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1、4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,1,I. Introduction,M. Peter Jurkat CS452/Mgt532 Simulation for Managerial Decisions The Robert O. Anderson Schools of Management University of New Mexico,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,2,Definitions,Simulation: process of experimenting
2、with a model of a dynamic systems (e.g., process) to study or test the behavior of the system improve, problem solve design and/or select new systems , and/or train operators on a model of an existing systems System: purposeful, interrelated components with interdependencies and complexity Behavior:
3、 purposeful, interrelated sequences of activities Dynamic: time varying (static systems are dull!),4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,3,Examples,Service Systems: Traffic on Networks: messages to/from computers, cars on roads/rails, airplanes to/from airports/gates, ships to/from harbors
4、/piers, elevators Retail/Service :stores selling goods, service/repair shops, logistics/inventory/distribution/MRP Manufacturing Systems: Materials, Chemicals, Biologicals Appliances, Automobiles/Trucks, Toys, Clothing Electronics, Weapons Systems Computations using models from other disciplines Mac
5、roeconomic: taxation/interest rate cost/benefits Pollution: environmental intervention cost/benefits Project Management: completion time vs resources,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,4,Why Simulate?,To overcome human limitations in Physical capability: avoid injury and death; be able
6、to control systems whose dynamics are not yet known, Mental capability: attention, memory, processing, Analysis: allows us to study systems too complex for analytic description and/or too dangerous for human safety gain knowledge Design: attempt changes in IVs to drive one or more DVs toward an “opt
7、imal” value or combination of values for design, improvement, and/or problem solving,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,5,When not to Simulate!,When theory can determine sufficient results When it will cost more to simulate than the return on the knowledge gained When there is incomplet
8、e information about the system (can handle imprecise but not missing pieces) Need at least inputs and related outputs for “black boxes” Can assume missing information and check against known results if agreement, support for assumptions When it is not possible to develop a representative, tractable
9、simplification of the system,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,6,Definitions (cont.),Model: representation of a system three phases: Verbal always included in any representation Graphical see pages 22, 39, 50, 54, 367, and 536 Algorithm and/or computer program Experimentation: purposef
10、ul, structured, and controlled change of the inputs factors (independent variables IVs, exogenous, ) of a product and/or process to observe resulting changes in outputs (dependent variables - DVs, responses, results, outcomes, ) Both IVs, DVs also called measures or metrics In simulation literature
11、a run is one execution of the simulation program at one combination of input variable values also called a replication,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,7,Graphical Representation: Logical Symbols,BCNN 4th Ed., Figure 2.1, page 22: Single Server Queuing System,4/20/2019,MPJ/UNM CS452/M
12、gt 532 I. Introduction,8,Graphical Representation: State Variable Tracking,BCNN 4th Ed., Example 2.2, Figure 2.11, page 39,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,9,Graphical Representation: Physical Layout,BCNN 4th Ed., Example 2.6, Figure 2.15, page 50,4/20/2019,MPJ/UNM CS452/Mgt 532 I. In
13、troduction,10,Graphical Representation: Network Model,BCNN 4th Ed., Example 2.8, Figure 2.18, page 54,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,11,Graphical Representation: “Black Box”,BCNN 4th Ed., Figure 10.5, page 367,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,12,Graphical Representati
14、on: Component Relationship,BCNN 4th Ed., Example 14.4, Figure 14.10, page536: Website configuration,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,13,Simulation Study Representation (after Banks et al, Figure 1.3, Page 15),Problem Formulation,Set Objectives and Project Plan,(Re)Conceptualize Model
15、& Collect Data,Translate Model,Can Model be Verified?,No,Can Model be Validated?,Yes,No,DOE - Design Experiments,Runs and Replications,Analysis,Results Clear and Able to be Described?,No,Document, Report and Recommend,Yes,Yes,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,14,Simulation Study,Identi
16、fy problem(s), improvement(s), and/or plan new capabilities Specify the system select boundaries, identify inputs, entities, attributes, events, activities, processes, and state variables - specify output(s) and their desired values Build a conceptual and operational model of the system build a representation of inputs, entities, ,4/20/2019,MPJ/UNM CS452/Mgt 532 I. Introduction,15,Simulation Study (cont.),Verify and Validate (as best you can)
