Accelerating backtrack search with a best-first-search strategy

• Autorzy: Zoltán Ádám Mann , Tamás Szép
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

best-first search; backtrack; branch-and-bound; constraint satisfaction problem; frequent restarting

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2014
• Tom: 24
• Numer: 4
• Strony: 901-916

Daty

wydano

2014

otrzymano

2014-02-02

poprawiono

2014-05-07

Twórcy

autor

Zoltán Ádám Mann

• Department of Computer Science and Information Theory, Budapest University of Technology and Economics, Magyar tudósok körútja 2., 1117 Budapest, Hungary

autor

Tamás Szép

• Department of Computer Science and Information Theory, Budapest University of Technology and Economics, Magyar tudósok körútja 2., 1117 Budapest, Hungary

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Identyfikatory

DOI

10.2478/amcs-2014-0066