Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/13843
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dc.titleTwo agent-based approaches for solving multi-objective multi-constraint optimization problems
dc.contributor.authorWANG HUI
dc.date.accessioned2010-04-08T10:36:58Z
dc.date.available2010-04-08T10:36:58Z
dc.date.issued2004-03-29
dc.identifier.citationWANG HUI (2004-03-29). Two agent-based approaches for solving multi-objective multi-constraint optimization problems. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/13843
dc.description.abstractIn this thesis, we propose two different agent-based approaches, the Coarse Grained Agent System (CGAS) and Fine Grained Agent System (FGAS) to solve Multi-Objective Multi-Constraint Problems (MOMCP), which represent the nature of many real life problems. CGAS gives a generic agent-model for multi-objective multi-constraint problem, while FGAS caters more for distributed multi-objective multi-constraint problem like most multiagent systems. We apply our approaches to solve the Inventory Routing Problem with Time Window (IRPTW). Experimental results indicate CGAS achieves a much better results than previous work, while FGAS runs very fast, whose run time is about one-sixth of CGAS with solution quality less than 10% poorer, which is still better than previous work.
dc.language.isoen
dc.subjectAgent-based approach, Multi-objective multi-constraint problem
dc.typeThesis
dc.contributor.departmentCOMPUTER SCIENCE
dc.contributor.supervisorLAU HOONG CHUIN
dc.description.degreeMaster's
dc.description.degreeconferredMASTER OF SCIENCE
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Master's Theses (Open)

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