Title: Bi-objective optimisation model with societal constraints for green closed loop supply chain network - a case of battery industry

Authors: S. Umar Sherif; P. Sasikumar; P. Asokan; J. Jerald

Addresses: Department of Production Engineering, National Institute of Technology, Tiruchirappalli, 620015, Tamil Nadu, India ' Department of Industrial Engineering Technology, Abu Dhabi Women's Campus, Higher Colleges of Technology, UAE ' Department of Production Engineering, National Institute of Technology, Tiruchirappalli, 620015, Tamil Nadu, India ' Department of Production Engineering, National Institute of Technology, Tiruchirappalli, 620015, Tamil Nadu, India

Abstract: Scrap-battery collection, recovery and new-battery production activities in the battery industries have increased a large quantity of materials and products distribution between the facilities. This situation leads to the sustainability issue in terms of higher transportation cost, greenhouse gas (GHG) emission and drivers fatigue (long driving). In order to address the sustainable issues, the present closed loop supply chain network (CLSCN) is customised. The objective of this paper is to develop bi-objective multi product multi echelon multi period green CLSCN model with societal constraints (GCLSCN-SC) to minimise: 1) the sum of distribution centres' (DC) storage capacity expansion cost and transportation cost; 2) the GHG emission (CO₂ and NO_x). The storage capacity expansion strategy and the transportation strategy are established in the proposed model to stimulate the bi-directional flow of the products and materials between facilities and the model is solved by using GAMS-23.5. The performance of proposed model has been compared with the present model and the evaluation demonstrates that the proposed model is efficient. The analysed results of the proposed model under different scenarios are presented in this paper.

Keywords: green closed loop supply chain network; battery industry; societal issues; bidirectional flow; capacity expansion; GHG emission.

DOI: 10.1504/IJPQM.2019.101518

International Journal of Productivity and Quality Management, 2019 Vol.27 No.3, pp.276 - 304

Received: 28 Feb 2018
Accepted: 17 May 2018
Published online: 11 Aug 2019 *

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