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Conference Paper: Multi-objective genetic algorithms for scheduling mateiral handling equipment at automated air cargo terminals
| Title | Multi-objective genetic algorithms for scheduling mateiral handling equipment at automated air cargo terminals |
|---|---|
| Authors | |
| Issue Date | 2004 |
| Publisher | IEEE. |
| Citation | IEEE Conference on Cybernetics and Intelligent Systems, Singapore, 1-3 December 2004, v. 2, p. 718-723 How to Cite? |
| Abstract | In order to improve thc productivitics of a typical cargo handling system, it is important to reduce the waiting time of stacker crancs (SCs) and the total traveling time of automated guided vehicles (AGVs) through efficient scheduling of SCs and ACVs, which are cooperating tightly to perform cargo handling operations in an optimal way. In this paper, we devclop and investigate the application of the multi-objective genetic algorithm (MOCA) to solve such schcduling problem with the objectives of minimizing the ACV total traveling time and thc total delay time of the SC. The results of the experimcnts demonstrated that MOGA produces better solution than the single objective genetic algorithms. |
| Persistent Identifier | http://hdl.handle.net/10722/46557 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lau, HYK | en_HK |
| dc.contributor.author | Zhao, Y | en_HK |
| dc.date.accessioned | 2007-10-30T06:52:53Z | - |
| dc.date.available | 2007-10-30T06:52:53Z | - |
| dc.date.issued | 2004 | en_HK |
| dc.identifier.citation | IEEE Conference on Cybernetics and Intelligent Systems, Singapore, 1-3 December 2004, v. 2, p. 718-723 | en_HK |
| dc.identifier.uri | http://hdl.handle.net/10722/46557 | - |
| dc.description.abstract | In order to improve thc productivitics of a typical cargo handling system, it is important to reduce the waiting time of stacker crancs (SCs) and the total traveling time of automated guided vehicles (AGVs) through efficient scheduling of SCs and ACVs, which are cooperating tightly to perform cargo handling operations in an optimal way. In this paper, we devclop and investigate the application of the multi-objective genetic algorithm (MOCA) to solve such schcduling problem with the objectives of minimizing the ACV total traveling time and thc total delay time of the SC. The results of the experimcnts demonstrated that MOGA produces better solution than the single objective genetic algorithms. | en_HK |
| dc.format.extent | 1011756 bytes | - |
| dc.format.extent | 2836 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | text/plain | - |
| dc.language | eng | en_HK |
| dc.publisher | IEEE. | en_HK |
| dc.relation.ispartof | IEEE Conference on Cybernetics and Intelligent Systems | - |
| dc.rights | ©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
| dc.title | Multi-objective genetic algorithms for scheduling mateiral handling equipment at automated air cargo terminals | en_HK |
| dc.type | Conference_Paper | en_HK |
| dc.description.nature | published_or_final_version | en_HK |
| dc.identifier.doi | 10.1109/ICCIS.2004.1460676 | en_HK |
| dc.identifier.hkuros | 107261 | - |