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» Function Optimization with Coevolutionary Algorithms
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GECCO
2006
Springer
153views Optimization» more  GECCO 2006»
14 years 1 months ago
On the local performance of simulated annealing and the (1+1) evolutionary algorithm
Simulated annealing and the (1+1) EA, a simple evolutionary algorithm, are both general randomized search heuristics that optimize any objective function with probability
Thomas Jansen, Ingo Wegener
CORR
2010
Springer
170views Education» more  CORR 2010»
13 years 10 months ago
Global Optimization for Value Function Approximation
Existing value function approximation methods have been successfully used in many applications, but they often lack useful a priori error bounds. We propose a new approximate bili...
Marek Petrik, Shlomo Zilberstein
SODA
2010
ACM
163views Algorithms» more  SODA 2010»
14 years 7 months ago
Geometric optimization and sums of algebraic functions
We present a new optimization technique that yields the first FPTAS for several geometric problems. These problems reduce to optimizing a sum of non-negative, constant description...
Antoine Vigneron
CONSTRAINTS
2008
138views more  CONSTRAINTS 2008»
13 years 10 months ago
Minimization of Locally Defined Submodular Functions by Optimal Soft Arc Consistency
Submodular function minimization is a polynomially-solvable combinatorial problem. Unfortunately the best known general-purpose algorithms have high-order polynomial time complexi...
Martin C. Cooper
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
14 years 3 months ago
Enhancing differential evolution performance with local search for high dimensional function optimization
In this paper, we proposed Fittest Individual Refinement (FIR), a crossover based local search method for Differential Evolution (DE). The FIR scheme accelerates DE by enhancing...
Nasimul Noman, Hitoshi Iba