A Hybrid MCDM Approach for Large Group Green Supplier Selection With Uncertain Linguistic Information

Mei-Yun Quan,Hua Shi,Hu-Chen Liu,Ze-Ling Wang

doi:10.1109/access.2018.2868374

Abstract

With increasing global concerns toward environmental protection and sustainable development, green supply chain management (GSCM) has drawn much attention from academicians and practitioners. Selecting an optimal green supplier is a critical part of GSCM, which can be viewed as a kind of multi-criteria decision making (MCDM) problem. To derive the best result, a large group of decision makers are often involved in the green supplier selection nowadays. Besides, decision makers tend to express their evaluations utilizing uncertain linguistic terms due to the vagueness of human thinking. Hence, this paper aims to propose a hybrid MCDM approach for green supplier selection within the large group setting. More concretely, interval-valued intuitionistic uncertain linguistic sets are applied for assessing the performance of green suppliers concerning each criterion. Ant colony algorithm is utilized to cluster decision makers into several subgroups. The linear programming technique for multidimensional analysis of preference is adopted for the determination of the optimal weights of criteria objectively. Finally, an extended MULTIMOORA approach is utilized to generate the ranking of alternative suppliers. The practicality and usefulness of the developed large group green supplier selection framework is illustrated using an empirical example of a real estate company.

Highlights

Because of growing public concerns over the environmental issues and government regulations toward sustainable development, green supply chain management (GSCM) has become popular in production operation management of modern enterprises [1]
We propose a hybrid multi-criteria decision making (MCDM) model based on interval-valued intuitionistic uncertain linguistic sets (IVIULSs) and MULTIMOORA method in this paper for evaluating and ranking green suppliers under large group environment
Decision makers are clustered by employing an ant colony algorithm; assessment values of clusters are aggregated by the IVIULWA operator; criteria weights are computed by the LINMAP method; the alternative suppliers are ranked based on a modified MULTIMOORA approach

Summary

INTRODUCTION

Because of growing public concerns over the environmental issues and government regulations toward sustainable development, green supply chain management (GSCM) has become popular in production operation management of modern enterprises [1]. Quan et al.: Hybrid MCDM Approach for Large Group Green Supplier Selection With Uncertain Linguistic Information supplier selection process due to the increasing complexity of the problem. We propose a hybrid MCDM model based on IVIULSs and MULTIMOORA method in this paper for evaluating and ranking green suppliers under large group environment. We utilize ant colony algorithm to cluster decision makers, an extended LINMAP approach to calculate the objective weights of criteria, and an improved MULTIMOORA technique to rank alternative green suppliers. The presented large group green supplier selection approach is able to reflect the vagueness and ambiguity of decision makers’ judgements and acquire an accurate ranking result of green suppliers. Methods of green supplier estimation and selection can be seen in [31] and [32]

APPLICATIONS OF MULTIMOORA METHOD

THE PROPOSED GREEN SUPPLIER SELECTION MODEL

AGGREGATE CLUSTERS

RANK THE ALTERNATIVE SUPPLIERS

CONCLUSIONS