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Unanswered Questions

33 questions with no upvoted or accepted answers
9 votes
0 answers
230 views

Solving large-scale stochastic mixed integer program

What are some methods or algorithms for solving a large-scale stochastic mixed-integer optimization problem that runs on an hourly dataset for a year? Do we employ some kind of decomposition? (the ...
6 votes
0 answers
226 views

Airline revenue management re-solving problem

I am considering a bid prices (shadow price of the capacity constraint) problem (from Chen, L. and Homem-de Mello, T. (2009)., page 14) where the acceptable classes for booking requests for ...
6 votes
0 answers
95 views

Sample Average Approximation vs. Numerical Integration

In the sense of the calculation of the expected value of objective functions, we have two choices to evaluate the value; 1. Sample Average Approximation (SAA): $$ \frac{1}{N}\sum_{i=1}^N f(x,\xi^i). $$...
5 votes
0 answers
154 views

Chance constrained optimization - interpretation

Suppose that we have a stochastic vector $\psi$ and $S$ realisations of $\psi$ given by $\psi_1,\dots,\psi_S$ with equal probability of occurrence. In addition, we have constraints of the form \begin{...
5 votes
0 answers
54 views

What kind of algorithm is this: water foraging

I am pondering if a machine learning problem might be better formulated as a reinforcement or control problem. I have no experience with the latter, so bear with me. Let's say I am organising a tour ...
5 votes
0 answers
44 views

In a binary logistic regression context, how to introduce a constraint to model the dependency between consecutive samples

Imagine we are running a logistic regression to identify opportunities for car sale promotion, using previous promotion campaign's result. Each $y$ is the increase of car sale after the promotion. ...
4 votes
0 answers
164 views

Stochastic optimization for inventory management

The deterministic problem is to minimize operational cost subject to constraints in demand, supply and capacity. The ordering policy is periodic review, order-up-to. The stochastic version of the ...
4 votes
0 answers
54 views

How to find range of values for the first-stage decisions resulting in the same cuts in two-stage stochastic programming?

Suppose we have a two-stage stochastic program as follows: \begin{equation} \begin{split} \min \ & c^Tx + \mathbb{E}_\xi[Q(x,\xi)] \\ & \text{where}\\ &Q(x,\xi)=\min q(\xi)^Ty\\ &Tx+...
3 votes
0 answers
50 views

Control variables and cofounding effects in stochastic programming/,model predictive control/reinforcement learning

How can we be sure that confounding variables/control variables don’t pickup the effect our decisions w.r.t decision variables had on the actual control variable? Since the term control variable ...
3 votes
0 answers
32 views

How to establish the optimal value functions and optimal control policy for a controlled random walk problem?

Question: How to establish an explicit characterization of both the optimal value functions and the optimal control policy for a controlled random walk? Background: Assume our system is a perfectly-...
3 votes
0 answers
89 views

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
0 answers
86 views

Reformulate the deterministic equivalent model as an Expected Value problem

Given an optimization problem as follows: $$ \begin{array}{cc} \operatorname{Max} Z=3 x_{1}+9 x_{2}-2 y_{1}-4 y_{2} \\ \text { subject to, } y_{1}+y_{2}=15 \\ 5 x_{1}+2 x_{2} \leq 10 \\ x_{1}, x_{2}, ...
2 votes
0 answers
100 views

Two-stage stochastic with non-linear recourse

I am working on a two-stage facility location problem as I described in this question. I am solving it with the L-shaped method (Benders decomposition). The cost value between each $(i,j)$ is a ...
2 votes
0 answers
312 views

What is the intuition behind Progressive hedging algorithm?

I am reading some papers about PHA to solve multi-stage stochastic programming, but I think it is not still clear to me. This is my understanding and I would be thankful to know if it is correct or ...
2 votes
0 answers
812 views

How to write nonanticipativity constraints?

In Multi-stage stochastic programming, we write the constraints that for scenarios $s$ and $s^{\prime}$ which have the same trajectory up to time $t$, should take the same value. That is, $$ x_{t,s} =...

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