A TODIM-Based Decision Support Framework for G-Resilient Supplier Selection in Fuzzy Environment

2016 ◽  
Vol 33 (05) ◽  
pp. 1650033 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
Siba Sankar Mahapatra
Keyword(s):  
Decision Support ◽  
Supplier Selection ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Selection Problems ◽  
Fuzzy Environment ◽  
Decision Support Framework ◽  
Application Potential

A novel decision support framework has been proposed herein to solve supplier selection problems by considering green as well as resiliency criteria, simultaneously. In this work subjectivity of evaluation criteria has been tackled by exploring fuzzy set theory. A dominance based approach has been conceptualized which is basically a simplified version of TODIM. Application potential of the proposed dominance based fuzzy decision making approach has been compared to that of fuzzy-TOPSIS, fuzzy-VIKOR and also fuzzy-TODIM. The concept of a unique performance index, i.e. “g-resilient” index has been introduced here to help in assessing suppliers’ performance and thereby selecting the best candidate. The work has also been extended to identify the areas in which suppliers are lagging; these seek further improvement towards g-resilient suppliers’ performance to be boosted up to the desired level.

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.

An integrated supplier selection approach incorporating decision maker’s risk attitude using ANN, AHP and TOPSIS methods

Kybernetes ◽  
2019 ◽  
Vol 49 (9) ◽  
pp. 2263-2284 ◽  
Author(s):  
Chunxia Yu ◽  
Zhiqin Zou ◽  
Yifan Shao ◽  
Fengli Zhang
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Evaluation Criteria ◽  
Risk Attitude ◽  
Integrated Approach ◽  
Fuzzy Topsis ◽  
Ann Model ◽  
Content Type ◽  
Selection Approach

Purpose The purpose of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the artificial neural network (ANN), analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods. Design/methodology/approach In the proposed approach, the ANN model is used to classify decision maker’s risk attitude; the fuzzy AHP method is used to determine the relative weights of evaluation criteria; and the fuzzy TOPSIS method is used to evaluate ratings of suppliers. Finally, experiments are conducted to verify the feasibility and efficiency of the proposed integrated approach. Findings Experiments results show that the proposed integrated approach is effective and efficient to help decision makers to select suitable suppliers according to their risk attitudes. Originality/value The aim of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the ANN, AHP and TOPSIS methods. The decision maker’s risk attitude toward procurement transaction is originally considered in supplier selection process.

scholarly journals Decision Support Framework for Cycling Investment Prioritization

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Draženko Glavić ◽  
Miloš N. Mladenović ◽  
Marina Milenković
Keyword(s):  
Sensitivity Analysis ◽  
Decision Support ◽  
Evaluation Criteria ◽  
Cost Benefit ◽  
Preference Ranking ◽  
Regulatory Constraints ◽  
User Attitudes ◽  
Decision Support Framework ◽  
Conflicting Objectives

Considering the significant potential for environmental, economic, social and health benefits from cycling, transport planners around the world are considering a wide variety of strategies for its promotion. However, cycling investments still have to find their place in a coherent package among other policies. Different constraints often imply a need for prioritization in cycling project implementation. The need for prioritization list of proposed investments can be caused by different factors such as available budget, available time, and regulatory constraints. Evaluation of investments in cycling infrastructure is a field of study that still requires further development, as previous research has mostly focused on questions of what to build and where. Previously used cost-benefit methods have substantive and procedural limitations in dealing with non-commensurable effects, and dealing with multiple conflicting objectives stemming from different stakeholders. On the contrary, development of prioritization list is formulated here as a semi-structured decision problem, thus belonging to the group of multi-criteria analysis (MCA) methods. The MCA methodology implemented in this decision-support framework is based on Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE). The expert-based decision-support framework includes procedures for defining list of evaluation criteria and their weights, scoring of alternatives, and sensitivity analysis. Presented decision-support framework is applied on six bicycle sections of the EuroVelo route 8 through Montenegro. Results provide a list of prioritized infrastructural investments, as well as list of criteria with weights, and sensitivity analysis. Decision-support framework is discussed in the context of further professionalizing of cycling planning, as well as short-term and long-term structuration of organization learning in the transition country context. Finally, this development opens up directions for further contextualization of decision criteria, and greater consideration of user attitudes in cycling promotion.

A two-phased fuzzy decision making procedure for IT supplier selection

2013 ◽  
Author(s):  
Fairuz Shohaimay ◽  
Nazirah Ramli ◽  
Siti Rosiah Mohamed ◽  
Ainun Hafizah Mohd
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision

Using fuzzy decision making for supplier selection in public procurement

2011 ◽  
Vol 11 (3) ◽  
pp. 403-427 ◽  
Author(s):  
Nicola Costantino ◽  
Mariagrazia Dotoli ◽  
Marco Falagario ◽  
Maria Pia Fanti
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Public Procurement ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision

Selecting the Most Appropriate Supplier in the Green Environment

2020 ◽  
pp. 101-124
Author(s):  
Muhittin Sagnak
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Analytic Network Process ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Strategic Decisions ◽  
Chain Management ◽  
Customer Expectations ◽  
Network Process ◽  
Fuzzy Analytic Network Process

Nowadays, supply chain management decisions have become strategic decisions. Also, greening process of supply chain activities were required due to satisfy the customer expectations, and protect the environmental life. Since one of the strategic decisions for supply chains is the supplier selection, greening process also became necessary for supplier evaluations. Within this context, in this chapter, a comprehensive list of the criteria for green supplier selection was determined. Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) method was applied to determine the cause-effect relationships between the main criteria. Fuzzy Analytic Network Process (ANP) method was used to find the relative weights of the criteria. Finally, fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method was applied to prioritize the various suppliers.

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