Hasil Pencarian  ::  Simpan CSV :: Kembali

Abstrak :
Penelitian tentang model persediaan telah banyak dilakukan dan menjadi solusi bagi perusahaan dalam menghadapi ketidakpastiaan dari permintaan pelanggan. Beberapa permasalahan bagi perusahaan yang tidak menerapkan model persediaan pada proses pembelian bahan baku adalah terjadinya stockout serta tingginya total biaya inventori. Namun, pemecahan model persediaan yang memiliki permintaan bersifat stokastik tidak dapat dilakukan dengan menggunakan metode analisis tradisional biasa. Hal tersebut dikarenakan permintaan pelanggan tidak mengikuti distribusi normal. Sehingga penelitian ini dibuat dengan mengembangkan metode simulasi Monte Carlo untuk menyelesaikan masalah persediaan dengan permintaan stokastik dan intermiten. Simulasi dilakukan untuk mengevaluasi dua jenis sistem persediaan, yaitu kebijakan peninjauan persediaan berkelanjutan (Q,R), serta kebijakan peninjauan persediaan berkala (s,S). Model simulasi kemudian dioptimalkan menggunakan model persediaan (Q,R) dan (s,S) dengan metode integer linear programming. Model-model tersebut diterapkan berdasarkan data dari salah satu perusahaan manufaktur perhiasan di Indonesia dengan produk yang diuji bertipe diamond jewelry. Hasil penelitian menunjukkan bahwa kebijakan kuantitas peninjauan persediaan berkelanjutan (Q, R) lebih baik daripada kebijakan peninjauan persediaan berkala (s, S) dari segi total biaya persediaan untuk kelompok bahan baku komponen. ......Research on the inventory models have conducted intensively and become a solution for companies when dealing with the uncertainty of customer demand. Some problems that occur to companies that have not applied the inventory models in the process of purchasing raw materials are stockout material and high total inventory costs. However, solving the inventory models that have stochastic demand cannot be done using traditional analysis methods. That is because the customer demand does not follow the normal distribution. So, this research was made by developing a Monte Carlo simulation method to solve inventory problems with stochastic and intermittent demand. Simulations is conducted to evaluate two types of inventory systems, which is the continuous inventory review policy (Q, R), and the periodic inventory review policy (s, S). The simulation models are optimized using the inventory model (Q, R) and (s, S) with the integer linear programming method. The models are applied based on data from one of the jewelry manufacturing companies in Indonesia with the product being tested as diamond jewelry. The results showed that the continuous inventory review policy (Q, R) was better than the periodic inventory review policy (s, S) in terms of total inventory cost for the component raw material group.

Abstrak :
This book provides a concise introduction to the behavior of mechanical structures and testing their stochastic stability under the influence of noise. It explains the physical effects of noise and in particular the concept of Gaussian white noise. In closing, the book explains how to model the effects of noise on mechanical structures, and how to nullify/compensate for it by designing effective controllers.

Abstrak :
This volume provides a general overview of discrete- and continuous-time Markov control processes and stochastic games, along with a look at the range of applications of stochastic control and some of its recent theoretical developments. These topics include various aspects of dynamic programming, approximation algorithms, and infinite-dimensional linear programming. In all, the work comprises 18 carefully selected papers written by experts in their respective fields.