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Questions tagged [disciplined-quasiconvex-programming]

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7 votes
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Maximizing a Ratio/Percent

I'm using cvxpy to model a problem. Inside a very large and complex LP, I create two continuous, affine (unconstrained) expressions: $x$ and $y$. Due to how they ...
Adi Shavit's user avatar
5 votes
2 answers

Piecewise linear and global optimization

I am new to OR, and apologies if my mathematical notation is not clear. I have tried my best to keep it concise and given an explanation with numerical data. I would like to understand: Can this ...
Marry's user avatar
  • 81
5 votes
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How to write this objective in CVXPY for quasiconvex programming?

I have the following objective that I want to maximize: \begin{equation} \max_{U_T\in \mathbb{R}, x\in\mathbb{R}^T} J_\alpha(U_T) = \frac{\alpha}{\alpha-1}\log\left(\frac{\cosh(U_T)}{\cosh(\alpha U_T)^...
Uomond's user avatar
  • 86
3 votes
1 answer

On a clarification on usage of inequalities in convex programming

The inequality $x^3\leq y$ is not convex. But $0<x$ added to the above provides a convex region. My question is whether in convex programming it is allowed to use both inequalities together and use ...
Turbo's user avatar
  • 131
2 votes
1 answer

How to minimize a quasi-convex function in 2 dimensions?

I know that if $f$ is a quasi-convex function in one dimension (that is, $f: \mathbb{R} \to \mathbb{R}$), then we can use the 'golden section' line search to find the optimizer. Now suppose I have a ...
Karagounis Z's user avatar
2 votes
0 answers

How to linearize this multiplicative constraint?

I have a constraint in the form $\sqrt{|\sum_{c\in C}{h_cw_c}|^2}\ge\sqrt{x}\zeta$ Here, $h_c$ is s row vector (know), $w_c$ is a column vector (variable). $x$ and $\zeta$ are also optimization ...
KGM's user avatar
  • 2,377
1 vote
0 answers

Handling Variable Division in CVXPY for Calculating Annualized Rate of Change

I am working with a dataset that contains multiple entries for different IDs across various years. Some IDs might have a gap of years between entries. My goal is to solve an optimization problem using ...
user760900's user avatar
0 votes
1 answer

How is this problem quasi-convex?

I'm currently reading the following paper B. Sinopoli, L. Schenato, M. Franceschetti, K. Poolla, M. I. Jordan, and S. S. Sastry, “Kalman filtering with intermittent observations,” IEEE Transactions ...
mhdadk's user avatar
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