Apichat Sopadang. Optimization of order quantity with uncertainty demand using simulation. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2021.
Optimization of order quantity with uncertainty demand using simulation
Abstract:
This research aims to determine optimal order quantity that minimize the sum of total inventory cost. The current ordering policy of studied company is, the order is placed with random replenishment point (Q) when inventory level is less than or equal reorder point (ROP) based on the manager decision. However, the studied company stated that this policy cannot cover the uncertainty demand which affect the overall of company financial. This research focuses on the order quantity of single item which the most valued in the production of studied company. The Monte Carlo simulation based genetic algorithm was applied in this research to handle the uncertainty of demand. Spreadsheet simulation model was generated to optimize the value of ROP from Lordahl and Bookbinders formula and trial Q under the uncertainty demand condition. The result shows that 780 units of reorder point can provide the minimum total inventory cost with new replenishment quantity at 1,260 units. The new order quantity can reduce the total inventory cost from 757,172 THB to 399,999 THB or counted to 47.17 percent reduction.
King Mongkut's University of Technology North Bangkok. Central Library