Simulation-Based Optimization on Control Strategies of Three-Echelon Inventory in Hybrid Supply Chain With Order Uncertainty Article Swipe
Wendan Zhao
,
Dingwei Wang
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1109/access.2018.2870856
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1109/access.2018.2870856
Multi-echelon inventory control is the main form of the management of supply chain inventory, and it has been paid extensive attention by scholars because of its importance in supply chain management. Process industries, represented by metallurgy, petrochemical and pharmaceutical industry, have typical characteristics such as high investment, high costs, and high resource utilization, they play a key role in industrialization. In this paper, the simulation model of a multiproduct three-echelon inventory control system is established for the hybrid supply chain of the process industry. Based on the idea of control engineering, a feedback control law is designed for inventory control. Several mixed inventory control strategies were applied to the model. The proportional plus integral control algorithm is used to modify the inventory control strategies. Based on this simulation model, a simulation-based optimization method is applied to the three-echelon inventory control system. The results show that the reciprocal of total entropy ratio and customer satisfaction are optimized by the mixed inventory control strategies when the hybrid supply chain is affected by order uncertainty.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2018.2870856
- OA Status
- gold
- Cited By
- 19
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2891323087
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2891323087Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/access.2018.2870856Digital Object Identifier
- Title
-
Simulation-Based Optimization on Control Strategies of Three-Echelon Inventory in Hybrid Supply Chain With Order UncertaintyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-01-01Full publication date if available
- Authors
-
Wendan Zhao, Dingwei WangList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2018.2870856Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1109/access.2018.2870856Direct OA link when available
- Concepts
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Supply chain, Inventory theory, Inventory control, Control (management), Computer science, Simulation-based optimization, Process control, Operations research, Process (computing), Business, Engineering, Marketing, Machine learning, Artificial intelligence, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
19Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 2, 2022: 4, 2021: 4, 2020: 4Per-year citation counts (last 5 years)
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43Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.when | 162 |
| abstract_inverted_index.Based | 84, 124 |
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| abstract_inverted_index.mixed | 101, 158 |
| abstract_inverted_index.model | 65 |
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| abstract_inverted_index.model, | 128 |
| abstract_inverted_index.model. | 109 |
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| abstract_inverted_index.Process | 31 |
| abstract_inverted_index.Several | 100 |
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| abstract_inverted_index.results | 142 |
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| abstract_inverted_index.industry. | 83 |
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| abstract_inverted_index.three-echelon | 69, 137 |
| abstract_inverted_index.pharmaceutical | 38 |
| abstract_inverted_index.characteristics | 42 |
| abstract_inverted_index.simulation-based | 130 |
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| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.49000000953674316 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.9232704 |
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| citation_normalized_percentile.is_in_top_10_percent | True |