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GECCO
2004
Springer
14 years 3 months ago
Towards a Generally Applicable Self-Adapting Hybridization of Evolutionary Algorithms
When applied to real-world problems, the powerful optimization tool of Evolutionary Algorithms frequently turns out to be too time-consuming due to elaborate fitness calculations t...
Wilfried Jakob, Christian Blume, Georg Bretthauer
CEC
2010
IEEE
13 years 11 months ago
Evolutionary multi-objective optimization algorithms with probabilistic representation based on pheromone trails
Abstract-- Recently, the research on quantum-inspired evolutionary algorithms (QEA) has attracted some attention in the area of evolutionary computation. QEA use a probabilistic re...
Hui Li, Dario Landa Silva, Xavier Gandibleux
EOR
2007
77views more  EOR 2007»
13 years 9 months ago
Solving the short-term electrical generation scheduling problem by an adaptive evolutionary approach
In this paper, we introduce an adaptive evolutionary approach to solve the short-term electrical generation scheduling problem (STEGS). The STEGS is a hard constraint satisfaction...
Jorge Maturana, María-Cristina Riff
GECCO
2004
Springer
152views Optimization» more  GECCO 2004»
14 years 3 months ago
Ant System for the k-Cardinality Tree Problem
This paper gives an algorithm for finding the minimum weight tree having k edges in an edge weighted graph. The algorithm combines a search and optimization technique based on phe...
Thang Nguyen Bui, Gnanasekaran Sundarraj
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 4 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart