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7 votes
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Which solvers should I use to solve large, but extremely sparse LP problems with 100-500 thousand variables?

One of the best-performing free LP solvers exploiting sparsity is HiGHS (https://github.com/ERGO-Code/HiGHS). It allows passing a starting point. For comparing relative performance of a number of LP ...
Michael Feldmeier's user avatar
6 votes
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"GLPK: No Primal Feasible Solution" for Travelling Salesman Problem (Dantzig–Fulkerson–Johnson formulation)

The problem is indeed infeasible but becomes feasible if you omit the subtour57 constraint. For a tour on $6$ nodes, you need to use $6$ arcs, but that constraint allows only $5$.
RobPratt's user avatar
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5 votes

Which solvers should I use to solve large, but extremely sparse LP problems with 100-500 thousand variables?

Based on the Mittelmann benchmarks, I would agree that HiGHS is a contender, as is Clp (which is faster than HiGHS on some test problems, slower on others). You might also want to look at SCIP, which ...
prubin's user avatar
  • 38.8k
5 votes
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GLPK solver with Pyomo, not recognizing infeasibility

This is indeed a little weird! When I run your example, I get the output from GLPK: ...
Sune's user avatar
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3 votes
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Reoptimization with GLPK in Julia/JuMP

Yes, you can do such a thing in JuMP. If you use the so-called direct mode, then incremental changes to the model are passed directly to the solver. If your solver supports incremental changes and re-...
mtanneau's user avatar
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2 votes
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Python and GLPK to solve Linear programming problem (infeasible solution)

The first step is deciding what constraints you are willing to relax. It appears that you have chosen to relax the bounds on food quantities (as opposed to nutrient requirements). The next step is to ...
prubin's user avatar
  • 38.8k
2 votes

Pyomo.solvers on anaconda mac Ventura 13.0.1 (22A400)

The pyomo.solvers conda-forge package is no longer maintained. You can install the solvers you mentioned manually using something like: ...
Bethany Nicholson's user avatar
1 vote

"GLPK: No Primal Feasible Solution" for Travelling Salesman Problem (Dantzig–Fulkerson–Johnson formulation)

For python implementation using pyscipopt, you can refer as following: ...
ytsao's user avatar
  • 366

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