State University of New York at Oswego



    

  1.  COURSE NUMBER AND CREDIT  
    2. 

    
 CSC 454 - 3 Semester Hours

    


  2.  COURSE TITLE 
    3. 

    
 System Simulation and Modeling

    


  3.  COURSE DESCRIPTION 
    4. 

    
          Simulation, modeling and problem-solving techniques; 
          discrete event and continuous change models; 
          simulation languages; simulation applications.

    


  4.  PREREQUISITES 
    5. 

    
 CSC 241, MAT 215 and at least one upper-level programming course.

    



  5.  COURSE JUSTIFICATION 
    6. 
 
    
        The course provides students with the basic knowledge
        and experience necessary to utilize computer
        simulation as a tool for system modeling and problem solving.  The
        technical aspects of constructing and analyzing a
        simulation model will be discussed, along with the
        implementing the basic components of a discrete-event simulator.
        The students will be exposed to a wide variety of
        computer simulation applications.


    
Software Engineering Curriculum Justification: This course provides
in-depth content-oriented coverage of software requirements,
design, construction, analysis, testing, tools, and project management.



  6.  COURSE OBJECTIVES 
    7. 
 
    
Upon successful completion of this course, students will be able to:

    

      

    1.   Model a real-life system, including data gathering,
            input and output analysis.

    2.  Write a discrete-event simulator.

    3.  Apply knowledge of data structures, algorithms, discrete
math, probability, and user interfaces for simulation

    4.  Evaluate the correctness and validity of simulations

    5.  Communicate the rationale and design of a simulation program.

    


    

  7.  COURSE OUTLINE 
    8. 

      

    1.  Continuous Time Simulation
   
         
   
      1.  Examples of Physical Systems
   
      2.  Approximation by Finite Differences
   
      


    2.  Introduction to Discrete-Event System Simulation
   
        
   
      1.   Simulation examples: queueing and inventory systems 
   
      2.   Concepts discrete-event simulation:  event list, event-scheduling, and
         time advance algorithms
   
      

    3.  Statistical Models in Simulation
   
        
   
      1.   Discrete and continuous distributions
   
      2.   Poisson process
   
      3.   Empirical distributions
   
      4.   Useful statistical models
   
      

    4.  Queueing Models
   
        
   
      1.   Characteristics of queueing systems and queueing notation
   
      2.   Long-run measurements of performance
   
      3.   Steady state behaviors of infinite- and finite-population models
  
      

    5.  Random Numbers
   
        
   
      1.  Properties of random number generators
   
      2.  Techniques for generation of pseudo-random numbers
   
      3.  Tests for random numbers
   
      4.  Random Variate Generation
   
      

    6.  Engineering Simulation Software
   
        
   
      1.  Creating Requirements
   
      2.  Input modeling:  data collection, identification of the distribution,
        parameter estimation, goodness-of-fit tests.
   
      3.  Verification and validation of simulation models:  model building, verification,
        calibration and validation of models.
   
      4.  Output analysis: measures of performance and their estimation, terminating and
        steady-state simulations
   
       

    

    



  8.  METHODS OF INSTRUCTION 
    9. 

     

      
 
    1.  Lectures.
 
    2.  Discussion.

    

    



  9.  COURSE REQUIREMENTS 
    10. 

     
        Assigned readings, homework, papers, programs, and projects.
The main project entails requirements and data gathering,
selection among available simulation techniques,
implementation and evaluation.

    


  10.  MEANS OF EVALUATION 
    11. 

    

      

    1.  Homework, exams, programming assignments, programming project, modeling project

    


    


  11.  RESOURCES 
    12. 

    
         No additional resources needed.

    


  12.  BIBLIOGRAPHY 
    13. 




    
          J. Banks (ed).
          Handbook of Simulation:  Principles, Methodology, Advances, Applications,
            and Practice.
          John Wiley,
          New York,
          1998.


    

          J. Banks, J.S. Carson, II, B.L. Nelson and D.M. Nicol.
          Discrete-Event System Simulation.
            Prentice Hall,
            New Jersey,
            2000.


    

          C. Hanell, B.K. Ghosh and R Bowden.
          Simulation Using ProModel.
          McGraw Hill,
          Boston,
          2000.


    


          W.D. Kelton, R.P.Sadowski and D.A. Sadowski.
          Simulation with Arena.
            McGraw Hill,
            Boston,
            1997.


    
          A.M. Law and W.D. Kelton.
          Simulation Modeling and Analysis, (3rd ed).
          McGraw Hill,
          Boston,
          2000.


    

          S.M. Ross.
          Simulation.
          Academic Press,
          MA,
          1997.


    

          J.R. Thompson.
          Simulation: A Modeler's Approach.
          John Wiley and Sons,
          New York,
          1999.


    



  13. SIGNATURES
    14. 
    
    
  





                                                                                         
      Elaine Wenderholm, Computer Science Curriculum Committee Chair           Date



                                                                                         
      Rameen Mohammadi, Computer Science Department Chair                      Date



                                                                                        
                          Undergraduate Curriculum Committee Chair             Date






 





 
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