A multi-product model for evaluating and selecting two layers of suppliers considering environmental factors

¹ Department of Industrial Engineering, University of Kurdistan, Sanandaj, Iran.
alireza.eydi@uok.ac.ir
² Masters student of Industrial Engineering, University of Kurdistan, Sanandaj, Iran.
baxtiarim70@yahoo.com

Received: 13 July 2016
Accepted: 20 October 2016

Abstract

New requirements and developments in the world of business and commerce era provide a background to the emergence of new attitudes which are essential for those involved in the field of production and trade. In this regard, there are new approaches and attitudes toward the subject matter of supply chain which is following an approach to a green chain via environmental requirements. In this study, not only the suppliers directly associated with the company, but also those providing raw materials for manufacturers were also considered in a second layer of supply chain, so as to select optimal suppliers from the both layers. Considering the first and second layers of suppliers as well as the green factor, a criteria called “second layer” was developed, with its associated fuzzy numbers been calculated using a proposed method, so as to rank suppliers on the first layer in hierarchical fuzzy TOPSIS method based on different levels of alpha. Finally, in order to assign orders to suppliers from the first and second layer, multi-objective linear programming was used to formulate various constraints such as size of each supplier on either the first or second layers as well as the capacity of the communication paths between suppliers on the first layer and the buyer, with respect to extenuating circumstances. In this paper, a multi-product model is proposed to solve multiple sourcing supplier problem in green supply chains considering environmental issues. The proposed model aims to maximize value of the suppliers while minimizing the costs associated with environmental pollutions, purchasing expenses, fixed ordering cost, transportation costs and penalties for returned goods. The solution method succeed to improve epsilon constraint in GAMS Software. The efficiency and applicability of the proposed approach is further illustrated with a case study in a washing machine manufacturing company.