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» Function Optimization with Coevolutionary Algorithms
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GECCO
2006
Springer
153views Optimization» more  GECCO 2006»
15 years 7 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»
15 years 4 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»
16 years 1 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»
15 years 4 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»
15 years 9 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