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Analysis of an Optimized Search Algorithm for Skip Lists
 Theoretical Computer Science
, 1994
"... It was suggested in [8] to avoid redundant queries in the skip list search algorithm by marking those elements whose key has already been checked by the search algorithm. We present here a precise analysis of the total search cost (expectation and variance), where the cost of the search is measured ..."
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Cited by 13 (5 self)
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It was suggested in [8] to avoid redundant queries in the skip list search algorithm by marking those elements whose key has already been checked by the search algorithm. We present here a precise analysis of the total search cost (expectation and variance), where the cost of the search is measured
Improved algorithms for optimal winner determination in combinatorial auctions and generalizations
, 2000
"... Combinatorial auctions can be used to reach efficient resource and task allocations in multiagent systems where the items are complementary. Determining the winners is NPcomplete and inapproximable, but it was recently shown that optimal search algorithms do very well on average. This paper present ..."
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Cited by 582 (53 self)
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Combinatorial auctions can be used to reach efficient resource and task allocations in multiagent systems where the items are complementary. Determining the winners is NPcomplete and inapproximable, but it was recently shown that optimal search algorithms do very well on average. This paper
Applications Of Levin's Universal Optimal Search Algorithm
, 1995
"... New applications of Levin's Universal Optimal Search are presented in this paper. Using this method one finds solutions to a few chosen problems. Such solutions are characterized by possibility of the maximal generalization. In the deterministic version of the Universal Optimal Search algorithm ..."
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New applications of Levin's Universal Optimal Search are presented in this paper. Using this method one finds solutions to a few chosen problems. Such solutions are characterized by possibility of the maximal generalization. In the deterministic version of the Universal Optimal Search
An Optimal Algorithm for Approximate Nearest Neighbor Searching in Fixed Dimensions
 ACMSIAM SYMPOSIUM ON DISCRETE ALGORITHMS
, 1994
"... Consider a set S of n data points in real ddimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any po ..."
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Cited by 984 (32 self)
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Consider a set S of n data points in real ddimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any
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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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
Depthfirst IterativeDeepening: An Optimal Admissible Tree Search
 Artificial Intelligence
, 1985
"... The complexities of various search algorithms are considered in terms of time, space, and cost of solution path. It is known that breadthfirst search requires too much space and depthfirst search can use too much time and doesn't always find a cheapest path. A depthfirst iteratiwdeepening a ..."
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Cited by 527 (24 self)
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deepening algorithm is shown to be asymptotically optimal along all three dimensions for exponential pee searches. The algorithm has been used successfully in chess programs, has been eflectiuely combined with bidirectional search, and has been applied to bestfirst heuristic search as well. This heuristic depth
A STOCHASTICALLY QUASIOPTIMAL SEARCH ALGORITHM FOR THE MAXIMUM OF THE SIMPLE RANDOM WALK
"... an asymptotically optimal algorithm, with respect to the average cost, among algorithms that find the maximum of a random walk by using only probes and comparisons. We extend Odlyzko’s techniques to prove that his algorithm is indeed asymptotically optimal in distribution (with respect to the stocha ..."
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Cited by 1 (0 self)
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an asymptotically optimal algorithm, with respect to the average cost, among algorithms that find the maximum of a random walk by using only probes and comparisons. We extend Odlyzko’s techniques to prove that his algorithm is indeed asymptotically optimal in distribution (with respect
A NEW OPTIMAL SEARCH ALGORITHM FOR THE TRANSPORTATION FLEET MAINTENANCE SCHEDULING PROBLEM
, 2004
"... Abstract In this study, we propose a new solution approach for the Transportation Fleet Maintenance Scheduling Problem (TFMSP). Before presenting our solution approach, we first review Goyal and Gunasekaran’s [International Journal of Systems Science, 23 (1992) 655659] mathematical model and their ..."
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and their search procedure for determining the economic maintenance frequency of a transport fleet. To solve the TFMSP, we conduct a full analysis on the mathematical model. By utilizing our theoretical results, we propose an efficient search algorithm that finds the optimal solution for the TFMSP within a very
Optimal Search Algorithms for Structured Problems in Natural Language Processing by
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