Linear Programming Production Line

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SUMMARY

This discussion focuses on solving a linear programming problem for a manufacturing plant contracted by Apple to produce iPhones and iPods. The profit per iPhone is $50 and per iPod is $30, with constraints of 480 minutes of skilled labor and 2,000 minutes of machine use. The production requirements are 2 minutes of skilled labor and 6 minutes of machine use for each iPhone, and 1 minute of skilled labor and 10 minutes of machine use for each iPod. The objective function and constraints must be clearly defined to determine the optimal production quantities of iPhones and iPods.

PREREQUISITES
  • Understanding of linear programming concepts
  • Familiarity with objective functions and constraints
  • Basic knowledge of inequalities and feasible regions
  • Ability to interpret production requirements and profit calculations
NEXT STEPS
  • Learn how to formulate linear programming problems using the Simplex method
  • Study graphical methods for solving linear programming problems
  • Explore software tools like LINDO or MATLAB for linear programming
  • Investigate the concept of feasible regions and vertices in optimization
USEFUL FOR

Students in operations research, manufacturing managers, and anyone involved in optimizing production processes through linear programming techniques.

masrad
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I have absolutely no ides where to go from here, I am horrible at this, If you could help me I would appreciate it, I want help doing it, not just answers.

Homework Statement


You are the owner of a manufacturing plant. We've been hired by Apple to produce iPhone and iPods. Apples pays us $50 for every iPhone and $30 for every iPod. The constraints are that I only have 480 minutes of skilled labor and 2,000 minutes of machine use.

The iPhones require 2 minutes of skilled labor and 6 minutes of machine use time.
The iPods require 1 minute of skilled labor, and 10 minutes of machine use time.

In TOTAL, I can only make 250 unitsP= Profit
A= iPhone
B= iPod

The Attempt at a Solution



a = 2(skilled) + 6(machine) + 50(profit)
b = 1(skilled) + 10(machine) + 30(profit)
 
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masrad said:
I have absolutely no ides where to go from here, I am horrible at this, If you could help me I would appreciate it, I want help doing it, not just answers.

Homework Statement


You are the owner of a manufacturing plant. We've been hired by Apple to produce iPhone and iPods. Apples pays us $50 for every iPhone and $30 for every iPod. The constraints are that I only have 480 minutes of skilled labor and 2,000 minutes of machine use.

The iPhones require 2 minutes of skilled labor and 6 minutes of machine use time.
The iPods require 1 minute of skilled labor, and 10 minutes of machine use time.

In TOTAL, I can only make 250 units


P= Profit
A= iPhone
B= iPod
Much better to write full sentences in order to be clear and precise. I presume that what you mean is that you can make P dollars if you make A iphones and B ipods.




The Attempt at a Solution



a = 2(skilled) + 6(machine) + 50(profit)
b = 1(skilled) + 10(machine) + 30(profit)
Again, you haven't defined your terms. Are "a" and "b" the same as "A" and "B"? If so that makes no sense. Those numbers look like the numbers given in how many minutes are required to make an iPhone or iPod. But then those are NOT equations. It looks like you are multiplying "2" by "skilled" and that is meaningless. And you certainly cannot add "minutes" and "dollars".

Let A be the number of iPhones made and let B be the number of iPods made. How much money would you make? That is the "object function".

How many minutes of skilled labor would be required? That must be larger than or equal to 0 and less than or equal to 480.

How many minutes of machine time would be required? That must be larger than or equal to 0 and less than or equal to 2000.

The total number of units made, A+ B, must be greater than or equal to 0 and less than or equal to 250.

The two inequalities define your "feasible region". The basic theorem of Linear programing is that max or min of a linear object function occur at the vertices of a convex polygonal feasible region.
 

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