Event-Scheduling View

Event-Scheduling View

• Event-Scheduling View

• As with our project 1
• Focus on processing each event

• 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

• Based on block diagrams
• Well-suited for queuing models
• Expensive at first

• 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