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GECCO
2008
Springer
156views Optimization» more  GECCO 2008»
13 years 10 months ago
Computing minimum cuts by randomized search heuristics
We study the minimum s-t-cut problem in graphs with costs on the edges in the context of evolutionary algorithms. Minimum cut problems belong to the class of basic network optimiz...
Frank Neumann, Joachim Reichel, Martin Skutella
SIAMIS
2010
171views more  SIAMIS 2010»
13 years 3 months ago
Global Optimization for One-Dimensional Structure and Motion Problems
We study geometric reconstruction problems in one-dimensional retina vision. In such problems, the scene is modeled as a 2D plane, and the camera sensor produces 1D images of the s...
Olof Enqvist, Fredrik Kahl, Carl Olsson, Kalle &Ar...
EC
2000
96views ECommerce» more  EC 2000»
13 years 8 months ago
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
David A. van Veldhuizen, Gary B. Lamont
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
14 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
CEC
2007
IEEE
14 years 3 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