OPTIMASI BIAYA DISTRIBUSI RANTAI PASOK TIGA TINGKAT DENGAN MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DAN TERDISTRIBUSI
Supply chain management is critical in business area. The main core of supply chain management is the process of distribution. Distribution is the process to move and store goods ranging from the level of the supplier to the customer level in the supply chain. Optimal distribution will be the key to...
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2014
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| author | , ZULFAHMI INDRA , Prof. Drs. Subanar , Ph.D. |
| author_facet | , ZULFAHMI INDRA , Prof. Drs. Subanar , Ph.D. |
| author_sort | , ZULFAHMI INDRA |
| collection | UGM |
| description | Supply chain management is critical in business area. The main core of
supply chain management is the process of distribution. Distribution is the process
to move and store goods ranging from the level of the supplier to the customer
level in the supply chain. Optimal distribution will be the key to the company's
success in running a business, because the distribution process will directly impact
on supply chain costs. One issue is the distribution of decision strategies in
determining the allocation of the number of products that must be moved from the
level of the supplier to the customer level.
This study take optimization of three levels distribution from factory �
supplier � distributor � retailer. The approach taken is adaptive and distributed
genetic algorithm. Solution in the form of allocation of the number of products
delivered at each level will be modeled as a chromosome. Genetic parameters
such as the number of chromosomes in the population, crossover probability and
adaptive mutation probability will change adaptively according to conditions on
the population of that generation. This study used 3 sub-populations that exchange
individuals at any time in accordance with the probability of migration.
The results of research conducted 30 times for each value of the parameter
genetic fusion showed that the lowest cost value obtained is 80.910, which occurs
at the crossover probability 0,4, mutation probability 0,1, the probability of
migration 0,1 and migration rate 0,1. This result has shown that adaptive and
distributed genetic algorithm is better than stepping stone method that obtained 89.825. |
| first_indexed | 2024-03-13T23:18:17Z |
| format | Thesis |
| id | oai:generic.eprints.org:127748 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:18:17Z |
| publishDate | 2014 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1277482016-03-04T08:19:20Z https://repository.ugm.ac.id/127748/ OPTIMASI BIAYA DISTRIBUSI RANTAI PASOK TIGA TINGKAT DENGAN MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DAN TERDISTRIBUSI , ZULFAHMI INDRA , Prof. Drs. Subanar , Ph.D. ETD Supply chain management is critical in business area. The main core of supply chain management is the process of distribution. Distribution is the process to move and store goods ranging from the level of the supplier to the customer level in the supply chain. Optimal distribution will be the key to the company's success in running a business, because the distribution process will directly impact on supply chain costs. One issue is the distribution of decision strategies in determining the allocation of the number of products that must be moved from the level of the supplier to the customer level. This study take optimization of three levels distribution from factory � supplier � distributor � retailer. The approach taken is adaptive and distributed genetic algorithm. Solution in the form of allocation of the number of products delivered at each level will be modeled as a chromosome. Genetic parameters such as the number of chromosomes in the population, crossover probability and adaptive mutation probability will change adaptively according to conditions on the population of that generation. This study used 3 sub-populations that exchange individuals at any time in accordance with the probability of migration. The results of research conducted 30 times for each value of the parameter genetic fusion showed that the lowest cost value obtained is 80.910, which occurs at the crossover probability 0,4, mutation probability 0,1, the probability of migration 0,1 and migration rate 0,1. This result has shown that adaptive and distributed genetic algorithm is better than stepping stone method that obtained 89.825. [Yogyakarta] : Universitas Gadjah Mada 2014 Thesis NonPeerReviewed , ZULFAHMI INDRA and , Prof. Drs. Subanar , Ph.D. (2014) OPTIMASI BIAYA DISTRIBUSI RANTAI PASOK TIGA TINGKAT DENGAN MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DAN TERDISTRIBUSI. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=68023 |
| spellingShingle | ETD , ZULFAHMI INDRA , Prof. Drs. Subanar , Ph.D. OPTIMASI BIAYA DISTRIBUSI RANTAI PASOK TIGA TINGKAT DENGAN MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DAN TERDISTRIBUSI |
| title | OPTIMASI BIAYA DISTRIBUSI RANTAI PASOK TIGA TINGKAT DENGAN MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DAN TERDISTRIBUSI |
| title_full | OPTIMASI BIAYA DISTRIBUSI RANTAI PASOK TIGA TINGKAT DENGAN MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DAN TERDISTRIBUSI |
| title_fullStr | OPTIMASI BIAYA DISTRIBUSI RANTAI PASOK TIGA TINGKAT DENGAN MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DAN TERDISTRIBUSI |
| title_full_unstemmed | OPTIMASI BIAYA DISTRIBUSI RANTAI PASOK TIGA TINGKAT DENGAN MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DAN TERDISTRIBUSI |
| title_short | OPTIMASI BIAYA DISTRIBUSI RANTAI PASOK TIGA TINGKAT DENGAN MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DAN TERDISTRIBUSI |
| title_sort | optimasi biaya distribusi rantai pasok tiga tingkat dengan menggunakan algoritma genetika adaptif dan terdistribusi |
| topic | ETD |
| work_keys_str_mv | AT zulfahmiindra optimasibiayadistribusirantaipasoktigatingkatdenganmenggunakanalgoritmagenetikaadaptifdanterdistribusi AT profdrssubanarphd optimasibiayadistribusirantaipasoktigatingkatdenganmenggunakanalgoritmagenetikaadaptifdanterdistribusi |