Question 1

When applying linear programming to diet problems,the objective function is usually designed to

Accepted Answer

A) maximize profits from blends of nutrients. 
B) maximize ingredient blends. 
C) minimize production losses. 
D) maximize the number of products to be produced. 
E) minimize the costs of nutrient blends. 
A) maximize profits from blends of nutrients. 
B) maximize ingredient blends. 
C) minimize production losses. 
D) maximize the number of products to be produced. 
E) minimize the costs of nutrient blends.

Question 2

When formulating transportation LP problems,the objective function usually deals with the

Accepted Answer

A) number of items to be transported. 
B) choice of transportation mode (e.g. ,truck,airplane,railroad,etc. ). 
C) shipping cost or distances associated with transporting goods. 
D) number of origins and destinations. 
E) capacities of origins and requirements of destinations. 
A) number of items to be transported. 
B) choice of transportation mode (e.g. ,truck,airplane,railroad,etc. ). 
C) shipping cost or distances associated with transporting goods. 
D) number of origins and destinations. 
E) capacities of origins and requirements of destinations.

Question 3

Table 8-5
Each coffee table produced by Timothy Kent Designers nets the firm a profit of $9.Each bookcase yields a $12 profit.Kent's firm is small and its resources limited.During any given production period (of 1 week),10 gallons of varnish and 12 lengths of high quality redwood are available.Each coffee table requires approximately 1 gallon of varnish and 1 length of redwood.Each bookcase takes 1 gallon of varnish and 2 lengths of wood.
T = number of tables produced each week
B = number of bookcases produced each week
-Referring to Table 8-5,which of the following constraints would be used?

Accepted Answer

A) 9T + 12B ≤ 12 
B) 1T + 1B ≥ 10 
C) 1T + 2B ≤ 12 
D) All of the above 
E) None of the above 
A) 9T + 12B ≤ 12 
B) 1T + 1B ≥ 10 
C) 1T + 2B ≤ 12 
D) All of the above 
E) None of the above

Question 4

Describe the production scheduling linear programming application.

Accepted Answer

a decision aid similar to the

Question 5

Describe the truck loading linear programming application.

Accepted Answer

a decision aid to de

When applying linear programming to diet problems,the objective function is usually designed to

When formulating transportation LP problems,the objective function usually deals with the

Describe the production scheduling linear programming application.

Describe the truck loading linear programming application.

Introduction to Quantitative Analysis

Probability Concepts and Applications

Decision Analysis

Regression Models

Forecasting

Inventory Control Models

Linear Programming Models: Graphical and Computer Methods

Transportation,assignment,and Network Models

Integer Programming,goal Programming,and Nonlinear Programming

Project Management

Waiting Lines and Queuing Theory Models

Simulation Modeling

Markov Analysis

Statistical Quality Control

Analytic Hierarchy Process

Dynamic Programming

Decision Theory and the Normal Distribution

Game Theory

Mathematical Tools: Determinants and Matrices

Calculus-Based Optimization

Linear Programming: The Simplex Method

Transportation, Assignment, and Network Algorithms

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Exam 8: Linear Programming Applications

When applying linear programming to diet problems,the objective function is usually designed to

When formulating transportation LP problems,the objective function usually deals with the

Describe the production scheduling linear programming application.

Describe the truck loading linear programming application.

Introduction to Quantitative Analysis

Probability Concepts and Applications

Decision Analysis

Regression Models

Forecasting

Inventory Control Models

Linear Programming Models: Graphical and Computer Methods

Transportation,assignment,and Network Models

Integer Programming,goal Programming,and Nonlinear Programming

Project Management

Waiting Lines and Queuing Theory Models

Simulation Modeling

Markov Analysis

Statistical Quality Control

Analytic Hierarchy Process

Dynamic Programming

Decision Theory and the Normal Distribution

Game Theory

Mathematical Tools: Determinants and Matrices

Calculus-Based Optimization

Linear Programming: The Simplex Method

Transportation, Assignment, and Network Algorithms

Filters