# Questions tagged [numerical-optimization]

Numerical methods for continuous optimization.

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### Is there a way to identify singular points in a spectrahedron without finding the entire set?

I'm a physicist working in a non-linear optimization problem that reduces to a semidefinite program (SDP). In the simple low dimensional cases we workout in the research we could identify singular ...
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### Extracting diagonal of $J^TJ$ via automatic differentiation like techniques

First of all please, let me know if this question is more suited for scicomp.stackexchange.com or or.stackexchange.com, and ...
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### How to convert a semidefinite program to an optimization problem that can be solved by the ellipsoid method?

Suppose we have the following set of linear inequalities in $x \in \mathbb R^n$ \begin{aligned} a_1^T x &\leq b_1\\ a_2^T x &\leq b_2\\ &\vdots\\ a_k^T x &\leq b_k\end{aligned} ...
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### Optimization with probabilistic variable distribution

Let $u \in \mathcal{R}^n$ be a vector of decision variables. Let $C(u)$ be a function $\mathcal{R}^n \to \mathcal{R}$ that is a measure of performance of the variables. Further, it is required that ...
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### How to improve the numerical stability of the inverse rank-one Cholesky update?

I am trying to use the inverse Cholesky update from the page 10 of the Efficient covariance matrix update for variable metric evolution strategies paper as a part of the optimization step in a neural ...
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### When to use which “closed” Newton Cotes rule?

Given a set of datapoints, I was thinking about when to use which (closed) Newton-Cotes formula? I developed a decision tree which would go like this: Are the given datapoints equally spaced? ...
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### Solving mathematical optimization problems with nonnegative, non-analytical objective functions

I am studying a kind of nonlinear mathematical optimization problems where the objective functions are guaranteed to be nonnegative. In addition, the objective function is non-analytical; in fact, it ...
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### Adapting gradient descent for numerical functional optimization?

Let's say we have a functional $J[f] = \int_a^b L(x, f, f') dx$ that we are trying to minimize. I'm trying to think what is the best way to do this numerically, with something like gradient descent. ...
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### mating proposal for genetic algorithms

I am using a genetic algorithm to solve an optimization problem. However, I want a mating process that enables to create new solutions that are outside the range of current solutions. In the book: ...
I am currently working on a life cycle model about saving and investing for pension funds. However, I have some problems solving the model. The model runs for $T$ years over the life cycle. At every ...