https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Chaudhry_2018aChaudhry 2018a - Revision history2026-04-06T16:14:31ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10https://www.scipedia.com/wd/index.php?title=Chaudhry_2018a&diff=236724&oldid=prevImran chaudhry: Imran chaudhry moved page Draft Chaudhry 585920006 to Chaudhry 2018a2022-02-28T16:58:07Z<p>Imran chaudhry moved page <a href="/public/Draft_Chaudhry_585920006" class="mw-redirect" title="Draft Chaudhry 585920006">Draft Chaudhry 585920006</a> to <a href="/public/Chaudhry_2018a" title="Chaudhry 2018a">Chaudhry 2018a</a></p>
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</td></tr></table>Imran chaudhryhttps://www.scipedia.com/wd/index.php?title=Chaudhry_2018a&diff=236723&oldid=prevImran chaudhry: Created page with " == Abstract == This paper considers a no-wait flow shop scheduling (NWFS) problem, where the objective is to minimise the total flowtime. We propose a genetic algorithm (GA)..."2022-02-28T16:58:04Z<p>Created page with " == Abstract == This paper considers a no-wait flow shop scheduling (NWFS) problem, where the objective is to minimise the total flowtime. We propose a genetic algorithm (GA)..."</p>
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== Abstract ==<br />
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This paper considers a no-wait flow shop scheduling (NWFS) problem, where the objective is to minimise the total flowtime. We propose a genetic algorithm (GA) that is implemented in a spreadsheet environment. The GA functions as an add-in in the spreadsheet. It is demonstrated that with proposed approach any criteria can be optimised without modifying the GA routine or spreadsheet model. Furthermore, the proposed method for solving this class of problem is general purpose, as it can be easily customised by adding or removing jobs and machines. Several benchmark problems already published in the literature are used to demonstrate the problem-solving capability of the proposed approach. Benchmark problems set ranges from small (7-jobs, 7 machines) to large (100-jobs, 10-machines). The performance of the GA is compared with different meta-heuristic techniques used in earlier literature. Experimental analysis demonstrate that solutions obtained in this research offer equal quality as compared to algorithms already developed for NWFS problems.<br />
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== Full document ==<br />
<pdf>Media:Draft_Chaudhry_585920006-6721-document.pdf</pdf></div>Imran chaudhry