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Inside Discrete-Event Simulation Software: How It Works and Why It Matters

Inside Discrete-Event Simulation Software: How It Works and Why It Matters. Thomas J. Schriber, Daniel T. Brunner WSC05’ Presented by Geng Yue Mar 24. Syllabus. 1. Nature of discrete event simulation 2. Basic simulation constructs 3. Entity states 4. Entity management data structure

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Inside Discrete-Event Simulation Software: How It Works and Why It Matters

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  1. Inside Discrete-Event Simulation Software: How It Works and Why It Matters Thomas J. Schriber, Daniel T. Brunner WSC05’ Presented by Geng Yue Mar 24

  2. Syllabus • 1. Nature of discrete event simulation • 2. Basic simulation constructs • 3. Entity states • 4. Entity management data structure • 5. Specific implementations • 6. Why it matters

  3. 1. Nature of Discrete-Event Simulation • Event time: discrete; state: usually discrete • Transaction-flow world view: discrete units of traffic that move from point to point while competing for scarce resources • Two or more events often have to be manipulated at the same time point. How to order them? m1 l m2

  4. Discrete-Event Modeling Languages • There are different implementations, which aim to provide convenience for modelers. • Arena for example, provides graphical user interface for the users to input the simulation model.

  5. 2. Basic Simulation Constructs • Topics includes: • Entity – a unit of traffic • Resources – service machine • Control Elements – support delay or logical alternatives • Operations - an action for an entity

  6. Model Execution • The simulation advances with the simulation clock, which advances when an event happens • Carry out all possible actions at the current simulated time -> advance the simulated clock; and repeat; initialize event list get next (nearest future) event from event list time = event time process event (change state values, add/delete future events from event list update statistics n done?

  7. 3. Entity States • Active State: current moving state • Ready State: ready but wait due to limited resource • Time-Delayed State: entity waiting for a known future time so they can enter ready state • Condition-Delayed State: remove automatically when conditions permit • Dormant State: modelers set it

  8. 4. Entity Management Structure • Active State – kept in a list • Ready State – in current event list • Time-Delayed State – in future event list • Conditional-Delayed State – delay list • Dormant State – user-managed list • All these lists are used to store data and provide easy access to their elements

  9. 5. Different Implementation in Tools • The paper together with its WSC96’ version gives 6 representative implementations. • Two examples here: • AutoMod, version 9 (Phillips 1997) • Siman, the core of Arena • To get some intuitive, refer to “A Simple Simulation Language: simlib   P114” of the text book, which is around 30KB in C

  10. AutoMod Language

  11. Siman Language • It is the engine for Arena.

  12. 6. Why It Matters • Trying to re-capture a resource immediately • The first in line is still delayed • Yielding control • Conditions involving the clock • Mix Mode Waiting

  13. Why It Helps and Performance Issues • Why it helps: interactive model verification • Performance: given the same model, computer time depends on the design and implementation of the software used to build the model

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