A Novel Approach for Sustainable Supplier Selection Using Differential Evolution: A Case on Pulp and Paper Industry

Abstract

Abstract. Diverse sustainable supplier selection (SSS) methodologies have been suggested by the practitioners in earlier, to find a solution to the SSS problem. A SSS problem fundamentally is a multi-criteria practice. It is a judgment of tactical significance to enterprises. The nature of this decision usually is difficult and unstructured. Optimization practices might be useful tools for these types of decision-making difficulties. During last few years, Differential Evolution has arisen as a dominating tool used for solving a variety of problems arising in numerous fields. In the current study, we present an approach to find a solution to the SSS problem using Differential Evolution in pulp and paper industry. Hence this paper presents a novel approach is to practice Differential Evolution to select the efficient sustainable suppliers providing the maximum fulfillment for the sustainable criteria determined. Finally, an illustrative example on pulp and paper industry validates the application of the present approach.

An extended framework to evaluate sustainable suppliers in manufacturing companies using a new Pythagorean fuzzy entropy-SWARA-WASPAS decision-making approach

“…Bai and Sarkis (2010) applied a grey system and the rough set theory to incorporate sustainable supplier selection problem and have an effective decision-making process. Jauhar et al (2014) presented a model to effectively address the sustainable supplier selection problem based on satisfaction factors versus sustainable factors.…”

Application of multi-objective optimization based on genetic algorithm for sustainable strategic supplier selection under fuzzy environment

“…The manager needs to know which suppliers should be selected and how much of the quantity Y ij should be ordered considering the objectives. However, as to the supplier selection problem, it is hard to describe the cost and demand as known values because there is not sufficient data available to analyze, which usually cause uncertainty, imprecise or vague situation (Xu & Yan, 2011;Jauhar, Pant & Abraham, 2014;Khatie, Bulgak & Segovia, 2010;Lee, Kang, Hsu & Hung, 2009;Ordoobadi, 2009;Qiang, Hui & Xiao-Dong, 2013;Tako & Robinson, 2012;Alinezad, Seif & Esfandiari, 2013;Baskaran, Nachiappan & Rahman, 2012). Considering this situation, we use fuzzy variable to describe uncertain, imprecise or ambiguous information in the (SSSS) problem.…”

“…It does not require the sated information should be in form of gradient about the objective functions for optimization and it can also provide a number of possible solutions for solving the problem and the final decision depend on decision makers. From last three decades, it has been gained a significant success in providing smart solutions to several complicated optimization issues (Jauhar et al, 2014;Khatie et al, 2010). It belongs to stochastic search methodology that commonly used for the optimization of objectives for studying problems.…”

Sustainable Supplier Selection by a New Hybrid Support Vector-model based on the Cuckoo Optimization Algorithm

“…In Omurca's study [13], a hybridization of fuzzy c-means (FCM) and rough set theory (RST) procedures was reported as another answer for supplier selection, evaluation and development issue. Jauhar et al [14] intended to analyze the difficulties of sustainable supplier selection and proposed a differential evolutionbased approach for selecting sustainable suppliers in the pulp and paper industry. Jauhar and Pant [15] introduced the supplier contribution in the related activities of the SCM by using differential evolution (DE) to choose the effective practical supplier, giving the greatest satisfaction to the sustainable criteria decided.…”