 Comparing different types of robust possibilistic programming approaches in designing closed-loop networksMona Bahrami, Mehdi Seifbarghy, Mohsen Hamidi and Farshad Faghihzade International Journal of Mathematics in Operational Research, 2023, vol. 25, issue 4, 463-491 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. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmore:v:25:y:2023:i:4:p:463-491 Access Statistics for this article More articles in International Journal of Mathematics in Operational Research from Inderscience Enterprises Ltd |
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