Matakuliah Tahun : K0414 / Riset Operasi Bisnis dan Industri : 2008 / 2009 Model Simulasi Pertemuan 22 Learning Outcomes • Mahasiswa akan dapat menjelaskan definisi, pengertian, klasifikasi, motivasi penggunaan simulasi,model simulasi dan langkah-langkah proses simulasi. Bina Nusantara University 3 Outline Materi: • • • • Pengertian simulasi Klasifikasi model simulasi Motivasi menggunakan simulasi Langkah-langkah proses simulasi Bina Nusantara University 4 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 University 5 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 University 6 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 University 7 Simulating Distributions • Poisson – Mean of distribution is required • Normal – Need to know the mean and standard deviation Simulated = Mean value Bina Nusantara University + Random X Standard number deviation 8 Uniform Distribution F(x) 0 a b x Simulated a + (b - a)(Random number as a percentage) = value Bina Nusantara University 9 Negative Exponential Distribution F(t) P ( t T ) . RN 0 Bina Nusantara University T t 10 Computer Simulation • Simulation languages – SIMSCRIPT II.5 – GPSS/H – GPSS/PC – RESQ Bina Nusantara University 11 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 University 12 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 University 13 Bina Nusantara University 14