PERENCANAAN DISTRIBUSI UANG RUPIAH BANK INDONESIA

The conventional distribution planning of Bank Indonesia can easily leads to inefficienet capacity utilization, poor product availability, and high stock levels -- indicated by the high vault utilization average of 92,81% and the utilization level of full truckload only comprising 24,3% of all it...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: SITORUS, KREITON
التنسيق: Final Project
اللغة:Indonesia
الوصول للمادة أونلاين:https://digilib.itb.ac.id/gdl/view/66134
الوسوم: إضافة وسم
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المؤسسة: Institut Teknologi Bandung
اللغة: Indonesia
الوصف
الملخص:The conventional distribution planning of Bank Indonesia can easily leads to inefficienet capacity utilization, poor product availability, and high stock levels -- indicated by the high vault utilization average of 92,81% and the utilization level of full truckload only comprising 24,3% of all its shipments. This is caused by lack of demand visibility hence the implementation of vendor-managed iniventory is proposed -- with inventory routing as its core problem. In this research, a model and an algorithm is developed to solve the inventory routing problem to optimize the rupiah distribution plan of Bank Indonesia. The problem is approached using mixed integer programming constructed from the time-expanded network representation and solved using optimality gap approximation. The use of the model and algorithm in a rolling horizon framework is the simulated. From all the testing, it is demonstrated the lowest cost solution of inventory routing problem reduces 51,44% of average vault utilization and increases the frequency of full truckload deliveries by 11,66%. It is also shownn that the model gives savings by the use of longer planning horizons and more options of shipments to choose from. Model is not so sensitive to changes in cost parameters and expected to increase in total cost with deviations of demand realization. It is concluded that the model is a worth considering for alternative methods of rupiah distribution planning.