Chapter 1 Basic Simulation Modeling Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 1 of 51 CONTENTS 1 1 The Nature of Simulation 1 2 Systems Models and Simulation 1 3 Discrete Event Simulation 1 4 Simulation of a Single Server Queueing System 1 5 Simulation of an Inventory System 1 6 Alternative Approaches to Modeling and Coding Simulations 1 7 Steps in a Sound Simulation Study 1 8 Other Types of Simulation 1 9 Advantages Disadvantages and Pitfalls of Simulation Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 2 of 51 1 1 THE NATURE OF SIMULATION Simulation Imitate the operations of a facility or process usually via computer What s being simulated is the system To study system often make assumptions approximations both logical and mathematical about how it works These assumptions form a model of the system If model structure is simple enough could use mathematical methods to get exact information on questions of interest analytical solution Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 3 of 51 1 1 The Nature of Simulation cont d But most complex systems require models that are also complex to be valid Must be studied via simulation evaluate model numerically and collect data to estimate model characteristics Example Manufacturing company considering extending its plant Build it and see if it works out Simulate current expanded operations could also investigate many other issues along the way quickly and cheaply Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 4 of 51 1 1 The Nature of Simulation cont d Some not all application areas Designing and analyzing manufacturing systems Evaluating military weapons systems or their logistics requirements Determining hardware requirements or protocols for communications networks Determining hardware and software requirements for a computer system Designing and operating transportation systems such as airports freeways ports and subways Evaluating designs for service organizations such as call centers fast food restaurants hospitals and post offices Reengineering of business processes Determining ordering policies for an inventory system Analyzing financial or economic systems Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 5 of 51 1 1 The Nature of Simulation cont d Use popularity of simulation Several conferences devoted to simulation notably the Winter Simulation Conference www wintersim org Surveys of use of OR MS techniques examples Longitudinal study 1973 1988 Simulation consistently ranked as one of the three most important techniques 1294 papers in Interfaces 1997 Simulation was second only to the broad category of math programming Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 6 of 51 1 1 The Nature of Simulation cont d Impediments to acceptance use of simulation Models of large systems are usually very complex But now have better modeling software more general flexible but still relatively easy to use Can consume a lot of computer time But now have faster bigger cheaper hardware to allow for much better studies than just a few years ago this trend will continue However simulation will also continue to push the envelope on computing power in that we ask more and more of our simulation models Impression that simulation is just programming There s a lot more to a simulation study than just coding a model in some software and running it to get the answer Need careful design and analysis of simulation models simulation methodology Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 7 of 51 1 2 SYSTEMS MODELS AND SIMULATION System A collection of entities people parts messages machines servers that act and interact together toward some end Schmidt and Taylor 1970 In practice depends on objectives of study Might limit the boundaries physical and logical of the system Judgment call level of detail e g what is an entity Usually assume a time element dynamic system State of a system Collection of variables and their values necessary to describe the system at that time Might depend on desired objectives output performance measures Bank model Could include number of busy tellers time of arrival of each customer etc Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 8 of 51 1 2 Systems Models and Simulation cont d Types of systems Discrete State variables change instantaneously at separated points in time Bank model State changes occur only when a customer arrives or departs Continuous State variables change continuously as a function of time Airplane flight State variables like position velocity change continuously Many systems are partly discrete partly continuous Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 9 of 51 1 2 Systems Models and Simulation cont d Ways to study a system Simulation is method of last resort Maybe But with simulation there s no need or less need to look where the light is Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 10 of 51 1 2 Systems Models and Simulation cont d Classification of simulation models Static vs dynamic Deterministic vs stochastic Continuous vs discrete Most operational models are dynamic stochastic and discrete will be called discrete event simulation models Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 11 of 51 1 3 DISCRETE EVENT SIMULATION Discrete event simulation Modeling of a system as it evolves over time by a representation where the state variables change instantaneously at separated points in time More precisely state can change at only a countable number of points in time These points in time are when events occur Event Instantaneous occurrence that may change the state of the system Sometimes get creative about what an event is e g end of simulation make a decision about a system s operation Can in principle be done by hand but usually done on computer Simulation Modeling and Analysis Chapter 1 Basic Simulation Modeling Slide 12 of 51 1 3 Discrete Event Simulation cont d Example Single server queue Estimate expected average delay in queue line not service State variables Status of server idle busy needed to decide what to do with an arrival Current length of the queue to know where to store an arrival that must wait in line Time of arrival of each customer now in queue needed to compute time in