Maximize x1
Subject To
x1 >= 1
Bounds
x1 free
x2 <= -1
End
Clp detects unboundedness and reports a correct unbounded ray but returns an infeasible solution (i.e. [0, 0]).
Can we expect Clp to return a feasible solution when the problem is unbounded ? We are currently wondering whether this is a reasonable expectation for LP solver here https://github.com/JuliaOpt/MathProgBase.jl/pull/144
Moved from TRAC as part of COIN fORgery: https://projects.coin-or.org/Clp/ticket/80
Dear Clp maintainers,
When trying to solve the following problem
Clp detects unboundedness and reports a correct unbounded ray but returns an infeasible solution (i.e.
[0, 0]).Can we expect Clp to return a feasible solution when the problem is unbounded ? We are currently wondering whether this is a reasonable expectation for LP solver here https://github.com/JuliaOpt/MathProgBase.jl/pull/144
Comment: I asked the same question for Gurobi (here: https://groups.google.com/forum/#!topic/gurobi/cKZY6huEBZo) and they replied that the solver stops as soon as it finds an unbounded ray and therefore has no guarantee on the feasibility of the problem. This is also explained here: https://www.gurobi.com/documentation/7.0/refman/optimization_status_codes.html Therefore, to obtain a feasible solution, one needs to set the objective to 0 and reoptimize. Is it the same for Clp ?