Maximizing problem with an inequality constraint.

In summary, The problem involves maximizing a function with an inequality constraint. The first two possibilities are ruled out and in the third one, the value of lambda is 2. The value of x2 is determined to be 10 in this case, leading to a maximum value of 20 for the function y=2*x2.
  • #1
Rabolisk
6
0
Hello I have a worked example where I have to maximize a function with an inequality constraint. The problem is worked out below.

https://zgqqmw.sn2.livefilestore.com/y1pLc13HVWpA9dATZEzikySeSMBN2hn1mJCw71rJ5vvUJcr9W7KBPFkOz7HQEppa6EPbLi5yyAwDagh3ezF_7eyVL6tBK7q6ise/maxProbem.png?psid=1

I know how to get the kuhn-tucker conditions in the first step. I also understand how the first two possibilities (i) and (ii) are ruled out. In the third one the value of [itex]\lambda[/itex] is 2. But how did the problem work out the value of and x2 to be 10?

Thanks.
 

Attachments

  • maxProbem.png
    maxProbem.png
    51.3 KB · Views: 575
Last edited by a moderator:
Physics news on Phys.org
  • #2
In case (iii), x_1=0. Why not just go back to the original conditions, you are trying to maximize y=2*x_2 subject to the constraint x_2<=10, so clearly we have a max when x_2=10, thus y=20.
 

1. What is an inequality constraint?

An inequality constraint is a restriction on the possible values of one or more variables in a problem. It is represented by an inequality, such as x < 5, and limits the feasible solutions to those that satisfy the given inequality.

2. Why is maximizing with an inequality constraint important?

Maximizing with an inequality constraint is important because it allows us to find the optimal solution to a problem while also considering any limitations or restrictions on the variables. This ensures that the solution is both efficient and feasible.

3. How do you solve a maximizing problem with an inequality constraint?

To solve a maximizing problem with an inequality constraint, you can use methods such as linear programming or calculus. These methods involve setting up the objective function and the inequality constraint, and then finding the values of the variables that maximize the objective function while satisfying the constraint.

4. Can the inequality constraint be a range instead of a single value?

Yes, the inequality constraint can be a range, such as 2 ≤ x ≤ 10. This means that the variable must be within the specified range in order for the solution to be feasible.

5. What is the difference between a hard and a soft inequality constraint?

A hard inequality constraint is a restriction that must be satisfied in order for the solution to be feasible. In contrast, a soft inequality constraint is a preference or goal that can be violated if necessary, but the solution is considered better if it is satisfied. Soft inequality constraints are often used in multi-objective optimization problems.

Similar threads

  • Calculus and Beyond Homework Help
Replies
2
Views
379
  • Computing and Technology
Replies
20
Views
2K
Replies
2
Views
2K
Replies
1
Views
1K
  • Advanced Physics Homework Help
Replies
2
Views
1K
  • Calculus and Beyond Homework Help
Replies
3
Views
747
  • Calculus and Beyond Homework Help
Replies
8
Views
466
  • Advanced Physics Homework Help
Replies
5
Views
1K
  • Calculus and Beyond Homework Help
Replies
6
Views
1K
Replies
2
Views
841
Back
Top