# Monte Carlo Simulation Approach to Determine the Optimal Solution of Probabilistic Supply Cost

## Authors

• Helmi Ramadan Department of Mathematics, Universitas Sumatera Utara, Medan, 20155, Indonesia
• Prana Ugiana Gio Department of Mathematics, Universitas Sumatera Utara, Medan, 20155, Indonesia
• Elly Rosmaini Department of Mathematics, Universitas Sumatera Utara, Medan, 20155, Indonesia

## Keywords:

EOQ Model, Monte Carlo Simulation

## Abstract

Monte Carlo simulation is a probabilistic simulation where the solution of problem is given based on random process. The random process involves a probability
distribution from data variable collected based on historical data. The used model is probabilistic Economic Order Quantity Model (EOQ). This model then assumed use Monte Carlo simulation, so that obtained the total of optimal supply cost in the future. Based on data processing, the result of probabilistic EOQ is \$486128,19. After simulation using Monte Carlo simulation where the demand data follows normal distribution and it is obtained the total of supply cost is \$46116,05 in 23 months later. Whereas the demand data uses Weibull distribution is obtained the total of supply stock is \$482301,76. So that, Monte Carlo simulation can calculate the total of optimal supply in the future based on historical demand data.

2020-02-24

## How to Cite


H. Ramadan, P. U. Gio, and Elly Rosmaini, “Monte Carlo Simulation Approach to Determine the Optimal Solution of Probabilistic Supply Cost”, J. of Research in Math. Trends and Tech., vol. 2, no. 1, pp. 1-6, Feb. 2020.

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