Designing a Reverse Logistics Network for End-of-Life Vehicles in an Uncertain Environment Article Swipe
Meiling He
,
Qipeng Li
,
Tianhe Lin
,
Jiangyang Fan
,
Xiaohui Wu
,
Xun Han
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/wevj15040140
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/wevj15040140
The strategic development of reverse logistics networks is crucial for addressing the common challenge of low recovery rates for end-of-life vehicles (ELVs) in China. To minimize the total cost of the reverse logistics network for ELVs, this paper proposes a mixed-integer linear programming (MILP) model. The model considers the recycling volume of different vehicle types, facility processing capacity, and the proportions of parts and materials. Building on this foundation, a fuzzy mixed-integer nonlinear programming (FMINLP) model is developed to account for the inherent uncertainty associated with recycling volumes and facility processing capacities. The model was solved using Lingo, and its effectiveness was validated using Jiangsu Province of China as a case study, followed by a sensitivity analysis. The results indicate that dismantling and machining centers incur the highest processing costs. Variations in recycling volume and facility handling capacity significantly impact total costs and site selection, with the former having a more pronounced effect. Increasing facility processing capacity effectively increases the recovery rate. Moreover, a higher confidence level corresponds to higher total costs and a greater demand for facilities.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/wevj15040140
- https://www.mdpi.com/2032-6653/15/4/140/pdf?version=1711705295
- OA Status
- gold
- Cited By
- 5
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4393308496
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4393308496Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/wevj15040140Digital Object Identifier
- Title
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Designing a Reverse Logistics Network for End-of-Life Vehicles in an Uncertain EnvironmentWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-03-29Full publication date if available
- Authors
-
Meiling He, Qipeng Li, Tianhe Lin, Jiangyang Fan, Xiaohui Wu, Xun HanList of authors in order
- Landing page
-
https://doi.org/10.3390/wevj15040140Publisher landing page
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https://www.mdpi.com/2032-6653/15/4/140/pdf?version=1711705295Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2032-6653/15/4/140/pdf?version=1711705295Direct OA link when available
- Concepts
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Reverse logistics, Business, Computer science, Manufacturing engineering, Transport engineering, Engineering, Supply chain, MarketingTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
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2025: 3, 2024: 2Per-year citation counts (last 5 years)
- References (count)
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52Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W122429625, https://openalex.org/W2136865410, https://openalex.org/W2041077582, https://openalex.org/W2036956232, https://openalex.org/W3163953711, https://openalex.org/W6675302507, https://openalex.org/W2026063805, https://openalex.org/W1979422419, https://openalex.org/W2566850286, https://openalex.org/W2552224707, https://openalex.org/W2331555905, https://openalex.org/W3097474349, https://openalex.org/W2090682341, https://openalex.org/W2944490796, https://openalex.org/W2909909131, https://openalex.org/W2904728861, https://openalex.org/W2036295094, https://openalex.org/W1993794811, https://openalex.org/W1976262218, https://openalex.org/W2021558351, https://openalex.org/W2321000906, https://openalex.org/W2890422014, https://openalex.org/W2617272365, https://openalex.org/W3033942892, https://openalex.org/W3148828588, https://openalex.org/W3193773163, https://openalex.org/W3181017229, https://openalex.org/W4301586875, https://openalex.org/W4220972851, https://openalex.org/W4319315710, https://openalex.org/W2069051348, https://openalex.org/W1966737366, https://openalex.org/W2342514950, https://openalex.org/W2282854823, https://openalex.org/W2291374026, https://openalex.org/W2346033674, https://openalex.org/W2087166465, https://openalex.org/W2220579252, https://openalex.org/W2538613596, https://openalex.org/W4242406798, https://openalex.org/W2791515286, https://openalex.org/W4285300941, https://openalex.org/W2922141454, https://openalex.org/W4293417802, https://openalex.org/W4362729087, https://openalex.org/W4295117873, https://openalex.org/W6654827835, https://openalex.org/W2982254759, https://openalex.org/W3033914165, https://openalex.org/W4283716732, https://openalex.org/W2100010517, https://openalex.org/W2018033885 |
| referenced_works_count | 52 |
| abstract_inverted_index.a | 39, 69, 109, 114, 149, 163, 173 |
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| abstract_inverted_index.as | 108 |
| abstract_inverted_index.by | 113 |
| abstract_inverted_index.in | 22, 131 |
| abstract_inverted_index.is | 7, 76 |
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| abstract_inverted_index.on | 66 |
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| abstract_inverted_index.The | 0, 45, 92, 117 |
| abstract_inverted_index.and | 58, 63, 88, 98, 122, 134, 142, 172 |
| abstract_inverted_index.for | 9, 18, 34, 80, 176 |
| abstract_inverted_index.its | 99 |
| abstract_inverted_index.low | 15 |
| abstract_inverted_index.the | 11, 26, 30, 48, 59, 81, 126, 146, 159 |
| abstract_inverted_index.was | 94, 101 |
| abstract_inverted_index.case | 110 |
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| abstract_inverted_index.more | 150 |
| abstract_inverted_index.site | 143 |
| abstract_inverted_index.that | 120 |
| abstract_inverted_index.this | 36, 67 |
| abstract_inverted_index.with | 85, 145 |
| abstract_inverted_index.China | 107 |
| abstract_inverted_index.ELVs, | 35 |
| abstract_inverted_index.costs | 141, 171 |
| abstract_inverted_index.fuzzy | 70 |
| abstract_inverted_index.incur | 125 |
| abstract_inverted_index.level | 166 |
| abstract_inverted_index.model | 46, 75, 93 |
| abstract_inverted_index.paper | 37 |
| abstract_inverted_index.parts | 62 |
| abstract_inverted_index.rate. | 161 |
| abstract_inverted_index.rates | 17 |
| abstract_inverted_index.total | 27, 140, 170 |
| abstract_inverted_index.using | 96, 103 |
| abstract_inverted_index.(ELVs) | 21 |
| abstract_inverted_index.(MILP) | 43 |
| abstract_inverted_index.China. | 23 |
| abstract_inverted_index.Lingo, | 97 |
| abstract_inverted_index.common | 12 |
| abstract_inverted_index.costs. | 129 |
| abstract_inverted_index.demand | 175 |
| abstract_inverted_index.former | 147 |
| abstract_inverted_index.having | 148 |
| abstract_inverted_index.higher | 164, 169 |
| abstract_inverted_index.impact | 139 |
| abstract_inverted_index.linear | 41 |
| abstract_inverted_index.model. | 44 |
| abstract_inverted_index.solved | 95 |
| abstract_inverted_index.study, | 111 |
| abstract_inverted_index.types, | 54 |
| abstract_inverted_index.volume | 50, 133 |
| abstract_inverted_index.Jiangsu | 104 |
| abstract_inverted_index.account | 79 |
| abstract_inverted_index.centers | 124 |
| abstract_inverted_index.crucial | 8 |
| abstract_inverted_index.effect. | 152 |
| abstract_inverted_index.greater | 174 |
| abstract_inverted_index.highest | 127 |
| abstract_inverted_index.network | 33 |
| abstract_inverted_index.results | 118 |
| abstract_inverted_index.reverse | 4, 31 |
| abstract_inverted_index.vehicle | 53 |
| abstract_inverted_index.volumes | 87 |
| abstract_inverted_index.(FMINLP) | 74 |
| abstract_inverted_index.Building | 65 |
| abstract_inverted_index.Province | 105 |
| abstract_inverted_index.capacity | 137, 156 |
| abstract_inverted_index.facility | 55, 89, 135, 154 |
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| abstract_inverted_index.handling | 136 |
| abstract_inverted_index.indicate | 119 |
| abstract_inverted_index.inherent | 82 |
| abstract_inverted_index.minimize | 25 |
| abstract_inverted_index.networks | 6 |
| abstract_inverted_index.proposes | 38 |
| abstract_inverted_index.recovery | 16, 160 |
| abstract_inverted_index.vehicles | 20 |
| abstract_inverted_index.Moreover, | 162 |
| abstract_inverted_index.analysis. | 116 |
| abstract_inverted_index.capacity, | 57 |
| abstract_inverted_index.challenge | 13 |
| abstract_inverted_index.considers | 47 |
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| abstract_inverted_index.logistics | 5, 32 |
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| abstract_inverted_index.nonlinear | 72 |
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| abstract_inverted_index.foundation, | 68 |
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| abstract_inverted_index.uncertainty | 83 |
| abstract_inverted_index.effectiveness | 100 |
| abstract_inverted_index.mixed-integer | 40, 71 |
| abstract_inverted_index.significantly | 138 |
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| corresponding_author_ids | https://openalex.org/A5101175335 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I4210139481 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/12 |
| sustainable_development_goals[0].score | 0.44999998807907104 |
| sustainable_development_goals[0].display_name | Responsible consumption and production |
| citation_normalized_percentile.value | 0.83939569 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |