On the reasons for average superlinear speedup in parallel backtrack search

Author(s):  
Andreas Goerdt ◽  
Udo Kamps
2011 ◽  
pp. 1955-1955
Author(s):  
Jack Dongarra ◽  
Piotr Luszczek ◽  
Felix Wolf ◽  
Jesper Larsson Träff ◽  
Patrice Quinton ◽  
...  
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2007 ◽  
Vol 155 (12) ◽  
pp. 1604-1612 ◽  
Author(s):  
I. Lynce ◽  
J. Marques-Silva

2014 ◽  
Vol 24 (4) ◽  
pp. 901-916
Author(s):  
Zoltán Ádám Mann ◽  
Tamás Szép

Abstract 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.


1994 ◽  
Vol 27 (5) ◽  
pp. 471-489 ◽  
Author(s):  
C. Kaklamanis ◽  
G. Persiano

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