Simulations - Industrial Engineering - Lecture Slides, Slides of Industrial Engineering

A process outlook for industrial engineering is actual course title. This lecture includes: Simulations, Hot Dog Sales, Hot Dog Sales Analysis, Developing a Model, Flight Simulators, Set of Processes, Computer Program, Simulation, Generating Randomness, Representation of Randomness

Typology: Slides

2012/2013

Uploaded on 10/01/2013

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Simulations

2

Hot Dog Sales

  • Revenue to carry out club activities
  • Basketball game – 10 games a year – all

are similar with respect to hot dog sales

(as all the tickets are sold out)

  • Facts:

Selling price of a hot dog: $ Buns ( “sandviç ekmeği”): $1. 44 /dozen Hot dogs can be bought: $6. 56 /dozen All unsold hot dogs are donated.

4

Hot Dog Sales (Analysis cont.)

Scenario 1:

  • Ordered (bought) 16 dozen of buns and

hot dogs. Sold 9 dozen. Profit?

  • Compute profit if 9 dozen were ordered.
  • What is the profit loss of over-ordering?

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Hot Dog Sales (Analysis cont.)

Scenario 2:

  • Ordered (bought) 9 dozen of buns and hot

dogs. Extreme demand of 14 dozen

(estimate, keep records) Profit?

  • Compute profit if 14 dozen were ordered.
  • What is the profit loss of under-ordering?

7

Hot Dog Sales - Simulation

  • One possibility: Create a demand randomly – if

hot dog is available sell it, otherwise do not. Record sales. Continue creating demands until game is over. Compute profit.

  • Other possibilities? Learn with simulation

modeling

  • What is the advantage? You can mimic the real

world in milliseconds, once the simulation is ready – computer lives faster!

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Key in simulation:

  • Generating randomness to represent sales

(or other things in general)

  • We do it several times for each set of

decisions, and select the one that gives

greater profits (hot dog case: how much to

order initially – just one decision variable)

  • Compute performance measures
  • This problem: Typical inventory decision

problem (how much to stock?)

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Modeling uncertainty in demand

  • For this case, I am telling you how to do it.

Learn next year

  • Roll three unbiased dice each with six

faces, numbered from 1 to 6 and add the

numbers. This represents the demand (in

dozens) for hot dogs (Computer can do be

very efficient and effective in this game).

  • Unbiased: For each die, the outcome is

equally likely.

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More on the demand for hot dogs

  • How many possible triplets?
  • Each triplet is equally likely
  • demand vs. number of triplets

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More on the demand for hot dogs

  • Comparison with data:
  • Minimum demand: 5 – 3 , 4 (4/216)
  • Maximum demand: 16– 17, 18 (4/216)
  • Average Demand: around 10 or 11– 10.
  • Most demand: between 9 and 12 (104/216)
  • Demand being less than 9 dozen or more

than 12 dozen was rare (56/216 each)

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Generalize randomness

representation

  • Demand value vs. proportion
  • Proportions add up to 1
  • Same computation can be made with an

arbitrary set of proportions

  • Called probability mass function - pmf (discrete),

or probability density function - pdf (continuous)

  • Randomness representation is identical to

selecting a pmf (or pdf)

  • Column G : Computation of Expected Value

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