What is the Lagrange Multiplier

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The Lagrange multiplier is an auxiliary variable used in optimization problems with equality constraints, allowing the conversion of constrained problems into unconstrained ones. This technique simplifies the process of finding maxima or minima by introducing an additional unknown while eliminating the constraint. The discussion also touches on the relationship between Lagrange multipliers and Lagrange's equations of motion, noting that both involve constrained optimization principles. For a clearer understanding, familiarity with basic multivariable calculus is recommended, and examples can help illustrate the concept. Overall, Lagrange multipliers are a fundamental mathematical tool applicable in various fields, including economics and mechanics.
Samia qureshi
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Can anybody explain in simple and easy words "Lagrange Multiplier" What is it? and when it is used? i googled it but that was explained in much difficult words.
 
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The Lagrange multiplier is a additional auxiliary variable that appears when applying Lagrange's technique to solve an optimization problem with equality constraints by converting it to an unconstrained optimization problem. So: You get rid of the constraint at the cost of introducing an extra unknown.

To proceed, I think it is necessary to introduce notation for the function to be maximized (or: minimized) as well as the constraint(s). For this I could recommend the Wikipedia article, which seems quite accessible if you are familiar with some basic multivariable calculus.
 
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Also, since this is a homework thread, it may be useful to post an example of a problem that you are working on in this context, so it can serve as an illustration.
 
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Krylov said:
The Lagrange multiplier is a additional auxiliary variable that appears when applying Lagrange's technique to solve an optimization problem with equality constraints by converting it to an unconstrained optimization problem. So: You get rid of the constraint at the cost of introducing an extra unknown.

To proceed, I think it is necessary to introduce notation for the function to be maximized (or: minimized) as well as the constraint(s). For this I could recommend the Wikipedia article, which seems quite accessible if you are familiar with some basic multivariable calculus.

Isn't it similar to Lagrange equation of motions?
 
Samia qureshi said:
Isn't it similar to Lagrange equation of motions?
Lagrange's formulation of classical mechanics is indeed based on a constrained energy minimization problem (where the constraints are dictated by the system's geometry) and the equations of motion are obtained from the "Lagrangian". The Lagrangian also appears more generally in constrained optimization problems, also in unrelated fields such as economics, but of course there it has another role and interpretation.

Since you asked for an explanation in simple words, I am hesitant to go further, but if you indicate more about the background of your question, perhaps we can give more adequate answers.
 
I am afraid that a simple explanation does not exist. The so called Lagrange multipliers is a fundamental mathematical construction, it is the reason why this construction arises in very different branches of math.

Consider three vector spaces ##X,Y,Z## these spaces can be infinite dimensional; and two linear operators ##B:X\to Y## and ##A:X\to Z##

2db0204aead4.png


Assume also that ##B(X)=Y##.

Theorem. If ##\ker B\subset\ker A## then there exists a linear operator ##\Lambda:Y\to Z## such that ##A=\Lambda B##.

This theorem and its several versions (for Banach spaces and bounded operators etc) is a source of all Lagrage multipliers in different topics.
 
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Here is a little puzzle from the book 100 Geometric Games by Pierre Berloquin. The side of a small square is one meter long and the side of a larger square one and a half meters long. One vertex of the large square is at the center of the small square. The side of the large square cuts two sides of the small square into one- third parts and two-thirds parts. What is the area where the squares overlap?

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