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GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 1 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
TEC
2010
112views more  TEC 2010»
14 years 4 months ago
Population-Based Algorithm Portfolios for Numerical Optimization
In this paper, we consider the scenario that a population-based algorithm is applied to a numerical optimization problem and a solution needs to be presented within a given time bu...
Fei Peng, Ke Tang, Guoliang Chen, Xin Yao
ISVC
2007
Springer
15 years 3 months ago
Combinatorial Shape Decomposition
We formulate decomposition of two-dimensional shapes as a combinatorial optimization problem and present a dynamic programming algorithm that solves it.
Ralf Juengling, Melanie Mitchell
VECPAR
2004
Springer
15 years 2 months ago
Domain Decomposition Methods for PDE Constrained Optimization Problems
Abstract. Optimization problems constrained by nonlinear partial differential equations have been the focus of intense research in scientific computing lately. Current methods for...
Ernesto E. Prudencio, Richard H. Byrd, Xiao-Chuan ...
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
15 years 3 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