Title: Comparing different types of robust possibilistic programming approaches in designing closed-loop networks

Authors: Mona Bahrami; Mehdi Seifbarghy; Mohsen Hamidi; Farshad Faghihzade

Addresses: Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran ' Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran ' Department of Strategic Management and Operations, Woodbury School of Business, Utah Valley University, 800 W University Pkwy, Orem, UT 84058, USA ' Industrial Engineering Department, Isfahan University of Technology, Isfahan, Iran

Abstract: This paper introduces a multi-objective, multi-product, and multi-period closed-loop supply chain network model with uncertainty. The network includes suppliers, plants, distribution centres, hybrid processing centres, and customers in its forward chain while in the backward chain; it is composed of customers, collection centres, disposal centres, hybrid processing centres, and plants. The problem has three objectives for optimising profit: delivery time, and quality. With these three objectives, the model creates a balance between customer satisfaction and business profitability. The model also considers the impact of average useful life of products on their return. We use several types of robust possibilistic approaches and multi-choice goal programming to tackle uncertainty and the multi-objective nature of the problem. The model is applicable in a variety of businesses such as automobile, electrical, and electronic industries.

Keywords: supply chain planning; robust possibilistic programming; RPP; multi-choice goal programming; uncertainty; closed-loop networks.

DOI: 10.1504/IJMOR.2023.132835

International Journal of Mathematics in Operational Research, 2023 Vol.25 No.4, pp.463 - 491

Received: 29 Nov 2021
Accepted: 03 Jun 2022
Published online: 11 Aug 2023 *

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