ratings and the weights of the criteria are known precisely. However, in eco-material selection exercises, the available data are typically inadequate because of the selection dual quantitative and qualitative natures. Some of the qualitative selection criteria can be rated in several classes rather being expressed by exact numerical values; hence the application of fuzzy concepts in decision-making seems attractive to deal with such kind of ratings. Thusly, the presented study attempts to propose an eco-material selection approach specific to the automobile body panels using a fuzzy technique for order preference by similarity to ideal solution (TOPSIS), to incorporate both numerical and rating-based criteria into one holistic sustainability model. TOPSIS and fuzzy logic can aid the material selection process in translating the design goals and parameters into usable numbers that in turn can be used to rank candidate materials in their closeness to the ideal solution. An additional uniqueness of this study stems from using the fuzzy-TOPSIS as a scoring tool without any assigned weights for the different selection attributes, in order to avoid the bias that is typically associated with other classical MADM, such as quality function deployment, analytical hierarchy process and digital logic.     

Dominance based fuzzy decision support framework for g-resilient (ecosilient) supplier selection: an empirical modelling

A novel decision support framework has been proposed herein to solve supplier selection problems by considering green as well as resiliency criteria, simultaneously. An expert team involving a finite number of Decision-Makers (DMs) is to be employed to obtain degree of importance of each of the evaluation criteria and also to assign an appropriate rating for each supplier alternative with respect to the criteria. Since subjective human judgment often bears some sort of ambiguity as well as vagueness, application of fuzzy set theory can be recommended in this context. The present work represents a dominance based decision support system in the light of fuzzy set theory which is basically a simplified version of TODIM and PROMETHEE. It explores dominance between two alternatives with respect to a particular criterion, based on which a global dominance measure is computed to facilitate ranking order of candidate suppliers. The approach proposed in this research seems straightforward which can exclude complex and tedious computational steps of TODIM as well as PROMETHEE. Application potential of the proposed dominance based fuzzy decision-making approach has been compared to that of Fuzzy-TOPSIS and Fuzzy-VIKOR. Good agreement has been observed. In addition to this, the concept of a unique performance index i.e. ‘g-resilient’ (also called ‘ecosilient’) index has been introduced to help in assessing suppliers’ overall performance extent. The work has also been extended to identify the ill (poor)-performing areas in which suppliers are lagging and seek further improvement towards enhancing g-resilient performance level.     

Sustainable supplier selection criteria classification for Indian iron and steel industry: a fuzzy modified Kano model approach

ABSTRACT

The aim of this work is to provide a systematic approach for sustainability criteria clustering into different useful categories. For this purpose, a methodology has been proposed with the following three steps. (i) A comprehensive set of the sustainability criteria in economic, environmental and social dimension has been extracted from the literature and have been customised for the iron and steel industry. (ii) A fuzzy Kano methodology has been used to classify these sustainability criteria into useful Kano cluster like must-be, one-dimensional, and attractive cluster (iii) further, must-be and attractive criteria derived from the second step were further sub-classified into three categories using Type IV Kano model. All steps have been examined in the iron and steel industry of India and findings indicate that quality and delivery criteria are classified as high must be criteria in the economic realm. Further, environmental and energy management system in the environmental dimension and social responsibility and right of stakeholders criteria in the social dimension are classified as high must be criteria. Prioritising must be and attractive criteria enable decision makers of other industries to select the appropriate criteria to adopt sustainability.     

Green supplier selection generic framework: a multi-attribute utility theory approach

This paper presents a generic framework integrating environmental and social criteria leading to a comprehensive selection process of green suppliers. Traditionally, price, quality, lead time and flexibility are considered for the supplier selection. With the increase in awareness of environmental and social responsibility issues, many companies are tending towards adopting green concepts and sourcing green suppliers. This study proposes a framework consisting of environmental (E), green (G) and organisational (O) factors that are required for the green supplier selection process. These factors are further classified as criteria for which attributes are presented. A hierarchy is constructed to facilitate in evaluating the importance of the selected criteria and alternatives of green suppliers. To cater to the multi-criteria decision-making approach with both quantitative and qualitative attributes, we applied the multiple attribute utility theory, which is a decision support that helps managers formulating viable sourcing strategies. A hypothetical example is presented to illustrate the applicability of the approach.     

Resilient and sustainable supplier selection via a new framework: a case study from the steel industry

Environment, Development and Sustainability - This study addresses the problem of selecting a supplier bound by sustainability and resilience criteria, focusing on the steel industry as a case in...     

Sustainable supplier selection for the cold supply chain (CSC) in the context of a developing country

Cold supply chain (CSC) is a process that involves temperature-controlled activities ranging from the acquisition of raw materials and down to the end consumers. A sustainable cold chain supplier is the one that incorporates sustainable practices in its complete cycle of operations. This is to ensure keeping the products from going to waste, especially in the case of a developing country. To identify the driving factors towards the sustainable cold chain supplier, this study utilizes the interpretive structural modelling (ISM) approach in the first phase. Fifteen various sustainability factors were analyzed and the “utilization of renewable resources” factor concluded to be the most important driving factor. By implementing renewable resources, a supplier can be able to convert its manufacturing processes and services to sustainable assets. The second phase of this study conducts the selection of cold chain suppliers in the context of Pakistan. For this purpose, fuzzy VIKOR, a multi-criteria decision-making (MCDM) technique is incorporated to analyze eight suppliers based on fifteen distinct criteria. The results concluded Mitchell foods to be the most economically, environmentally and socially sustainable suppliers in the context of Pakistan. This study recommends providing business-friendly incentives to suppliers like Mitchells and new investors who tend to keep their operations sustainable by adopting renewable resources. Furthermore, the relaxation of taxes and creating job employability by working with sustainable suppliers can contribute positively towards economic growth and the overall society. The study holds novelty in the area of cold chain supplier selection for Pakistan by utilizing a novel approach in the form of ISM and fuzzy VIKOR techniques, thus forming a major application of this research study.

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Developing a multi-criteria sustainable credit score system using fuzzy BWM and fuzzy TOPSIS

Environment, Development and Sustainability - Sustainability has emerged as a dominating paradigm across global institutions as a critical component for their prospects. Organisations all across...     

Decision support model to select crop pattern for sustainable agricultural practices using fuzzy MCDM

The crop pattern has a significant impact on the feasibility of sustainable agricultural practices. Selected crop pattern influences environmental and economic condition and affects sustainability profoundly in agricultural practices. Hence, a careful intervention is required in the selection of an optimal crop pattern for sustainable agricultural practices. Selection of a particular set of crop pattern depends on many criteria that may vary from place to place thus pose challenges in deciding an optimum crop pattern. The present research focuses on the crop selection pattern in Indian environment that considers comprehensive criteria related to sustainable farming practices. Based on the in-depth review of the literature and experts opinion, comprehensive criteria related to sustainable farming practices for Ravi season crop are identified. Total twelve criteria covering socioeconomic conditions, soil and water conditions, environmental and climatic conditions are earmarked and taken into account for eight most commonly grown crops in Ravi season and later on modeled to determine the crop pattern for most needed sustainability. A fuzzy-based multi-criteria decision-making model has been developed considering the Indian farming system. The scarce resources availability to Indian farmers poses many challenges to practice farming with most needed sustainability. The present research will be useful in the area of Indian farming practices in particular and global farming practices in general. It will also help stakeholders in their cost effective decision making for better crop productivity leading to sustainable farming practices. Additionally, the state policy makers will be able to formulate effective state driven sustainable farming policy to enhance its stake in gross domestic product to become self-reliance.     

Performance evaluation of lean sustainable systems using adaptive neuro fuzzy inference system: a case study

The modern manufacturing organisations have been adopting both lean and sustainable manufacturing paradigms to survive in the competitive environment. Lean and sustainable strategies aim at achieving productivity improvement by streamlined processes and waste elimination. The performance of such integrated lean sustainable system has to be assessed to ensure whether the strategic objectives are in line with customer value and to identify improvement opportunities that enable and enhance the competitive advantage of an integrated lean sustainable system. This paper presents the formulation of conceptual performance evaluation model to assess lean sustainable systems. Appropriate performance indicators have been identified and adaptive neuro fuzzy inference system approach is used to evaluate lean sustainability. A case of automotive component manufacturing firm in Indian scenario is exemplified. Based on the evaluation, lean sustainability index was computed and the firm was found to be ‘Averagely Lean Sustainable’. Further improvement actions to enhance the lean sustainable performance were planned and implemented. The developed performance evaluation model is capable of effectively evaluating the lean sustainable performance of manufacturing firms and has more practical relevance.     

Evaluation and selection of healthcare waste incinerators using extended sustainability criteria and multi-criteria analysis methods

Environment, Development and Sustainability - Disposal of healthcare waste is a key issue of environmental sustainability in the world. The amount of healthcare waste is increasing every day, and...     

An approach for environmental risk assessment of engineered nanomaterials using Analytical Hierarchy Process (AHP) and fuzzy inference rules

The usage of Engineered Nanoparticles (ENPs) in consumer products is relatively new and there is a need to conduct environmental risk assessment (ERA) to evaluate their impacts on the environment. However, alternative approaches are required for ERA of ENPs because of the huge gap in data and knowledge compared to conventional pollutants and their unique properties that make it difficult to apply existing approaches. This study aims to propose an ERA approach for ENPs by integrating Analytical Hierarchy Process (AHP) and fuzzy inference models which provide a systematic evaluation of risk factors and reducing uncertainty about the data and information, respectively. Risk is assumed to be the combination of occurrence likelihood, exposure potential and toxic effects in the environment. A hierarchy was established to evaluate the sub factors of these components. Evaluation was made with fuzzy numbers to reduce uncertainty and incorporate the expert judgements. Overall score of each component was combined with fuzzy inference rules by using expert judgements. Proposed approach reports the risk class and its membership degree such as Minor (0.7). Therefore, results are precise and helpful to determine the risk management strategies. Moreover, priority weights calculated by comparing the risk factors based on their importance for the risk enable users to understand which factor is effective on the risk. Proposed approach was applied for Ag (two nanoparticles with different coating) and TiO₂ nanoparticles for different case studies. Results verified the proposed benefits of the approach.     

Sustainable design of the household water treatment systems using a novel integrated fuzzy QFD and LINMAP approach: a case study of Iran

Environment, Development and Sustainability - There is a high possibility that pursuit of water policies goals which could have impacts on water security. Decision makers are interested in...     

Delineation of groundwater potentials of Sfax region,Tunisia, using fuzzy analytical hierarchy process,frequency ratio,and weights of evidence models

Environment, Development and Sustainability - Groundwater in semiarid regions is of extreme importance due to limited water resources and increasing population demand. Hence, a better knowledge of...