Optimization of Bulk Cargo Terminal Unloading and Outbound Operations Based on a Deep Reinforcement...
Optimization of Bulk Cargo Terminal Unloading and Outbound Operations Based on a Deep Reinforcement Learning Framework
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Publisher
Basel: MDPI AG
Journal title
Language
English
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Publisher
Basel: MDPI AG
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Scope and Contents
Contents
This study addresses the integrated scheduling problem of dry bulk cargo terminal yards, which includes three components: transportation planning, yard selection optimization, and equipment scheduling. Additionally, the research integrates safety considerations and addresses the complexities of dynamic transportation planning. This work presents tw...
Alternative Titles
Full title
Optimization of Bulk Cargo Terminal Unloading and Outbound Operations Based on a Deep Reinforcement Learning Framework
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Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_df8c63ac3980451499e636d431d397e5
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_df8c63ac3980451499e636d431d397e5
Other Identifiers
ISSN
2077-1312
E-ISSN
2077-1312
DOI
10.3390/jmse13010105
