Maximizing Income: Algebra II Problem Solving Tips

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The discussion focuses on solving a linear programming problem to maximize income from two models of light fixtures, A and B. The assembly and packaging times for each model are provided, along with the weekly limits for assembly and packaging hours. The objective function for income is established as 1.5a + 1.7b, where 'a' and 'b' represent the number of each model produced. Constraints are set based on the available assembly and packaging time, leading to a feasible region that can be graphed to find optimal solutions. The method involves testing the corners of this region to determine the best production quantities for maximizing income.
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Homework Statement


A company makes two models of light fixtures, A and B, each of which must be assembled and packed. The time required to Assemble model A is 12 minutes, and model B takes 18 minutes. It takes 2 minutes to package model A and 1 minute to package model B. Each week there are an available 240 hours of assembly time and 20 hours for packaging.

If model A sells for $1.50 and model B sells for $1.70, how many of each model should be made to obtain the maximum weekly income?

Homework Equations



I remember doing problems like this in Algebra II last year. Unfortunately, I completely forget how to set up problems like this.

The Attempt at a Solution



I can't think of a way to solve it. I don't have my notes from last year either :frown:.

All I really need is the method to solving this type of problem.
 
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Welcome to PF!

Hi Superstring! Welcome to PF! :smile:
Superstring said:
A company makes two models of light fixtures, A and B, each of which must be assembled and packed. The time required to Assemble model A is 12 minutes, and model B takes 18 minutes. It takes 2 minutes to package model A and 1 minute to package model B. Each week there are an available 240 hours of assembly time and 20 hours for packaging.

If model A sells for $1.50 and model B sells for $1.70, how many of each model should be made to obtain the maximum weekly income?

Basically, just say that there are a of A, and b of B, calculate the profit, and find an equation that specifies "Each week there are an available 240 hours of assembly time and 20 hours for packaging" :wink:
 
This is an example of something called a Linear Programming Question. You are being asked to optimize (in this case maximize) income, which will become the objective function. You are given two features (assembling and packing) that will form constrainsts on the variables. Since these quantities represent physical objects then their number must be non-negative.

If you let a be the number of units of type A, and similarly for b, then we get:

Objective function: \text{Income}=1.5a+1.7b

Constraints:

Assembly: 12a+18b\leq 240(60)=14,400

Packing: a+2b \leq 20(60)=1200

Practical: x,y \geq 0

(Note there are 60 minutes in an hour - watch your units.)

Graphing the constraints in the xy-plane will form a "freasible region," the corners of which are the only candidates for being optimal solutions (maximal in this case).

Graph the region.
Find the corners.
Test the corners in the objective function.
Determine the optimal solution point.
Answer the question.

I hope this helps.

--Elucidus
 
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Elucidus said:
This is an example of something called a Linear Programming Question. You are being asked to optimize (in this case maximize) income, which will become the objective function. You are given two features (assembling and packing) that will form constrainsts on the variables. Since these quantities represent physical objects then their number must be non-negative.

If you let a be the number of units of type A, and similarly for b, then we get:

Objective function: \text{Income}=1.5a+1.7b

Constraints:

Assembly: 12a+18b\leq 240(60)=14,400

Packing: a+2b \leq 20(60)=1200

Practical: x,y \geq 0

(Note there are 60 minutes in an hour - watch your units.)

Graphing the constraints in the xy-plane will form a "freasible region," the corners of which are the only candidates for being optimal solutions (maximal in this case).

Graph the region.
Find the corners.
Test the corners in the objective function.
Determine the optimal solution point.
Answer the question.

I hope this helps.

--Elucidus

Thank you so much. You made it all come back to me.
 
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