https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Chaudhry_Mahmood_2011aChaudhry Mahmood 2011a - Revision history2026-04-10T02:49:14ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10https://www.scipedia.com/wd/index.php?title=Chaudhry_Mahmood_2011a&diff=236744&oldid=prevImran chaudhry: Imran chaudhry moved page Draft Chaudhry 460752305 to Chaudhry Mahmood 2011a2022-02-28T17:18:07Z<p>Imran chaudhry moved page <a href="/public/Draft_Chaudhry_460752305" class="mw-redirect" title="Draft Chaudhry 460752305">Draft Chaudhry 460752305</a> to <a href="/public/Chaudhry_Mahmood_2011a" title="Chaudhry Mahmood 2011a">Chaudhry Mahmood 2011a</a></p>
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</td></tr></table>Imran chaudhryhttps://www.scipedia.com/wd/index.php?title=Chaudhry_Mahmood_2011a&diff=236743&oldid=prevImran chaudhry: Created page with " == Abstract == dentical parallel machine scheduling problem for minimizing the makespan is a very important production scheduling problem which has been proven to be NP-hard..."2022-02-28T17:18:04Z<p>Created page with " == Abstract == dentical parallel machine scheduling problem for minimizing the makespan is a very important production scheduling problem which has been proven to be NP-hard..."</p>
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== Abstract ==<br />
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dentical parallel machine scheduling problem for minimizing the makespan is a very important production scheduling problem which has been proven to be NP-hard. The problem further compounds with additional constraints. Genetic algorithms (GA) have shown great advantages in solving the combinatorial optimization problem in view of its characteristic that has high efficiency and that is fit for practical application. In this chapter we present a spreadsheet based GA approach for minimizing the makespan for scheduling of a set of tasks for identical parallel machines and worker assignment to machines. The results obtained from the proposed approach are compared with two sets of benchmark problems consisting of 100 problems each. It has been demonstrated that the performance of proposed approach is superior to the results that have been obtained earlier. The proposed approach produces optimal solution for almost 95% of the problems demonstrating the effectiveness of the proposed approach. An empirical analysis of GA parameters has also been carried out to see the effect on the performance of the proposed algorithm.<br />
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== Full document ==<br />
<pdf>Media:Draft_Chaudhry_460752305-6203-document.pdf</pdf></div>Imran chaudhry