OPTIMASI POLA PENYUSUNAN BARANG DALAM RUANG TIGA DIMENSI MENGGUNAKAN METODE GENETIC ALGORITHMS
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https://doi.org/10.9744/informatika.4.1.pp.%2013-17Keywords:
optimization, good arangement, genetic algorithms.Abstract
The good arrangement pattern in the three dimension space, for example container, must be made as optimal as possible to keep the dispatch cost down. Genetic algorithms as the solution search methods which depends on the natural selection to get an individual with the best gene arrangement, is able to give the solution towards how the good arrangement pattern is optimized through iteration process until some generations with reproduction, crossover, and mutation operators. By inserting some input such as the space and goods specification, and the probability of the three genetic algorithms operator, the optimization process will look for the good arrangement pattern based on fitness or the best grade, that is the fewer empty space left. Abstract in Bahasa Indonesia : Pola penyusunan barang dalam ruang tiga dimensi, contohnya kontainer, harus bisa seoptimal mungkin untuk menekan biaya pengiriman dalam berbisnis. Algoritma genetik sebagai metode pencarian solusi yang berpatokan pada seleksi alam untuk mendapatkan sebuah individu dengan susunan gen-gen terbaik, mampu memberikan solusi bagaimana pola susunan barang dioptimalkan melalui proses iterasi sampai beberapa generasi dengan operatornya yaitu reproduksi, pindah silang, dan mutasi. Dengan memasukkan inputan berupa spesifikasi ruang dan barang beserta probabilitas ketiga operator algoritma genetik, proses optimasi akan menemukan pola susunan barang berdasarkan fitness atau nilai terbaik, yaitu semakin sedikit ruang kosong yang tersisa. Kata kunci: optimasi, penyusunan barang, algoritma gemetik.Downloads
Published
2004-06-21
How to Cite
Gunadi, K., Julistiono, I. K., & Hariyanto, B. (2004). OPTIMASI POLA PENYUSUNAN BARANG DALAM RUANG TIGA DIMENSI MENGGUNAKAN METODE GENETIC ALGORITHMS. Jurnal Informatika, 4(1), pp. 13-17. https://doi.org/10.9744/informatika.4.1.pp. 13-17
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