Contemporary challenges and AI solutions in port operations: applying Gale–Shapley algorithm to find best matches
Abstract Artificial intelligence (AI) developments enable human capability to deliver the same outcome at a lower cost. This research performs a high-level matching between AI solutions and challenges within the port area by developing a novel academic approach. This way, the matching is carried out...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2023-09-01
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| Series: | Journal of Shipping and Trade |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s41072-023-00155-8 |
| _version_ | 1827635593434103808 |
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| author | Mehran Farzadmehr Valentin Carlan Thierry Vanelslander |
| author_facet | Mehran Farzadmehr Valentin Carlan Thierry Vanelslander |
| author_sort | Mehran Farzadmehr |
| collection | DOAJ |
| description | Abstract Artificial intelligence (AI) developments enable human capability to deliver the same outcome at a lower cost. This research performs a high-level matching between AI solutions and challenges within the port area by developing a novel academic approach. This way, the matching is carried out more structured than when one (manager, developer, challenge owner, etc.) fulfils it based on their opinion without following any structured approach. Therefore, the study defines first a comprehensive typology of port stakeholders' challenges, which can be solved via AI solutions. This typology presents challenges, including their main issues, widespread impact, and potential solutions. A state-of-the-art review of AI solutions that can address these challenges is carried out in parallel. Secondly, this review clearly distinguishes between AI solutions based on their technology and functionality. Thirdly, this research selects an appropriate AI solution for addressing each identified challenge in the port operation by upgrading the Gale–Shapley algorithm. Finally, it shows that the most critical presented AI solutions in this study use various machine learning (ML) techniques. Besides, concerning the AI solution's reusability feature and the result of high-level matching, this research shows that the implementation phase effort can be drastically reduced by using the recently developed matching algorithm. |
| first_indexed | 2024-03-09T15:29:45Z |
| format | Article |
| id | doaj.art-ef0a711e0deb42ea91ec8ea74f3bb1e6 |
| institution | Directory Open Access Journal |
| issn | 2364-4575 |
| language | English |
| last_indexed | 2024-03-09T15:29:45Z |
| publishDate | 2023-09-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Shipping and Trade |
| spelling | doaj.art-ef0a711e0deb42ea91ec8ea74f3bb1e62023-11-26T12:21:52ZengSpringerOpenJournal of Shipping and Trade2364-45752023-09-018114410.1186/s41072-023-00155-8Contemporary challenges and AI solutions in port operations: applying Gale–Shapley algorithm to find best matchesMehran Farzadmehr0Valentin Carlan1Thierry Vanelslander2Department of Transport and Regional Economics, University of AntwerpDepartment of Transport and Regional Economics, University of AntwerpDepartment of Transport and Regional Economics, University of AntwerpAbstract Artificial intelligence (AI) developments enable human capability to deliver the same outcome at a lower cost. This research performs a high-level matching between AI solutions and challenges within the port area by developing a novel academic approach. This way, the matching is carried out more structured than when one (manager, developer, challenge owner, etc.) fulfils it based on their opinion without following any structured approach. Therefore, the study defines first a comprehensive typology of port stakeholders' challenges, which can be solved via AI solutions. This typology presents challenges, including their main issues, widespread impact, and potential solutions. A state-of-the-art review of AI solutions that can address these challenges is carried out in parallel. Secondly, this review clearly distinguishes between AI solutions based on their technology and functionality. Thirdly, this research selects an appropriate AI solution for addressing each identified challenge in the port operation by upgrading the Gale–Shapley algorithm. Finally, it shows that the most critical presented AI solutions in this study use various machine learning (ML) techniques. Besides, concerning the AI solution's reusability feature and the result of high-level matching, this research shows that the implementation phase effort can be drastically reduced by using the recently developed matching algorithm.https://doi.org/10.1186/s41072-023-00155-8Port challengesAI solutionsMatchingGale–Shapley algorithmPorts |
| spellingShingle | Mehran Farzadmehr Valentin Carlan Thierry Vanelslander Contemporary challenges and AI solutions in port operations: applying Gale–Shapley algorithm to find best matches Journal of Shipping and Trade Port challenges AI solutions Matching Gale–Shapley algorithm Ports |
| title | Contemporary challenges and AI solutions in port operations: applying Gale–Shapley algorithm to find best matches |
| title_full | Contemporary challenges and AI solutions in port operations: applying Gale–Shapley algorithm to find best matches |
| title_fullStr | Contemporary challenges and AI solutions in port operations: applying Gale–Shapley algorithm to find best matches |
| title_full_unstemmed | Contemporary challenges and AI solutions in port operations: applying Gale–Shapley algorithm to find best matches |
| title_short | Contemporary challenges and AI solutions in port operations: applying Gale–Shapley algorithm to find best matches |
| title_sort | contemporary challenges and ai solutions in port operations applying gale shapley algorithm to find best matches |
| topic | Port challenges AI solutions Matching Gale–Shapley algorithm Ports |
| url | https://doi.org/10.1186/s41072-023-00155-8 |
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