Theory Flashcards

1
Q

What is a Mathematical Problem and what is its purpose?

A
  • A math model is a quantitative representation of a real problem
  • The purpose is to represent the problem in a concise form
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2
Q

What are the types of models? Elaborate

A
  • Descriptive models; simply describe a situation
  • Optimization model: model that suggest a desirable course of action
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3
Q

What are the proprieties of Linear Programming?

A

1) Proportionality
2) Divisibility
3) Additivity

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4
Q

Proportionality

A

Proportionality means that if the level of any activity is multiplied by a
constant factor, the contribution of this activity to the objective, or to any
of the constraints in which the activity is involved, is multiplied by the same
factor.
* Proportionality is a perfectly valid assumption in the product mix model,
but it is often violated in certain types of models.
* For example, in various blending models used by petroleum companies, chemical
outputs vary in a nonlinear manner as chemical inputs are varied.

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5
Q

Additivity

A

The additivity property implies that the sum of the contributions from the various activities to a particular constraint equals the total contribution to that constraint.
* The additivity property implies that the contribution of any decision
variable to the objective or to any constraint is independent of the levels of the other decision variables

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6
Q

Divisibility

A

The divisibility property simply means that both integer and non-integer
levels of the activities are allowed.
* In general, if you want the levels of some activities to be integer values,
there are two possible approaches:
1. You can solve the LP model without integer constraints, and if the solution turns
out to have fractional values, you can attempt to round them to integer values; or
2. You can explicitly constrain certain changing cells to contain integer values.

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7
Q

What are the 2 things that can go wrong in Solver? Elaborate

A
  • Unboundedness; it be large or small as you like – the objective function
  • Infeasibility- no feasible solution
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8
Q

Examples of LP applications

A

1) Blending model
2) Investment plan
3) Production process plan

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9
Q

What is a node?

A

Geographical location

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10
Q

what is an arc and arca capacity?

A
  • An arc, indicated by an arrow,
    generally represents a route for
    getting a product from one node
    to another.
  • Upper limits are called arc
    capacities, and they can also be
    shown on the model.
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11
Q

what is flow?

A

The decision variables are usually
called flows. They represent the
amounts shipped on the various
arcs. They can also contain the
unit shipping costs.

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12
Q

What is an inflow?

A
  • An arc pointed into a node
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13
Q

What is an outflow?

A
  • An arrow pointed out of a node
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14
Q

What is required for a typical transportation problem?

A
  • capacities (or supplies),
  • demands (or requirements), and
  • unit shipping (and production)
    costs.
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15
Q

What lines are the feasible solution in a graph? integer model

A

vertical lines

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16
Q

LP Relaxation

A

gives the upper bound of the integer optimal solution

17
Q

Maximization IP

A

rounding down gives a feasible solution

18
Q

Minimization IP

A

round up gives a feasible solution

19
Q

Branch and Bound

A

solution procedure used by solver.

20
Q

What is the incumbent solution?

A

The best solution so far. It represents the lower bound. The upper bound is more difficult to find (not in our class scope)

21
Q

Application of Integer Programming

A

Fixed Cost
Capital Budjeting

22
Q

convex function

A

In NLP, A function of one variable is convex in a region if its slope (rate of change) in that region is always nondecreasing.
Equivalently, a function of one variable is convex if a line drawn connecting two points on the curve lies above the curve.

23
Q

Concave function

A

The function is concave if its slope is always nonincreasing, or equivalently, if a line
connecting two points on the curve never lies above the curve.
Equivalently, a function of one variable is concave if a line drawn connecting two points on the curve lies below the curve.