Chapter 1 Introduction to Simulation Prof. Dr. Mesut Güneş▪Ch. 1 Introduction to Simulation 1.1 Introduction to Simulation • What is a simulation? • A simulation is the imitation of the operation of a real-world system over time. • Simulations can be particularly useful in fields like physics, engineering, and computer science, where physical experiments may be challenging or costly to conduct. S0 S1 S2 Time • How is it done? • Develop a model • Model consists of: entities (objects of the real-world system, ex, products, customers, events), and their behaviors (describe how entity changes over time and how it interacts with other entities or the environment). Prof. Dr. Mesut Güneş▪Ch. 1 Introduction to Simulation 1.2 Cont. Simulation modeling can be used as: - Analysis Tool: It can be used as an analysis tool to predict the effect of changes to existing systems. By simulating different scenarios and manipulating variables, analysts can study the impact of changes on system performance. Ex, in the context of the grocery store checkout counter, simulation modeling could be used to assess the effect of adding more checkout counters or implementing different queue management strategies on customer wait times. - Design Tool: Simulation modeling can also be used as a design tool to predict the performance of new systems before their implementation. By creating a simulation model of a proposed system, designers can evaluate its performance and identify potential issues or areas for improvement. Ex, in the context of a new grocery store, simulation modeling could help determine the optimal number of checkout counters and staff required to minimize customer wait times and maximize efficiency. Simulation examples Entertainment Games Prof. Dr. Mesut Güneş▪Ch. 1 Introduction to Simulation Serious Games 1.5 Cont. Simulation is widely used in both entertainment games and serious games to create virtual environments and provide interactive experiences for players. 1.Entertainment Games (Ex: Flight Simulators): Simulation used in flight simulators to recreate the experience of piloting an aircraft. -These games simulate various aspects of aviation, including aircraft controls, weather conditions, navigation systems, and airport procedures. -The goal is to provide a realistic flying experience to players. 2. Serious Games: are designed with a purpose: education, training, or simulation of real-world scenarios. Simulation used in serious games to recreate specific environments, scenarios, or processes for educational or training purposes. Ex: Disaster Management Simulations: Serious games focused on disaster management employ simulation to recreate emergency situations such as natural disasters, fires, or terrorist attacks. - Users can learn and practice crisis response, decision-making under pressure, and coordination among different agencies or stakeholders. -These simulations help improve preparedness and response capabilities in real-world scenarios. When is simulation appropriate? • Simulation enables the study of experiments with internal interactions of a complex system, or of a subsystem within a complex system. • Informational, organizational, and environmental changes can be simulated to see the model’s behavior • The knowledge gained in designing a simulation model may be of great value toward suggesting improvement in the system under investigation. • Observing results from simulation can give insight to which variables are the most important ones • Simulation can be used as pedagogical device to reinforce the learning material • Simulations can be used to verify analytical results in, e.g., queueing systems (mathematical models and formulas to analyze the behavior and performance of systems with waiting lines or queues) by providing a practical approach. • Animation of a simulation can show the system in action, so that the plan can be visualized Prof. Dr. Mesut Güneş▪Ch. 1 Introduction to Simulation 1.7 When is simulation not appropriate? • • • • • When problem is solvable by common sense When the problem can be solved mathematically When direct experiments are easier When the simulation costs exceed the savings When the simulation requires time, which is not available • When no (input) data is available, but simulations need data • When the simulation can not be verified or validated • When the system behavior is too complex or unknown • Example: human behavior is extremely complex to model Prof. Dr. Mesut Güneş▪Ch. 1 Introduction to Simulation 1.8 Advantages of simulation ( Simulations provide a valuable tool for decision-making, optimization, and gaining insights into system behavior.) • Policies, procedures, decision rules, information flows can be explored without disrupting the real system. (Ex: a simulation can be used to test different scheduling algorithms in a manufacturing facility (involves determining the sequence and timing of production activities to achieve specific objectives, such as minimizing production time or meeting customer demand) to determine the most efficient production plan. • New hardware designs, transportation systems, protocols, computer systems, and network architectures can be tested without committing resources (EX: a simulation can be used to assess the performance of a proposed network protocol before implementing it in a real network.) Prof. Dr. Mesut Güneş▪Ch. 1 Introduction to Simulation 1.9 Advantages of simulation (Cont.) • Hypotheses about how or why a phenomenon occurs can be tested for feasibility (Ex: a simulation can evaluate the feasibility of a hypothesis that increased advertising expenditure leads to higher sales for a product.) • Time can be compressed or expanded, allowing for the study of processes that occur over extended periods in a shorter timeframe. • Slow-down or Speed-up (EX: a simulation can be used to model the growth and evolution of a forest ecosystem over several decades in hours or days.) • Insight can be obtained about the interaction of variables (Ex: simulation can reveal how changes in pricing, marketing efforts, and customer preferences interact to impact the revenue of a retail business.) • Insight can be obtained about the importance of variables to the performance of the system (Ex:, a simulation of a supply chain can assess the impact of factors like inventory levels, transportation costs, and demand variability on overall supply chain efficiency.) Advantages of simulation • Bottleneck analysis can be performed to detect problems (Ex: a simulation can identify bottlenecks in a production line and suggest changes to improve throughput and reduce delays.) • Simulation can help to understand how the system operates rather than how people think the system operates (Ex: a simulation of traffic flow can reveal patterns and congestion points that may not be immediately apparent from observation alone.) • “What if …” questions can be answered, exploring the consequences of different scenarios or decisions. (EX:, a simulation can assess the impact of changing interest rates on the profitability of a financial institution.) Prof. Dr. Mesut Güneş▪Ch. 1 Introduction to Simulation 1.11 Disadvantages of simulation • Model building requires training, it is like an art since it requires experience and domain knowledge to create an accurate representation of the real-world system. Furthermore, if two models are constructed by two different individuals, they may have similarities, but it is highly unlikely that they will be the same. • Simulation results can be difficult to interpret (Ex: Analyzing the results of a simulation model that predicts stock market prices may require statistical techniques to identify meaningful patterns in the data and differentiate between random fluctuations and actual market trends.) -Most outputs are essentially random variables (they are usually based on random inputs) -Thus, not simple to decide whether output is randomness or system behavior (EX: Simulating the spread of a contagious disease within a population would involve incorporating randomness in factors such as individual interactions, infection rates, and recovery times, making it challenging to precisely predict the outcome of the simulation. This randomness can make it difficult to determine whether observed results are due to chance or represent actual system behavior.) 1.12 Prof. Dr. Mesut Güneş▪Ch. 1 Introduction to Simulation Disadvantages of simulation (Cont.) • Simulation can be time consuming and expensive • Skimping (use less) resources and time could lead to a simulation model or analysis that is not sufficient for the task. (Example: Simulating the behavior of a nuclear power plant during an emergency scenario would require significant computational resources and time to accurately capture the complex interactions of various systems) • The disadvantages are offset as follows: • Simulation packages contain pre-built models that only need input data, and this reduces the effort required to create a model from scratch. • Simulation packages contain tools for analyzing and interpreting simulation outputs, facilitating result interpretation. • Sophistication in computer technology, such as faster processors and parallel computing, have reduced simulation runtimes. • For most of the real-world problems there are no closed form solutions, thus Simulation provides a valuable approach when closed-form solutions are not available, allowing for the study of complex systems and their Prof. Dr. Mesut Güneş▪Ch. 1 Introduction to Simulation behaviors. 1.13 Application areas of simulation • • • • • • • • • • Manufacturing applications Construction engineering and project management Military applications Transportation models and traffic Business process simulation Health care Call-center Computers and Networks Games, Entertainment ... Prof. Dr. Mesut Güneş▪Ch. 1 Introduction to Simulation 1.14
