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<http://digilib.unila.ac.id/id/eprint/12892> <http://purl.org/dc/terms/title> "Evaluasi Kinerja Genetic Algorithm (GA) dengan Strategi Perbaikan Kromosom: Studi Kasus Knapsack Problem"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://digilib.unila.ac.id/id/eprint/12892> <http://purl.org/ontology/bibo/abstract> "Abstrak:\r\nSering ditemui persoalan packing, pengoptimalan jumlah nilai prioritas dari beberapa barang yang akan di-packing dalam suatu sack tampa melebihi kapasitasnya. Persoalan ini dikenal dengan Knapsack Problem. Untuk persoalan yang kecil, persoalan Knapsack mudah untuk diselesaikan. Namun untuk persoalan dengan jumlah barang yang sangat banyak akan sangat sulit untuk diselesaikan. Beberapa penelitan terdahulu telah dikembangkan. Teori pemrograman dinamis Bellman digunakan pertama kali untuk menyelesaikan pesoalan 0-1 KP kemudian Kolesar (1967) mencoba menyelesaikan 0-1 KP dengan menggunakan algoritma Branch and Bound, dan Gupta menggunakan Genetic Algorithm (GA) dengan operasi fchek untuk mengatasi kendala solusi yang tidak memenuhi fungsi pembatas. Salah satu metode yang digunakan adalah Genetic Algorithm (GA).\r\nNamun, persoalan Knapsack memiliki fungsi kendala yang akan membagi ruang solusi menjadi dua, yaitu solusi layak dan tidak layak. Untuk mengatasi kendala ini, fungsi fchek ditambahkan pada salah satu tahap GA. Mengulang penelitian sebelumnya, penelitian ini juga akan mengatasi kendala tersebut. Namun, penelitian ini menggunakan strategi perbaikan kromosom pada tahap evaluasi. Penelitian ini bertujuan untuk mengimplementasikan GA dengan strategi perbaikan kromosom. Metode yang dikembangkan diujicobakan pada beberapa data tes uji (test problem). Kinerja metode ini akan dievaluasi dengan membandingkan dengan kinerja GA dengan strategi penalty.\r\n\r\nKata kunci: Combinatorial Optimization, Genetic Algorithm (GA), Knapsack Problem, Repairing Strategy\r\n---------------------------------------------------------\r\n\r\nAbstact\r\nPacking, frequently encountered problems, optimizing the total value of several items that priority will be packing a sack without exceeding its capacity. This issue is known to Knapsack Problem. For small problems, Knapsack problem is easier to solve. However, for the issue of the number of goods that very much will be very difficult to resolve. Some previous research has been developed. Bellman dynamic programming theory was first used to settle the issue of 0-1 KP then Kolesar (1967) tried to finish 0-1 KP using Branch and Bound algorithm, and Gupta using a Genetic Algorithm (GA) with fchek operation to overcome a solution that does not meet barrier function. One method used is the Genetic Algorithm (GA).\r\nHowever, the issue of constraint Knapsack has a function that will divide the space into two solutions: solutions feasible and not feasible. To overcome this obstacle, the function fchek added at one stage GA.\r\nRepeating previous studies; this research will overcome these obstacles. However, this study uses chromosomal repair strategy at this stage of the evaluation. This research aims to implement GA with chromosomes improvement strategies. The method developed was tested in several test test data (test problem). This method of performance will be evaluated by comparing the performance of GA with penalty strategy.\r\n\r\nKeywords: Combinatorial Optimization, Genetic Algorithm (GA), Knapsack Problem, Repairing Strategy"^^<http://www.w3.org/2001/XMLSchema#string> .
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<http://digilib.unila.ac.id/id/document/1088802> <http://eprints.org/relation/isVolatileVersionOf> <http://digilib.unila.ac.id/id/document/1088765> .
<http://digilib.unila.ac.id/id/document/1088802> <http://eprints.org/relation/isIndexCodesVersionOf> <http://digilib.unila.ac.id/id/document/1088765> .
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<http://digilib.unila.ac.id/12892/91/preview.jpg> <http://www.w3.org/2000/01/rdf-schema#label> "preview.jpg"^^<http://www.w3.org/2001/XMLSchema#string> .
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<http://digilib.unila.ac.id/id/document/1088842> <http://eprints.org/relation/ispreviewThumbnailVersionOf> <http://digilib.unila.ac.id/id/document/1088760> .
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