期刊
COMPUTERS & CHEMICAL ENGINEERING
卷 112, 期 -, 页码 211-238出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2018.02.011
关键词
Mathematical modeling; Uncertainty; Product design; Closed-loop supply chain; Stochastic approach
资金
- CONICET [PIP 112 20150100641]
- Universidad Nacional del Litoral under Grant CAI+D [500 201101 00024 LI]
The shortage of natural resources, the need to take into account societal considerations, the emergence of new government regulations and the necessity to maintain and/or improve the economic benefit of the supply chain, have created a growing awareness on academia as well as industries towards the development of closed-loop supply chains (CLSCs), where explicitly products' life-cycles are accounted for. Concentrating on the problems of the product and network design for a multi-product, multi-echelon and multi-period CLSC, in this work a two-stage stochastic mixed integer linear model incorporating uncertainty on the quality and quantity of the return flows is proposed. In addition, risk management related to critical uncertain parameters is performed, where a conditional value at risk (CVaR) concept is applied to supply chain profits. The formulation considers decisions associated with the network design and, simultaneously, with the products to manufacture (new and remanufactured) and their associated raw materials (new and recovered). A network superstructure is considered accounting for two types of customers (first and second markets), raw material suppliers, factories, distribution centers, customer demands, recovery centers, recycle centers, final disposal locations and re-distribution centers. Optimal solutions with high economic and environmental benefits are obtained where the advantages of using the proposed approach are shown. A case study from a European consumer goods company is explored. (C) 2018 Elsevier Ltd. All rights reserved.
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