973 questions
0
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GLPK sensitivty result parsing with PULP
I am trying to figure out how to read the GLPK sensitivity results back into Python
An example of how i am generating it:
import pulp
from pulp import LpStatus, value
from glpk_sensitivity_parser ...
- 303
1
vote
1
answer
82
views
Root mean square linearisation for linear programming
I am trying to linearise the function root mean square to use it in a linear optimisation or Mixed integer linear optimisation. Any idea how I could do this? For instance with the example below, if I ...
- 631
0
votes
1
answer
40
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Python PuLP sorting 2D results
I have a Mixed Integer Programming problem very similar set up as introduced in this link.
https://colab.research.google.com/github/ffraile/operations-research-notebooks/blob/main/docs/source/MIP/...
- 115
0
votes
3
answers
66
views
Binary indicator variable related to another variable
In PulP modeling, I have an integer variable s that can take on values 0, 1, or 2. I want a binary indicator variable y such that y=1 if s=0 or s=2, and y=0 if s=1.
I tried defining three binary ...
- 3
0
votes
1
answer
319
views
PuLP Solvers Not Available
I am running an LP using pulp but getting the error AttributeError: 'NoneType' object has no attribute 'actualSolve'. So I found this post on determining the solvers that are available. This directed ...
- 71
0
votes
2
answers
82
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Maximizing correct classification with PuLP
In python, I’m trying to solve a problem of linear optimization with the pulp package.
I have N continuous indicators and a dichotomous target. I need to select a subset of at most M indicators and a ...
0
votes
1
answer
70
views
Python Pulp LP leaving rooms unassigned and penalties/constraints not preventing that
I am having difficulty getting all classrooms to be assigned to a class for a room assignment problem. I am using a grid calculated based on class capacity & room capacity (values 0-1). ...
-2
votes
1
answer
121
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How to restrict float arithmetics in pulp or pyomo to specifically use float32
I need pulp or pyomo to do ALL arithmetic operations exclusively using float32.
It seems that the default they use is float64.
The following are 2 examples from both pulp and pyomo for the sum ...
- 15
1
vote
1
answer
78
views
Need hints for tuning scipy .linprog/.milp
I have a task to optimize the cost of a product, for example, by finding the optimal combination of cans of paint of different volumes and prices for coloring a given square.
The simplest example is:
...
- 11
1
vote
1
answer
198
views
Working with large parameters in an integer linear program using pulp
In pulp's documentation https://coin-or.github.io/pulp/guides/how_to_debug.html, it says that
Check the precision of the numbers. If you have very big numbers (with a high precision), this generally ...
- 5,191
-1
votes
1
answer
59
views
How to speed up large number of calls of a pulp optimization fnction
I have a pulp function that optimizes an objective function based on relationship between two arrays. In its simplest form the objective function acts on two 1D arrays x and y each of size 20. The ...
- 1
1
vote
1
answer
64
views
How to improve scalability of my optimization problem?
I am trying to optimize the number of store managers given different constraints.
Basically I want to minimize the number of managers that have to visit stores everyday in the week.
I designed the ...
- 48
0
votes
0
answers
48
views
Linear relaxation infeasible in PuLP
I am modelling to optimal behaviour of a household battery. The buying price from the grid is different than the selling price to the grid (buying price is always higher). How do I model this ...
-2
votes
1
answer
134
views
Python Pulp Query - allocate task within timerange to achieve objective to minimize number of resource
Objective
Minimize the number of resource to handle all requirements
The input that we have is list of requirements which needs to be allocated to any one of the resource from list of resource that ...
- 1
0
votes
1
answer
30
views
How to run an optimiser with feasible constraints only?
I have a pulp optimiser with a huge number of constraints. We have a condition that if the constraints are not feasible together then we need to try it on a subset of constraints that makes it ...
- 1