Minimization - optimization alg. or equation alg.?

In summary, The conversation is about solving a minimization problem with constraints using either the Lagrangian method or an appropriate algorithm. The best approach depends on the specific problem at hand, but Lagrange multipliers are generally a good option.
  • #1
sodemus
29
0
Hello everybody!
I guess my question is mainly concerned with numerical algorithms...
Given a problem of the form
min w = f(x)
subject to
g1(x)=0
:
:
gn(x)=0
where x is a m x 1 vector, n < m.

From a numerical standpoint, how can I know whether it is preferably to solve it by setting up the Lagrangian and solve the resulting system of m + n non linear equations with appropriate algorithms OR to implement an appropriate algorithm to solve the minimization problem directly? As far as my particular problem goes, let's say n = 2 and m = 25.

Any help is more than appreciated!
 
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  • #2
If you had knowledge about the constraints, e.g. linearity, you could chose another approach. Without any further information, Lagrange multipliers should be fine.
 

1. What is minimization and optimization?

Minimization and optimization are methods used in mathematical and scientific fields to find the smallest or largest possible value of a function. This can be applied to various problems such as finding the shortest route or maximizing profits.

2. How do minimization and optimization algorithms work?

Minimization and optimization algorithms work by iteratively adjusting a set of parameters to minimize or maximize a given function. These adjustments are made based on the gradient or slope of the function, which helps the algorithm move towards the optimal solution.

3. What is the difference between minimization and optimization?

Minimization refers to finding the smallest possible value of a function, while optimization refers to finding the best possible value, which could be either the smallest or largest depending on the problem being solved.

4. How are minimization and optimization used in scientific research?

Minimization and optimization are commonly used in scientific research to find the optimal solutions to complex problems. This can be applied in various fields such as physics, chemistry, economics, and engineering.

5. What are some common minimization and optimization algorithms?

Some common minimization and optimization algorithms include gradient descent, Newton's method, and simulated annealing. These algorithms have different approaches and are suitable for different types of problems.

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