perbandingan kinerja algoritma genetika dan algoritma heuristik rajendran untuk penjadualan produksi jenis flow shop

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ID: 255714
1999
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Abstract
Flow shop scheduling problem is to schedule a production process of n jobs that go through the same process sequence and the same m machines. Most researches are don to accomplish only one objective, i.e. minimizing makespan. The other objective, such as total flow time, or multiple objectives that is minimizing makespan, total flow time and machine idle time, will be more effective in reducing scheduling cost, as written in French (1982). Rajendran algorithm (1995) that solves flow shop problem with multiple objectives will be used to evaluate the proposed algorithm: Genetic Algorithm, developed by Sridhar & Rajendran (1996) on a problem that existed in a shoe factory. Abstract in Bahasa Indonesia : Masalah penjadualan flow shop adalah menjadualkan proses produksi dari masing-masing n job yang mempunyai urutan proses produksi dan melalui m mesin yang sama. Kebanyakan penelitian hanya mengacu pada satu tujuan saja yaitu meminimumkan makespan. Tujuan yang lain, seperti meminimumkan total flow time atau multiple objectives yang meminimumkan makespan, total flow time dan machine idle time akan lebih efektif dalam mengurangi biaya penjadualan, sebagaimana dikatakan oleh French (1982). Algoritma Rajendran (1995) yang menyelesaikan masalah flow shop dengan multiple objectives akan dipergunakan untuk mengevaluasi algoritma usulan: Algoritma Genetika, yang dikembangkan oleh Sridhar & Rajendran (1996) pada suatu masalah yang ditemui di suatu perusahaan sepatu. Kata kunci: flow shop, algoritma genetika, multiple objectives
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Authors ;Tessa Vanina Soetanto;Ervin Medianti;Didik Wahyudi
Journal coatings
Year 1999
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