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GRASP  A New Search Algorithm for Satisfiability
, 1996
"... This paper introduces GRASP (Generic seaRch Algorithm for the Satisjiability Problem), an integrated algorithmic framework for SAT that un.$es several previously proposed searchpruning techniques and facilitates ident$cation of additional ones. GRASP is premised on the inevitability of confzicts dur ..."
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Cited by 449 (34 self)
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This paper introduces GRASP (Generic seaRch Algorithm for the Satisjiability Problem), an integrated algorithmic framework for SAT that un.$es several previously proposed searchpruning techniques and facilitates ident$cation of additional ones. GRASP is premised on the inevitability of confzicts
On the Convergence of Pattern Search Algorithms
"... . We introduce an abstract definition of pattern search methods for solving nonlinear unconstrained optimization problems. Our definition unifies an important collection of optimization methods that neither computenor explicitly approximate derivatives. We exploit our characterization of pattern sea ..."
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Cited by 243 (13 self)
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. We introduce an abstract definition of pattern search methods for solving nonlinear unconstrained optimization problems. Our definition unifies an important collection of optimization methods that neither computenor explicitly approximate derivatives. We exploit our characterization of pattern
Searching algorithms
"... Abstract: Here we want to represent an introduction about searching algorithms. Due to this, first we will discuss on general searching algorithm purposes. These are: virtual search spaces, substructures of a given structure and quantum computers. Also, for more information, we introduce some of si ..."
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Abstract: Here we want to represent an introduction about searching algorithms. Due to this, first we will discuss on general searching algorithm purposes. These are: virtual search spaces, substructures of a given structure and quantum computers. Also, for more information, we introduce some
Search Algorithms
"... • Search algorithms are fundamental techniques applied to solve a wide range of optimization problems. • Search algorithms attempt to find all the nodes in a network satisfying a particular property. • Examples – Find nodes that are reachable by directed paths from a source node. – Find nodes that c ..."
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• Search algorithms are fundamental techniques applied to solve a wide range of optimization problems. • Search algorithms attempt to find all the nodes in a network satisfying a particular property. • Examples – Find nodes that are reachable by directed paths from a source node. – Find nodes
Improvements To Propositional Satisfiability Search Algorithms
, 1995
"... ... quickly across a wide range of hard SAT problems than any other SAT tester in the literature on comparable platforms. On a Sun SPARCStation 10 running SunOS 4.1.3 U1, POSIT can solve hard random 400variable 3SAT problems in about 2 hours on the average. In general, it can solve hard nvariable ..."
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Cited by 174 (0 self)
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variable random 3SAT problems with search trees of size O(2 n=18:7 ). In addition to justifying these claims, this dissertation describes the most significant achievements of other researchers in this area, and discusses all of the widely known general techniques for speeding up SAT search algorithms
On The Convergence Of The Multidirectional Search Algorithm
, 1991
"... . This paper presents the convergence analysis for the multidirectional search algorithm, a direct search method for unconstrained minimization. The analysis follows the classic lines of proofs of convergence for gradientrelated methods. The novelty of the argument lies in the fact that explicit ca ..."
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Cited by 79 (7 self)
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. This paper presents the convergence analysis for the multidirectional search algorithm, a direct search method for unconstrained minimization. The analysis follows the classic lines of proofs of convergence for gradientrelated methods. The novelty of the argument lies in the fact that explicit
Adaptive floating search methods in feature selection
 PATTERN RECOGNITION LETTERS
, 1999
"... A new suboptimal search strategy for feature selection is presented. It represents a more sophisticated version of "classical" floating search algorithms (Pudil et al., 1994), attempts to remove some of their potential deficiencies and facilitates finding a solution even closer to the opti ..."
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Cited by 548 (21 self)
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A new suboptimal search strategy for feature selection is presented. It represents a more sophisticated version of "classical" floating search algorithms (Pudil et al., 1994), attempts to remove some of their potential deficiencies and facilitates finding a solution even closer
Depth first search and linear graph algorithms
 SIAM JOURNAL ON COMPUTING
, 1972
"... The value of depthfirst search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components of an undirect ..."
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Cited by 1406 (19 self)
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The value of depthfirst search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components
A Fast Quantum Mechanical Algorithm for Database Search
 ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING
, 1996
"... Imagine a phone directory containing N names arranged in completely random order. In order to find someone's phone number with a probability of , any classical algorithm (whether deterministic or probabilistic)
will need to look at a minimum of names. Quantum mechanical systems can be in a supe ..."
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Cited by 1135 (10 self)
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Imagine a phone directory containing N names arranged in completely random order. In order to find someone's phone number with a probability of , any classical algorithm (whether deterministic or probabilistic)
will need to look at a minimum of names. Quantum mechanical systems can be in a
TABU SEARCH
"... Tabu Search is a metaheuristic that guides a local heuristic search procedure to explore the solution space beyond local optimality. One of the main components of tabu search is its use of adaptive memory, which creates a more flexible search behavior. Memory based strategies are therefore the hallm ..."
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Cited by 822 (48 self)
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algorithms based on the tabu search. The experimentation shows that the procedures provide high quality solutions to the training problem, and in addition consume a reasonable computational effort.
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