Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/42789
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dc.contributor.authorChang, Sau Leng.-
dc.date.accessioned2011-01-11T05:42:58Z-
dc.date.available2011-01-11T05:42:58Z-
dc.date.copyright2000en_US
dc.date.issued2000-
dc.identifier.urihttp://hdl.handle.net/10356/42789-
dc.description.abstractIn this project, a local search algorithm has been implemented on a job-shop scheduling program[l] given at the initial stage of the project. The program was tested on 35 JSS benchmarks. The results show a range of performance that is 10% to 15% from the known optimum. Besides proposing and implementing the local search algorithm, the original JSS program is also ported to run on Win32 platforms(Win95 and NT). Its memory handling functions are modified to dynamically handle job-shop problems of any sizes from 5x5 up to 30x30. A Windows based graphical user interface(GUI) is written so that the user is able to modify benchmark specific parameters on the GUI and run several benchmarks in batch mode.en_US
dc.format.extent55 p.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleHeuristic driven genetic algorithm for job-shop schedulingen_US
dc.typeThesis-
dc.contributor.supervisorLim Meng Hioten_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Consumer Electronics)en_US
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