On the reasons for average superlinear speedup in parallel backtrack search

2006 ◽  
pp. 106-127
Author(s):  
Andreas Goerdt ◽  
Udo Kamps
Keyword(s):  
Backtrack Search ◽  
Superlinear Speedup

scholarly journals Backtrack search with isomorph rejection and consistency check

1989 ◽  
Vol 7 (5) ◽  
pp. 473-485 ◽  
Author(s):  
C.W.H. Lam ◽  
L. Thiel
Keyword(s):  
Consistency Check ◽  
Backtrack Search ◽  
Isomorph Rejection

Superlinear Speedup of Parallel Population-Based Metaheuristics: A Microservices and Container Virtualization Approach

2019 ◽  
pp. 386-393
Author(s):  
Hatem Khalloof ◽  
Phil Ostheimer ◽  
Wilfried Jakob ◽  
Shadi Shahoud ◽  
Clemens Duepmeier ◽  
...  
Keyword(s):  
Population Based ◽  
Superlinear Speedup

Is average superlinear speedup possible?

2005 ◽  
pp. 301-312 ◽  
Author(s):  
Ewald Speckenmeyer
Keyword(s):  
Superlinear Speedup

Superlinear Speedup

2011 ◽  
pp. 1955-1955
Author(s):  
Jack Dongarra ◽  
Piotr Luszczek ◽  
Felix Wolf ◽  
Jesper Larsson Träff ◽  
Patrice Quinton ◽  
...  
Keyword(s):  
Superlinear Speedup

scholarly journals Random backtracking in backtrack search algorithms for satisfiability

2007 ◽  
Vol 155 (12) ◽  
pp. 1604-1612 ◽  
Author(s):  
I. Lynce ◽  
J. Marques-Silva
Keyword(s):  
Search Algorithms ◽  
Backtrack Search

Virtualized environments in cloud can have superlinear speedup

2012 ◽  
Author(s):  
Sasko Ristov ◽  
Magdalena Kostoska ◽  
Marjan Gusev ◽  
Kiril Kiroski
Keyword(s):  
Superlinear Speedup

scholarly journals Accelerating backtrack search with a best-first-search strategy

2014 ◽  
Vol 24 (4) ◽  
pp. 901-916
Author(s):  
Zoltán Ádám Mann ◽  
Tamás Szép
Keyword(s):  
Search Strategy ◽  
Search Algorithm ◽  
Search Space ◽  
New Approach ◽  
Backtrack Search ◽  
Speed Up ◽  
Hard Problems ◽  
Best First Search ◽  
Problem Instances ◽  
Np Hard Problems

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.

Branch-and-bound and backtrack search on mesh-connected arrays of processors

1994 ◽  
Vol 27 (5) ◽  
pp. 471-489 ◽  
Author(s):  
C. Kaklamanis ◽  
G. Persiano
Keyword(s):  
Branch And Bound ◽  
Backtrack Search
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