Multi-Population Ant Colony System for Multiple Path Planning of Food Delivery Applications
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cheng, Yi-Bin | - |
dc.contributor.author | Huang, Ting | - |
dc.contributor.author | Huang, Huntley Ting | - |
dc.contributor.author | Gong, Yue-Jiao | - |
dc.contributor.author | Zhang, Jun | - |
dc.date.accessioned | 2023-11-24T02:34:50Z | - |
dc.date.available | 2023-11-24T02:34:50Z | - |
dc.date.issued | 2018-07 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/115712 | - |
dc.description.abstract | Food delivery service receives increasing attention nowadays, and path planning plays an important role in the related practical applications. To accomplish the delivery tasks in a short time, deliver staffs traverse all the customers in a short tour to guarantee the freshness of food. In addition, they also need diverse good solutions from which they can choose according to their preference. To obtain diverse good solutions, we propose a multi-population ant colony system algorithm. The ant colony system guides the ants towards a promising space, while the multi-population strategy promises to maintain multiple potential candidate solutions at simultaneously. To evaluate the performance of the proposed algorithm, it is applied to four test instances. The experimental results show that the proposed algorithm can obtain diverse good solutions. Furthermore, the proposed algorithm is utilized to deal with a range of practical problems, which indicates that the proposed algorithm is of practical significance. © 2018 IEEE. | - |
dc.format.extent | 6 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Multi-Population Ant Colony System for Multiple Path Planning of Food Delivery Applications | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1109/SSCI.2018.8628684 | - |
dc.identifier.scopusid | 2-s2.0-85062788388 | - |
dc.identifier.wosid | 000459238800010 | - |
dc.identifier.bibliographicCitation | 2018 IEEE Symposium Series on Computational Intelligence (SSCI), pp 68 - 73 | - |
dc.citation.title | 2018 IEEE Symposium Series on Computational Intelligence (SSCI) | - |
dc.citation.startPage | 68 | - |
dc.citation.endPage | 73 | - |
dc.type.docType | Conference paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.subject.keywordAuthor | Ant colony system | - |
dc.subject.keywordAuthor | multi-population optimization | - |
dc.subject.keywordAuthor | Path planning of food delivery | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/8628684 | - |
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