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https://scholarbank.nus.edu.sg/handle/10635/23662
DC Field | Value | |
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dc.title | Dynamic Job Shop Scheduling Using Ant Colony Optimization Algorithm Based On A Multi-Agent System | |
dc.contributor.author | ZHOU RONG | |
dc.date.accessioned | 2011-06-27T18:00:07Z | |
dc.date.available | 2011-06-27T18:00:07Z | |
dc.date.issued | 2008-02-26 | |
dc.identifier.citation | ZHOU RONG (2008-02-26). Dynamic Job Shop Scheduling Using Ant Colony Optimization Algorithm Based On A Multi-Agent System. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/23662 | |
dc.description.abstract | Ant Colony Optimization (ACO) algorithm is applied to a series of dynamic job shop scheduling problems (DJSSPs) for its unique property of simulating the optimization mechanism of real-world forage ants, which dynamically optimize the routes between their nest and a food source. The experimental results show that ACO can perform effectively in the given DJSSPs; the adaptation mechanism of ACO can significantly improve its overall performance for DJSSPs with proper dynamism; increasing the sizes of the minimal number of iterations and the ants per iteration does not necessarily improve the overall performance; finally, ACO can outperform several common dispatching rules in certain domains defined by machine utilization, variation of processing times, and performance measures. Experiments are carried out on a test-bed simulating a generic job shop as a discrete event system, which is then implemented as a multi-agent system. The steady-state performance of ACO is statistically analyzed. | |
dc.language.iso | en | |
dc.subject | Dynamic job shop scheduling, ant colony optimization algorithm, multi-agent system | |
dc.type | Thesis | |
dc.contributor.department | MECHANICAL ENGINEERING | |
dc.contributor.supervisor | NEE YEH CHING, ANDREW | |
dc.contributor.supervisor | LEE HEOW PUEH | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Ph.D Theses (Open) |
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ZhouRong-PhD-ME-NUS-022608.pdf | 864.88 kB | Adobe PDF | OPEN | None | View/Download |
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