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1500 questions
5
votes
2 answers
How can I move from an optimal feasible solution to an optimal basic feasible solution?
I have the following problem: \begin{align}\max&\quad c^T x\\\text{s.t.}&\quad Ax=b\\&\quad x\ge0\end{align}
The matrix $A$ is $m\times n$, where $m
Erel Segal-Halevi
- 989
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5
votes
2 answers
Estimate of mean lead time demand
I am trying to estimate the order-up-to level of inventory, $y_t$, according to ref [1]
$y_t = \hat{D}_t^L + z \hat{\sigma}^L_{et}$
where $\hat{D}_t^L$ is an estimate of the mean lead-time demand, $\hat{\sigma}^L_{et}$ is n estimate of the standard…
Jayyu
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5
votes
1 answer
If continuous variable < constant then same variable = 0
When I come across with a situation needs an if-then constraints I visit Larry's post. I am a bit confused with the titled constraint this time because I am not trying to set $y$ based on $x$ but trying to fix $x$ to $0$ if $x
tcokyasar
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5
votes
1 answer
Practical open source LP solvers for large linear programming problem with $10^7$ parameters
I have an LP problem of the form $\min\ c^Tx$ subject to $Ax\leq b$ where $x$ consists of 30 million parameters and $A$ is a very very sparse matrix of size 30M by 30M (with only 3 ones per row). I tried solving this using scipy.linprog (Interior…
vkmv
- 151
- 1
5
votes
1 answer
Boolean constraining another boolean
like the title suggest, I am trying to constraint a boolean with another boolean, if that makes sense.
x and y are both booleans, where y=1 when Parameter < Variable1
What I am trying to do is the following.
if y = 1, then 0 <= x <= 1. x can be…
DVRJ
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5
votes
1 answer
Enforce specific mean and standard deviation on data
Suppose I have some dataset $X = \{x_1, x_2, \ldots, x_n\}$ which has a mean $\bar{X}$ and a standard deviation $\sigma_X$. Now, suppose that I want to trim the tails of the dataset such that the new average is $\bar{X}_d$ with new standard…
Johnny
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5
votes
1 answer
(Integral) multi-commodity flow on undirected graph
Usually in (integral) multi-commodity flow problems the graph is assumed to be directed. Instead, I am working with an undirected graph. Is it possible to transform it in a digraph?
Does such a transformation work in both the continuous and integral…
Daniele Cuomo
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5
votes
1 answer
What methods are used to solve multi-objective optimization problem with non-linear objective functions and integer decision variables?
Case 1: NLP
When either the objective function or at least one of the constraints or both are non-linear it is a NLP. We use generalized reduced gradient or Quadratic Programming to solve NLP. However, NLP also requires the decision variables to be…
vp_050
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5
votes
3 answers
Minimizing cost of transportation and storage of items
I am looking for an optimization algorithm to minimize the cost of transportation and storage cost in warehouse.
Let's assume the following table gives us the weekly forecast of…
Lopez
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5
votes
2 answers
R package for multi objective integer evolutionary algorithm
I have a discrete event simulation (simmer package) based on probability distributions in R. I would like to optimize the variables according to several (2 or more) objectives. I used the NSGA-II algorithm, but this is only working with continous…
mcfly
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5
votes
1 answer
pyomo/ipopt: nonlinear network optimization not converging
The question (very short version)
Why can I not decrease the lower boundary for the decision variable model.v_dot (see implementation) below 30 ? As soon as I do so, the solver doesn't return results.
After only one iteration I get the solver…
Khalilbs
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5
votes
0 answers
Convergence of an approximate DP for a stochastic shortest path problem
I'm new to the field of sequential decision making. I got intrigued by a stochastic shortest path problem, described in Chapter 5 of this book by W. Powell.
Consider the following stochastic shortest path problem:
Undirected graph $G(V,E)$, a…
Joris Kinable
- 3,451
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5
votes
1 answer
Circular reference in states of the Bellman equation
I want to formulate a game of darts as a dynamic program. The goal is to minimize the number of darts thrown while reaching checkout. A dart player has a score s. If his score is s = 2, there is only a single legal / possible move.
He can checkout…
HJA24
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5
votes
0 answers
Constant-factor approximation algorithms for max-min number partitioning
In the k-way number partitioning problem, the input is a set of numbers and the goal is to partition them into $k$ parts in an optimal way. The most well-studied optimization objective is to minimize the largest sum; this problem is equivalent to…
Erel Segal-Halevi
- 989
- 5
- 18
5
votes
1 answer
Why does one objective function prove feasibility faster than another?
I recently ran a MIP model with cplex specifying it should stop solving when integer feasibility was proven (mipsolutions=1).
When I ran the model with one easy objective function, the model did not find any feasible integer solutions after an hour.…
Christian
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