Authors:
Simon P. Martin
1
;
Matthew J. Craven
2
and
John R. Woodward
3
Affiliations:
1
Brook, Isle of Wight, PO30 4EU, U.K.
;
2
Centre for Mathematical Sciences, University of Plymouth, Drake Circus, Plymouth PL4 8AA, U.K.
;
3
Computer Science, Queen Mary University of London, Mile End Road, London E1 4FZ, U.K.
Keyword(s):
Heuristic, Gadget, Approximation Algorithm, Optimisation Problem.
Abstract:
In some cases, heuristics may be transferred easily between different optimisation problems. This is the case if these problems are equivalent or dual (e.g., maximum clique and maximum independent set) or have similar objective functions. However, the link between problems can further be defined by the constraints that define them. This refining can be achieved by organising constraints into families and translating between them using gadgets. If two problems are in the same constraint family, the gadgets tell us how to map from one problem to another and which constraints are modified. This helps better understand a problem through its constraints and how best to use domain specific heuristics. In this position paper, we argue that this allows us to understand how to map between heuristics developed for one problem to heuristics for another problem, giving an example of how this might be achieved.