midterm 1 specific practice Flashcards

1
Q

Name the five elements of a descision model

A

decision variables, parameters, constraints, outputs, objective functions

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2
Q

Describe decision variables

A

represents quantities that can control or change(things the solver finds and fills in yellow cells)

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3
Q

Describe parameters

A

inputs that influence decision making but cannot control (blue colored cells, values given to us)

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4
Q

Describe outputs

A

results that model predicts based on decision variables and parameters( i think all outputs the solver fills in)

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5
Q

Describe objective function

A

outputs that represent measures of performance (the green revenue cell)

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6
Q

Describe contraints

A

interaction of inputs that limit feasibility of decisions (the blue cells that have conditional operators with other blue cells typically)

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7
Q

Optimization: describe optimization given a set of parameters

A

finding the best feasible combination of values for the decision variables

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8
Q

Describe a feasible combination of values for the decision variables

A

one that meets all the constraints of the model

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9
Q

The objective function determines what is best in terms of either ____ or ___ it’s value

A

maximizing or minimizing

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10
Q

Not all mathematical models are optimization models, true or false?

A

true, some just descrbie logical relationship between inputs and outputs

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11
Q

list the color of cells for Parameter, Decision Variable, Objective function (output), Calculation

A

blue, yellow, green, white

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12
Q

What are the three key questions to ask first?
What are the ___ to be made?
What are the ___ on these descisions?
What is the overall _____ for these decisions?

A

decisions, constraints, measure of performance?

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13
Q

Example Maximization and Feasibility: Regarding the diagram of feasibility range, what points would be the optimal solutions?

A

the corner points

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14
Q

Regarding graph and Feasibility: What does it mean to have redundant constriants?

A

a feasibility line or constraint that is outside feasibility already, but could become relevant later

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15
Q

Name the four Special conditions in LP Models

A

multiple optimal solutions, redundant constraints, unboundedness, infeasibility

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16
Q

Describe multiple optimal solutions

A

graph, when there is a line segment same as objective function instead of point so it has multiple optimal solutions

17
Q

Describe redundant constraints

A

a feasibility line that doesnt effect current feasibility

18
Q

Describe unboundedness

A

no limits, goes to infinite

19
Q

Describe infeasibility

A

constraints to not define any feasible region, check sign of operation

20
Q

List the types of models: Allocation Model, Covering, Blending, Transportation and assignment, transshipment, multiperiod and inventory models, netwrok models with yield, cash flow problem,

A

Allocation Model, Covering, Blending, Transportation and assignment, transshipment, multiperiod and inventory models, netwrok models with yield, cash flow problem,

21
Q

List the types of models

A

Allocation Model, Covering, Blending, Transportation and assignment, transshipment, multiperiod and inventory models, netwrok models with yield, cash flow problem,

22
Q

Describe Allocation Model

A

Maximizing and objective, with less than constraints on capacity

23
Q

Describe Covering problems

A

minimizing, subject to greater than or equal constrains on coverage

24
Q

Describe Blending problems

A

nonlinear, convert to linear constraints

25
Q

Transportation and assignment models: Describe network models

A

linear programs with special structure, describes configurations of flow in a connected system (nodes and arcs)

26
Q

Describe transshipment model

A

Multiple stages of flow (multiple nodes) instead of just one

27
Q

Describe multiperiod and inventory models

A

flow and network but with multiple periods, with conservation of flow