Claim Missing Document
Check
Articles

Found 1 Documents
Search

Pemanfaatan Algoritma Genetika Untuk Optimasi 0/1 Multi-Dimensional Knapsack Problem Dalam Pendistribusian Produk (Studi Kasus UD.TOSA) Ryan Iriany; Agus Wahyu Widodo; Wayan Firdaus Mahmudy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 4 (2017): April 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1062.046 KB)

Abstract

As a distributor company, the cost of distribution is very influential on the benefits to be obtained UD.TOSA. The affect of distribution cost is the distance distribution. Besides affected by distance, cost is also influenced by the frequency of maintenance vehicles used in the distribution process. The more frequent occurrence of damage to the vehicle, it will increase the frequency of maintenance so that adds to the cost of distribution. One cause damage to the vehicle is because vehicles are often excess payload (overtonase). Excessive loads can also increase the potential for accidents that could result in damage to the product as well as the vehicle itself. This will result in reduced profits obtained. Products are distributed and used vehicles have their respective characteristics. Each vehicle has a limited capacity, so not all products can be loaded, the distributor can perform any combination of products that should be loaded in order to maximize cargo volume without exceeding the capacity of the vehicle. The combination of products in the distribution process is a complex combinatorial problems, problems of this combination into the multi-dimensional knapsack problem (MKDP). Utilization of genetic algorithms in multi-dimensional knapsack problem is to perform such optimization of capacity in the distribution process.The algorithm parameters used in this study is a population of 200, the generation of 100, cr by 0.9 and 0.1 mr. Excess load on the solutions produced by the system is equal to 0% of the maximum load capacity of the vehicle. Solutions generated by the system can be ensured not exceed the capacity, both of maximum space vehicles as well as the maximum load of the vehicle. It can reduce the risk of damage to the vehicle so that the frequency of maintenance is not too often.