Bina Nusantara Model Simulasi Peretemuan 23 (Off Clas) Mata kuliah: K0194-Pemodelan Matematika Terapan Tahun: 2008
Bina Nusantara Learning Outcomes Mahasiswa akan dapat menjelaskan definisi, pengertian, klasifikasi, motivasi penggunaan simulasi,model simulasi dan langkah-langkah proses simulasi.
Bina Nusantara Outline Materi: Pengertian simulasi Klasifikasi model simulasi Motivasi menggunakan simulasi Langkah-langkah proses simulasi
Bina Nusantara Pengertian Simulasi (Simulation) Simulation: a descriptive technique that enables a decision maker to evaluate the behavior of a model under various conditions. Simulation models complex situations Models are simple to use and understand Models can play “what if” experiments Extensive software packages available
Bina Nusantara Simulation Process 1.Identify the problem 2.Develop the simulation model 3.Test the model 4.Develop the experiments 5.Run the simulation and evaluate results 6.Repeat 4 and 5 until results are satisfactory
Bina Nusantara Monte Carlo Simulation Monte Carlo method: Probabilistic simulation technique used when a process has a random component Identify a probability distribution Setup intervals of random numbers to match probability distribution Obtain the random numbers Interpret the results
Bina Nusantara Simulating Distributions Poisson – Mean of distribution is required Normal – Need to know the mean and standard deviation Simulated value Mean Random number Standard deviation + X=
Bina Nusantara Uniform Distribution ab0x F(x) Simulated value a + (b - a)(Random number as a percentage) =
Bina Nusantara Negative Exponential Distribution F(t) 0Tt
Bina Nusantara Computer Simulation Simulation languages –SIMSCRIPT II.5 –GPSS/H –GPSS/PC –RESQ
Bina Nusantara Advantages of Simulation Solves problems that are difficult or impossible to solve mathematically Allows experimentation without risk to actual system Compresses time to show long-term effects Serves as training tool for decision makers
Bina Nusantara Limitations of Simulation Does not produce optimum solution Model development may be difficult Computer run time may be substantial Monte Carlo simulation only applicable to random systems
Bina Nusantara