Originally posted by: JimDan
I do not understand your question fully. Could you provide more details as to what exactly you are looking for?
If your question is: how does CPLEX re-solve an LP after I change a certain parameter (objective function coefficient, constraint matrix, RHS or variable bounds) then I think the answer is that after every LP solution, CPLEX maintains the current basis. If a parameter changes, then the current basis is either feasible to the new problem or it is not. If it is feasible, well and good, the current is basis is used to proceed onward with optimization. If not, CPLEX "uses" the current basis to see if a new feasible basis can be obtained with "minimal" computational effort. Once found, well and good, CPLEX proceeds onward with optimization.
A useful way to check these things is to use cplex.getNIterations() after every cplex.solve(). If you are doing sensitivity analysis and what I said above is true then you should notice that cplex.getNIterations() reports fewer iterations to solve the modified problem from the current basis than if you were to solve the modified problem from scratch.
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