Event-Scheduling View



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Event-Scheduling View

  • Event-Scheduling View

  • Process-interaction View

    • View model as a set of processes through which an entity “flows”
    • Life-cycle approach – time-sequenced list of events, activities, & delays
    • Common in simulation environments


Activity Scanning Approach

  • Activity Scanning Approach

    • Focus on activities & conditions that allow it to begin
    • At each clock advance, scan conditions to start any activity that can begin
    • Approach is simple, but scan is slow
    • New 3-phase approach includes some event scheduling – somewhat more complex but more efficient


General Purpose Languages

  • General Purpose Languages

    • C, C++, Java
  • Simulation Languages

    • GPSS, SIMAN, SLAM, SSF
  • Simulation Environments

    • Enterprise Dynamics, Arena, SIMUL8


Some focus on a single type of application

  • Some focus on a single type of application

  • Built in features include

    • Statistics collection
    • Time management
    • Queue management
    • Event generation


Some focus on one type of application

  • Some focus on one type of application

  • Icon based

  • Analysis of I/O

  • Advanced Statistics

  • Optimization

  • Support for Experimentation



1955-60 Period of Search

  • 1955-60 Period of Search

  • 1961-65 Advent

  • 1966-70 Formative Period

  • 1971-78 Expansive Period

  • 1979-86 Period of Consolidation & Regeneration

  • 1987- 2008 Period of Integrated Environments

  • 2009 + The Future



1981 – 137 Simulation languages reported

  • 1981 – 137 Simulation languages reported

  • More have be developed since

  • Now Simulation Environments



FORTRAN – one of a few languages

  • FORTRAN – one of a few languages

  • Focus on unifying concepts & reusable functions

  • General Simulation Program – first effort at “language” which as a set of functions



GPSS – 1961 @ IBM

  • GPSS – 1961 @ IBM

  • SIMSCRIPT – 1963 – Rand Corp.

    • US Air Force – government is biggest user
    • FORTRAN influence
    • Owned by CACI in CA.


GASP – 1961

  • GASP – 1961

    • Based on Algol, then Fortran
    • Collection of Fortran functions
  • SIMULA – extension of Algol

    • Widely used in Europe
  • CSL (Control & Simulation Language)



Concepts caused major revisions of languages

  • Concepts caused major revisions of languages

  • Languages gained wider usage

  • GPSS (several variations)

  • Simscript II – English-like

  • ECSL – Europe

  • SIMULA – added classes & inheritance



GPSS/H – 1977

  • GPSS/H – 1977

  • GASP IV – 1974 – Purdue

  • SIMULA

    • Attempt to simplify the modeling process
    • Program generators – severe limitations


Movement to mini and PC computers

  • Movement to mini and PC computers

  • SLAM II (descendant of GASP)

    • 3 world views
        • Event, Network, Continuous
  • SIMAN (descendant of GASP)

    • General Modeling + Block Diagrams
    • 1st first major language - PC & MS-DOS
    • Fortran functions w/ Fortran programming


Growth on PC’s

  • Growth on PC’s

  • Simulation Environments

    • GUI
    • Animation
    • Data analyzers


What can we expect in the future? (2008)

  • What can we expect in the future? (2008)

  • Virtual Reality

  • Improved Interfaces

  • Better Animation

  • Agent-based Modeling



AnyLogic

  • AnyLogic

  • Ascape

  • MASON

  • NetLogo

  • StarLogo

  • Swarm

  • RePast



Consider multiple issues

  • Consider multiple issues

    • Ease of use, support, applicability
  • Speed of execution

    • Experimental runs – Debugging
  • Beware of demos & advertising

    • Will focus on strengths only
    • Ask for demo of YOUR problem


Carefully consider comparison checklists with yes/no answers

  • Carefully consider comparison checklists with yes/no answers

  • Can software link to external languages

  • Carefully consider trade-off between graphical model building & simulation programming language

  • Costs – one-time vs. licensing



See the following tables in text:

  • See the following tables in text:

  • Model-building features

    • P. 123 – Table 4.1
  • Runtime Environment

    • P. 124 – Table 4.2
  • Animation & Layout features

    • P. 124 – Table 4.3


  • Output features

    • P. 125 – Table 4.4
  • Vendor Support - Documentation

    • P. 125 – Table 4.5


Consider at standard checkout counter environment with on clerk and one queue. Interarrival times are exponentially distributed with mean 4.5 minutes; service times normally distributed with mean 3.2 and standard deviation 0.6 minutes.

  • Consider at standard checkout counter environment with on clerk and one queue. Interarrival times are exponentially distributed with mean 4.5 minutes; service times normally distributed with mean 3.2 and standard deviation 0.6 minutes.

  • Simulate for 1000 customers.



Section 4.4 – p.126

  • Section 4.4 – p.126

  • Note similarity to our process in project one



Highly Structured

  • Highly Structured

  • Process Approach

  • Queuing Systems

  • Block Diagrams

    • 40 standard blocks
    • Block corresponds to a statement
  • Transactions FLOW through the system



Figure 4.10 – p. 138

  • Figure 4.10 – p. 138

  • Each entity has a name

    • Name each queue, server, etc.
  • In rectangle, parameters (as necessary)

  • Right attachment, name of entity

  • Far right column – GPSS Command



Label OpCode Subfields ; comment

  • Label OpCode Subfields ; comment

  • Label: col. 1, <= 9 alphanumeric, alpha start

  • OpCode: 4+ characters of command

  • Subfields: as necessary, separated by commas

  • Comment: after ; or with * in column 1



Figure 4.11 – p. 139

  • Figure 4.11 – p. 139

  • Declaration Section

  • Customized vs. Standard Output

  • Code Section



Generate rvexpo (1,&IAT)

  • Generate rvexpo (1,&IAT)

  • Queue Systime

  • Queue Line

  • Seize Checkout

  • Depart Line

  • Advance rvnorm(1,&mean,&stdev)

  • Release Checkout

  • Depart Systime

  • Test_GE M1, 4, Term

  • Blet &Count = &Count +1

  • Ter Terminate 1

  • Start &Limit



Customized

  • Customized

    • Figure 4.12 – P. 141
  • Standard

    • Figure 4.13 – P. 142


SSF – Scalable Simulation Framework

  • SSF – Scalable Simulation Framework

    • Application Program Interface (API)
    • Object-oriented, process view
    • 5 Base Classes
      • Process, Entity, Event, InChannel, OutChannel
    • Designed for high-performance computers
    • Bridges pure Java & simulation languages
    • Figures 4.14 & 4.15


GUI

  • GUI

  • Animation

  • Automatic statistics

  • Output (tables, graphs, custom)

  • Analysis

  • Process world view



Some allow

  • Some allow

    • Event Scheduling
    • Mixed continuous-discrete models
  • Animations – 2D & 3D

  • Business Graphics



AnyLogic

  • AnyLogic

  • Arena

  • AutoMod

  • Enterprise Dynamics



Supports: discrete event, agent-based, system dynamics (& combination)

  • Supports: discrete event, agent-based, system dynamics (& combination)

  • Hybrid: discrete & continuous

  • Object library

  • Java models, publish as applets

  • Animation, Statistics, optimization, debugger



Discrete & Continuous systems

  • Discrete & Continuous systems

  • Object-based; GUI

  • 2D, 3D Animation

  • Business & Manufacturing processes

  • Supports Analysis

  • OptQuest for optimization

  • Based on SIMAN; embedded Visual Basic



Manufacturing & Materials handling

  • Manufacturing & Materials handling

  • Detailed large models for planning, decision support, control systems

  • AutoStat - Experimentation & analysis

  • AutoView - Make movies of 3D animations

  • Full simulation language included



Object oriented

  • Object oriented

  • Discrete Events

  • Open GL 3D visualization engine

  • 4D Script programming language

  • Interfaces with databases

  • OptQuest optimization



Block-diagram approach

  • Block-diagram approach

  • Versions for mixed and for continuous only

  • Includes C-like programming language

  • Supports linking to external languages



Dynamic-flow systems - manufacturing

  • Dynamic-flow systems - manufacturing

  • Discrete-event, Object-oriented simulator; developed in C++ using Open GL

  • Animation: 2D, 3D, Virtual reality

  • Drag & Drop



Manufacturing Systems

  • Manufacturing Systems

  • Simulation & Animation (2D & 3D)

  • Output viewer – graphs, tables

  • SimRunner – optimizer based on evolutionary algorithm technique

  • OptQuest is also available

  • MedModel, ServiceModel



Service industries, transaction processing

  • Service industries, transaction processing

  • Drop & Drag model development

  • Saves in XML format

  • Pre-built templates for common applications

  • 3D virtual reality graphics

  • Links to database



Included in most all simulation systems

  • Included in most all simulation systems

  • Add-ons also available

  • Features

    • Optimization – define fitness or cost function


Confidence intervals

  • Confidence intervals

  • Comparison of systems

  • Warm-up determinations

  • Graphs (all types) – 2D & 3D

  • Scenario definition



Warm-up determination

  • Warm-up determination

  • Steady state determination

  • Confidence intervals

  • Sensitivity analysis

  • Optimization via evolutionary strategy



Based on scatter search, tabu search, linear-integer programming, data mining, neural nets (evolutionary)

  • Based on scatter search, tabu search, linear-integer programming, data mining, neural nets (evolutionary)

  • Uncertainty problems

  • Global optimums

  • Handles non-linear and discontinuous relationships



Based evolutionary models & genetic algorithms

  • Based evolutionary models & genetic algorithms

  • Optimizations

  • 3D graphics

  • Warm-up (steady state) determination



Many simulation software environments available

  • Many simulation software environments available

  • Many do have trial versions to download for trying

  • Before deciding, consider the features and the add-ons available that will suit your particular environment




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