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» Evolutionary Algorithms for the Satisfiability Problem
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GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
15 years 6 months ago
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Peter A. N. Bosman, Han La Poutré
GECCO
2003
Springer
103views Optimization» more  GECCO 2003»
15 years 5 months ago
Multicriteria Network Design Using Evolutionary Algorithm
In this paper, we revisit a general class of multi-criteria multi-constrained network design problems and attempt to solve, in a novel way, with Evolutionary Algorithms (EAs). A ma...
Rajeev Kumar, Nilanjan Banerjee
GECCO
2004
Springer
15 years 5 months ago
How Are We Doing? Predicting Evolutionary Algorithm Performance
Abstract. Given an evolutionary algorithm for a problem and an instance of the problem, the results of several trials of the EA on the instance constitute a sample from the distrib...
Mark A. Renslow, Brenda Hinkemeyer, Bryant A. Juls...
CEC
2007
IEEE
15 years 6 months ago
Light beam search based multi-objective optimization using evolutionary algorithms
Abstract— For the past decade or so, evolutionary multiobjective optimization (EMO) methodologies have earned wide popularity for solving complex practical optimization problems,...
Kalyanmoy Deb, Abhay Kumar
KES
2008
Springer
14 years 11 months ago
Instruction-based development: From evolution to generic structures of digital circuits
Evolutionary techniques provide powerful tools to design novel solutions for hard problems in different areas. However, the problem of scale (i.e. how to create a large, complex s...
Michal Bidlo, Jaroslav Skarvada