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Unanswered Questions

49 questions with no upvoted or accepted answers
15 votes
1 answer
309 views

Integrality gap in bilevel binary linear programming problem

I have a bilevel max-min optimization problem over binary variables, with constraints expressed using linear inequalities. The inner (minimization) problem is $$ \begin{alignat}2 \min\limits_x&\...
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{...
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
144 views

Sources of Min-Cost Flow Models That Utilize Binary Variables for Transportation Networks

I am looking for articles that include min-cost flow models with binary variables for flow transportation like gas networks, traffic systems, heating systems. Is there any specific place(like OR ...
3 votes
0 answers
471 views

In binary linear programming, what's the relationship between the dual solution and the lagrangian multipliers?

In my optimization problem the objective function and all the constraints are linear. The decision variables are binary. [so, it's BLP] Some of the hard constraints are very time-consuming to be ...
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 ...
3 votes
1 answer
103 views

Modelling Question

Let $W^C_t$, $W_t$ be binary variables and $p$ an integer variable with $1 \leq p \leq 3$ The variables are related through the following equation: $$W^C_t = \sum_{\theta=1}^{p} W_{t-\theta}$$ I can ...
2 votes
0 answers
58 views

Is it useful to consider metaheuristics for power flow optimization involving binary variables?

I want to optimize the power flow in a low voltage grid, with respect to customer requests for electric vehicle (EV) charging, but also avoid grid overload (basically, the formulation can be seen in ...
2 votes
0 answers
92 views

Branching the product of binary and continuous variable in Gurobi

I have a binary variable (X) multiplying a continuous variable (Y). I know I can linearize by adding an auxiliary variable (I have that model working), but I now want to do my own branching in the ...
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}, ...

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