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ASC
2006
13 years 10 months ago
Simulation-based optimisation using local search and neural network metamodels
This paper presents a new algorithm for enhancing the efficiency of simulation-based optimisation using local search and neural network metamodels. The local search strategy is ba...
Anna Persson, Henrik Grimm, Amos Ng
SDM
2009
SIAM
112views Data Mining» more  SDM 2009»
14 years 5 months ago
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning.
Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
Frederik Janssen, Johannes Fürnkranz
GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
13 years 10 months ago
Stochastic local search in continuous domains: questions to be answered when designing a novel algorithm
Several population-based methods (with origins in the world of evolutionary strategies and estimation-of-distribution algorithms) for black-box optimization in continuous domains ...
Petr Posik
AUSAI
2005
Springer
13 years 10 months ago
A Comparison of Evolutionary Methods for the Discovery of Local Search Heuristics
Abstract. Methods of adaptive constraint satisfaction have recently become of interest to overcome the limitations imposed on “black-box” search algorithms by the no free lunch...
Stuart Bain, John Thornton, Abdul Sattar
AAAI
2004
13 years 10 months ago
Complete Local Search for Propositional Satisfiability
Algorithms based on following local gradient information are surprisingly effective for certain classes of constraint satisfaction problems. Unfortunately, previous local search a...
Hai Fang, Wheeler Ruml