midterm 1 specific practice Flashcards

(27 cards)

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
Transportation and assignment models: Describe network models
linear programs with special structure, describes configurations of flow in a connected system (nodes and arcs)
26
Describe transshipment model
Multiple stages of flow (multiple nodes) instead of just one
27
Describe multiperiod and inventory models
flow and network but with multiple periods, with conservation of flow