Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation
Due to environmental concerns, firms are under increasing pressure to comply with legislations and to take up environmental strategies. This leads researchers and firms to develop new sustainable supply chains, where a new area has emerged for a manufacturing and reconditioning system. The originali...
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MDPI AG
2020-05-01
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Series: | Applied Sciences |
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Online Access: | https://www.mdpi.com/2076-3417/10/10/3534 |
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author | Sadok Turki Soulayma Sahraoui Christophe Sauvey Nathalie Sauer |
author_facet | Sadok Turki Soulayma Sahraoui Christophe Sauvey Nathalie Sauer |
author_sort | Sadok Turki |
collection | DOAJ |
description | Due to environmental concerns, firms are under increasing pressure to comply with legislations and to take up environmental strategies. This leads researchers and firms to develop new sustainable supply chains, where a new area has emerged for a manufacturing and reconditioning system. The originality of this work consists in simultaneously considering carbon emissions strategies, carbon tax and mandatory emission in a manufacturing-reconditioning system. The proposed system is composed of two parallel machines, a manufacturing stock, a reconditioning stock and a recovery inventory. In order to make the proposed green manufacturing system more realistic, it is assumed that manufactured (new products) and reconditioned products are distinguishable. The quantity of worn products (used products) depends on the sales in the previous periods, and the repair periods of the machines are stochastic and independent. The aim of this work is to determine the optimal capacities of manufacturing and reconditioning stocks that maximize the total profit, as well as the optimal value of worn products under two carbon emissions’ limitations. An evolutionary algorithm is developed, along with an efficient improvement method, to find the optimal value of decision variables. Ultimately, numerical results are provided to show the impact of the period of carbon limit and the worn products (returned products) on decision variables. |
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id | doaj.art-841b50b5d1e247119f2393d81ffcf6ba |
institution | Directory Open Access Journal |
issn | 2076-3417 |
language | English |
last_indexed | 2024-03-10T19:42:54Z |
publishDate | 2020-05-01 |
publisher | MDPI AG |
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series | Applied Sciences |
spelling | doaj.art-841b50b5d1e247119f2393d81ffcf6ba2023-11-20T01:05:04ZengMDPI AGApplied Sciences2076-34172020-05-011010353410.3390/app10103534Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon RegulationSadok Turki0Soulayma Sahraoui1Christophe Sauvey2Nathalie Sauer3Laboratory of Informatics Engineering and Production of Metz (LGIPM), University of Lorraine, LGIPM, UFR MIM, 3 Rue Augustin Fresnel, F-57070 Metz, FranceLaboratory of Informatics Engineering and Production of Metz (LGIPM), University of Lorraine, LGIPM, UFR MIM, 3 Rue Augustin Fresnel, F-57070 Metz, FranceLaboratory of Informatics Engineering and Production of Metz (LGIPM), University of Lorraine, LGIPM, UFR MIM, 3 Rue Augustin Fresnel, F-57070 Metz, FranceLaboratory of Informatics Engineering and Production of Metz (LGIPM), University of Lorraine, LGIPM, UFR MIM, 3 Rue Augustin Fresnel, F-57070 Metz, FranceDue to environmental concerns, firms are under increasing pressure to comply with legislations and to take up environmental strategies. This leads researchers and firms to develop new sustainable supply chains, where a new area has emerged for a manufacturing and reconditioning system. The originality of this work consists in simultaneously considering carbon emissions strategies, carbon tax and mandatory emission in a manufacturing-reconditioning system. The proposed system is composed of two parallel machines, a manufacturing stock, a reconditioning stock and a recovery inventory. In order to make the proposed green manufacturing system more realistic, it is assumed that manufactured (new products) and reconditioned products are distinguishable. The quantity of worn products (used products) depends on the sales in the previous periods, and the repair periods of the machines are stochastic and independent. The aim of this work is to determine the optimal capacities of manufacturing and reconditioning stocks that maximize the total profit, as well as the optimal value of worn products under two carbon emissions’ limitations. An evolutionary algorithm is developed, along with an efficient improvement method, to find the optimal value of decision variables. Ultimately, numerical results are provided to show the impact of the period of carbon limit and the worn products (returned products) on decision variables.https://www.mdpi.com/2076-3417/10/10/3534production planningcarbon regulationreconditioninggreen logisticsoptimization |
spellingShingle | Sadok Turki Soulayma Sahraoui Christophe Sauvey Nathalie Sauer Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation Applied Sciences production planning carbon regulation reconditioning green logistics optimization |
title | Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation |
title_full | Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation |
title_fullStr | Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation |
title_full_unstemmed | Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation |
title_short | Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation |
title_sort | optimal manufacturing reconditioning decisions in a reverse logistic system under periodic mandatory carbon regulation |
topic | production planning carbon regulation reconditioning green logistics optimization |
url | https://www.mdpi.com/2076-3417/10/10/3534 |
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