Analysis Tools

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A question pack on design decisions in engineering.

Analysis Tools Q1

Estimates of risk can be made by ______________.

A

logic

B

statistical analysis

C

frequency

D

judgment

E

All of the above

Analysis Tools Q2

In database for Decision Supporting Systems, a data model ______________.

A

is a representation of the structure of a database

B

describes the categories of things that can exist in the database

C

are the things in each category that exist in the actual database at a given time

D

describes the database at a given time

E

describes the relationships that it can hold among entities

Analysis Tools Q3

In database for Decision Supporting Systems, a schema ______________.

A

is a representation of the structure of a database

B

describes the categories of things that can exist in the database

C

are the things in each category that exist in the actual database at a given time

D

describes the database at a given time

E

describes the relationships that it can hold among entities

Analysis Tools Q4

In database for Decision Supporting Systems, instance ______________.

A

is a representation of the structure of a database

B

describes the categories of things that can exist in the database

C

is the thing in each category that exists in the actual database at a given time

D

describes the database at a given time

E

describes the relationships that it can hold among entities

Analysis Tools Q11

In dynamic programming, problems are divided into a number of ______________.

A

decision stages

B

constraints

C

nodes

D

objectives

E

none of the above

Analysis Tools Q5

In dynamic programming, the output to stage n‑1 becomes the input to ______________.

A

stage n

B

stage n‑2

C

stage n+1

D

stage n+2

E

none of the above

Analysis Tools Q12

In multiobjective optimization, a noninferior solution Y for a given set of input X is ______________.

A

a solution that maximizes all objectives

B

a solution that minimizes all objectives

C

a solution such that no other feasible solution for the same input set X is better on all individual objectives

D

a solution such that no other feasible solution for the same input set X is worse on all individual objectives

E

None of the above

Analysis Tools Q6

In multiobjective optimization, the advantages of the weighting method include the following(s):

A

Less computing resources are required as compared with the constraint method.

B

A feasible solution always exists.

C

A complete description of the noninferior solutions is provided.

D

A and B

E

A, B, and C

Analysis Tools Q7

In multiobjective optimization, the constraint method ______________.

A

optimizes the weighted sum of the objectives, subjected to constraints on inputs

B

optimizes one objective while representing all other objectives as constraints

C

optimizes multiple objectives while representing one objective as constraints

D

optimizes the objectives, subjective to a weighted sum of the constraints

E

None of the above

Analysis Tools Q8

In multiobjective optimization, the weighting method ______________.

A

optimizes the weighted sum of the objectives, subjected to constraints on inputs.

B

optimizes one objective while representing all other objectives as constraints

C

optimizes multiple objectives while representing one objective as constraints

D

optimizes the objectives, subjective to a weighted sum of the constraints

E

None of the above

Analysis Tools Q9

In relational database, a ______________ operation forms a new table by combining records from two tables that match on a common attribute.

A

“select”

B

“project”

C

"join”

D

“union”

E

“difference”

Analysis Tools Q10

In relational database, a ______________ operation forms a new table containing all rows in the first table but not in the second (tables must match on all attributes).

A

“select”

B

“project”

C

“join”

D

“union”

E

“difference”

Analysis Tools Q22

In ______________ , feasible space consists of integer variables.

A

linear programming

B

nonlinear programming

C

integer programming

D

goal programming

E

dynamics programming

Analysis Tools Q13

Linear programming assumes ______________ .

A

certainty

B

linearity

C

D

divisibility

E

all of the above

Analysis Tools Q14

The risk avoider ______________.

A

prefers uncertain amounts that have an expected value equal to the certain amount

B

prefers certain amounts over uncertain amounts with the same expected value

C

is indifferent, or has a tie in terms of preference, between the two

D

all of the above

E

none of the above

Analysis Tools Q15

Utility theory ______________.

A

incorporates our attitude toward risk into the decision‑making process

B

measures risk

C

is a decision support tool that uses a tree‑like graph or model of decisions and their possible consequences

D

all of the above

E

none of the above

Analysis Tools Q16

Which of the following constraints is typical for a resource‑allocation problem?

A

$>$=

B

<=

C

=

D

none of the above

E

all of the above

Analysis Tools Q17

Which of the following is a method for solving a multiobjective optimization problem?

A

Weight sum

B

Weighted exponential sum

C

Lexicographic

D

Tchebycheff

E

All of the above

Analysis Tools Q18

Which of the following is not a component of a linear programming model?

A

Decisions

B

C

Data

D

Measures of performance

E

Constraints

Analysis Tools Q19

______________ cannot fit naturally into a relational model.

A

Complex constraints

B

C

Subtypes that share some but not all structure and features of parent type

D

Context‑dependent structure

E

All of the above

Analysis Tools Q20

Company A produces two products X and Y. Each X requires 4 units of material C and each Y requires 7 units of material C. The total amount of material C available for each month is 5000. Let x and y be the number of X and Y produced in a month. If we want to optimize products of X and Y, what is the appropriate constraint on material C?

A

4x+7y > 5000

B

4x+7y <= 5000

C

7y > 5000

D

4x > 5000

E

4x = 7y

Analysis Tools Q21

Hotel A is a one‑star hotel, located 0.7 miles from the beach and costs $12 a night. Hotel B is a three‑star hotel, located 0.2 miles from the beach and costs$1,500 a night. Hotel C is a two‑star hotel, located 0.5 miles from the beach and costs $1,000 a night. Hotel D is a three‑star hotel, located 0.6 miles from the beach and costs$2,000 a night. Hotel E is a two‑star hotel, located 1.5 miles from the beach, and costs \$1,100 a night. We want to find a hotel that has the most stars, closer to the beach, and less expensive. Find the Pareto optimal solution.

A

Hotel A

B

Hotel B

C

Hotel C

D

Hotel D

E

Hotel E

Analysis Tools Q23

Solve the following optimization problem: Maximize Y, which is subjected to the following constraints: (i) X – 2Y ≥‑1, (ii) X ≤ 2, (iii) X ≥ 0 and (iv) Y ≥ 0. Find the optimum.

A

X = 2, Y = 1.5

B

X = 2, Y = 1

C

X = 0, Y = 0

D

X = 1, Y = 2

E

X = 0, Y = 1

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