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- W2094356724 abstract "This paper focuses on cell loading and family scheduling in a cellular manufacturing environment. The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the presence of individual due dates for every job in a family and also allowing family splitting among cells. Three methods are examined in order to solve this problem, namely mathematical modelling, genetic algorithms (GA) and heuristics. The results showed that GA is capable of finding the optimal solution with varying frequency of 60–100% and it is efficient as compared to the mathematical modelling especially for larger problems in terms of execution times. The heuristics, on the other hand, were easy to implement but they could not find the optimal solution. The results of experimentation also showed that family splitting was observed in all multi-cell optimal solutions and therefore it can be concluded that family splitting is a good strategy for the problem considered in this paper." @default.
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- W2094356724 date "2014-04-10" @default.
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- W2094356724 title "Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness" @default.
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- W2094356724 doi "https://doi.org/10.1080/00207543.2014.903343" @default.
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