[SCIP] reoptimization

[James Cussens]

Dear SCIPers,

I am using reoptimization to solve a series of binary IPs, and I suspect I
am doing it wrong.

My problem is analogous, I think, to the k-Constrained Shortest Path
Problem mentioned in Section 4.2 of Jakob Witzig's master thesis. For my
original IP I want to get the optimal solution, then the 2nd best, then 3rd
best and so on. The objective function never changes.

I have set reoptimization/enable to TRUE and then do the following:

Do k times:
---Solve problem    SCIP_CALL( SCIPsolve(scip) );
---store information sufficient to identify optimal solution OPTSOL
---SCIP_CALL( SCIPfreeTransform(scip) );
---add in constraint ruling out just OPTSOL

I notice that there is a parameter
# separate the optimal solution, i.e., for constrained shortest path
# [type: bool, range: {TRUE,FALSE}, default: FALSE]
reoptimization/sepabestsol = FALSE

which, I suspect, can be used to do what I am doing 'by hand'. Is this the
case?

More generally, I would appreciate knowing the correct recipe for doing
this sort of thing (when using the SCIP callable library).

James

-- 
James Cussens
Dept of Computer Science &
York Centre for Complex Systems Analysis
Room 326, The Hub, Deramore Lane            Tel    +44 (0)1904 325371
University of York                                        Fax  +44 (0)1904
500159
York YO10 5GE, UK                               http://www.cs.york.ac.uk/~jc
http://www.york.ac.uk/docs/disclaimer/email.htm
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