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Accelerating backtrack search with a best-first-search strategy

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Mann Z., Szép T.

International Journal of Applied Mathematics and Computer Science

2014

tom 24

nr 4

901-916

Backtrack-style exhaustive search algorithms for NP-hard problems tend to have large variance in their runtime. This is because "fortunate" branching decisions can lead to finding a solution quickly, whereas “unfortunate” decisions in another run can lead the algorithm to a region of the search space with no solutions. In the literature, frequent restarting has been suggested as a means to overcome this problem. In this paper, we propose a more sophisticated approach: a best-firstsearch heuristic to quickly move between parts of the search space, always concentrating on the most promising region. We describe how this idea can be efficiently incorporated into a backtrack search algorithm, without sacrificing optimality. Moreover, we demonstrate empirically that, for hard solvable problem instances, the new approach provides significantly higher speed-up than frequent restarting.

Ograniczanie wyników

1 International Journal of Applied Mathematics and Computer Science

1 Mann Z.

1 Szép T.

1 2014

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Accelerating backtrack search with a best-first-search strategy