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EMO
2009
Springer
190views Optimization» more  EMO 2009»
14 years 2 months ago
Solving Bilevel Multi-Objective Optimization Problems Using Evolutionary Algorithms
Abstract. Bilevel optimization problems require every feasible upperlevel solution to satisfy optimality of a lower-level optimization problem. These problems commonly appear in ma...
Kalyanmoy Deb, Ankur Sinha
GECCO
2005
Springer
107views Optimization» more  GECCO 2005»
14 years 1 months ago
Minimum spanning trees made easier via multi-objective optimization
Many real-world problems are multi-objective optimization problems and evolutionary algorithms are quite successful on such problems. Since the task is to compute or approximate t...
Frank Neumann, Ingo Wegener
ICTAI
2006
IEEE
14 years 1 months ago
Intelligent Optimization via Learnable Evolution Model
A new method for optimizing complex functions and systems is described that employs Learnable Evolution Model (LEM), a form of non-Darwinian evolutionary computation guided by mac...
Ryszard S. Michalski, Janusz Wojtusiak, Kenneth A....
CORR
2010
Springer
152views Education» more  CORR 2010»
13 years 7 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
GECCO
2010
Springer
347views Optimization» more  GECCO 2010»
13 years 9 months ago
Comparison of cauchy EDA and BIPOP-CMA-ES algorithms on the BBOB noiseless testbed
Estimation-of-distribution algorithm using Cauchy sampling distribution is compared with the bi-population CMA evolutionary strategy which was one of the best contenders in the bl...
Petr Posík