Questions tagged [robust-optimization]
The robust-optimization tag has no usage guidance.
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Robust Linear Optimization for avoiding diminishing returns
My engineering problem can be formulated as an LP as shown below
\begin{align}
\max_{\mathbf{x}}~~&\mathbf{a}^T\mathbf{x} \\
\mbox{s.t.}~~~&\mathbf{b}^T\mathbf{x} \leq B~~,~~\mathbf{1}^T\...
2
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0
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Does YALMIP allow a user-defined function for the objective function and constraints?
I have a robust optimization problem where the decision variable is a matrix, and the uncertain parameter is a vector. My matrix is L, and the uncertain parameter ...
8
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3
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Difference between "Online Optimization" and "Stochastic Optimization"/"Robust Optimization"?
I just came across the notion of Online optimization (I got a look on Wikipedia page and some other webpages), but it was not enough for me and I am looking for a more elaborated comparison, namely in ...
2
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1
answer
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Can we take the constraints from one model and plug them into the other model in pyomo?
I am implementing data-driven robust optimization methodology introduced in this article in python. Somewhere of the method, I need to use pyomo for each constraint whose parameters are uncertain to ...
3
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0
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Derivative of sup(max) functions in distributionally robust optimization
In the distributionally robust optimization problem
\begin{aligned}
\min_{x\in X}\sup_{P\in\mathfrak{P}}\mathbb{E}_P[f(x,\xi)],
\end{aligned}
where $f:\mathbb{R}^n\to\mathbb{R}$ and $P$ is a ...
2
votes
1
answer
107
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Numerical problem regarding to classical benders cut of large scale problem
I am trying to implement benders decomposition for a simple two stage unit commitment problem. I implemented the classic Benders decomposition to add feasible cut and optimal cut to relax master ...
4
votes
1
answer
70
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Identify the specific parameters that reached their worst case in a robustly optimal solution
Assuming that we have a linear math model with $N$ bounded $[0,1]$ uncertain parameters $p_n$ within a typical polyhedral budget uncertainty set that says $\sum_{n}{p_n} \le \Gamma$.
I want to find ...
9
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1
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How is optimization under uncertainty done in real world applications?
In this post What is robust optimization? there is a nice introduction to robust optimization.
There are many concept for uncertainty in optimization problems like
robust optimization
stochastic ...
6
votes
1
answer
335
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What is intended when we use "robustness", "resilience" and "reliability" in Operations Research?
I will use an example to detail my question but I would like you to keep in mind that I wanted to define:
Robustness,
Resillience,
Reliability
in the most general case within Operations Research.
...
6
votes
1
answer
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Is JuMPeR good enough for Robust Optimization problem?
I'm a graduate student studying Robust Optimization (RO).
So far, I've been studied the theoretic point of RO, and now I am looking for an actual tool for solving RO problems, both for practice and ...
8
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349
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What is robust optimization?
What is the academic definition of robust optimization?
What are examples of robust optimization on:
shift rostering
vehicle routing problem
facility location problem
bin packing
...
3
votes
1
answer
113
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Robust/Stochastic optimization deployed in real-world systems/applications
In an applied project we are working on currently, we want to use robust or stochastic programming in order to enhance the performance of the systems (by reference to certain metrics). As you may ...
21
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3
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Difference between stochastic optimization and robust optimization
I would like to know whether stochastic optimization and robust optimization are the same and if not, what is the main difference between them. I did an Internet search and I found the following ...
13
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1
answer
193
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Robust counterpart: why is dual reformulation not working?
I am trying to solve robust optimisation problems, but I am getting nonsensical solutions most of the time… Here is a very simplified example:
\begin{alignat}{2}\max&\quad x+z&\\\text{s.t.}&...
7
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Calculating robustness of layout plans
We have tried to design a manufacturing cell which will produce specific families of products. We figure out three layout plans for implementation. For practical reasons, we need to calculate the ...
16
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Modeling the uncertainty of the input parameters
There are many approaches to deal with the uncertainty such as stochastic programming, robust optimization and fuzzy programming. Finding a suitable approach that is applicable in the real situations ...