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GECCO
2007
Springer
159views Optimization» more  GECCO 2007»
15 years 9 months ago
Two adaptive mutation operators for optima tracking in dynamic optimization problems with evolution strategies
The dynamic optimization problem concerns finding an optimum in a changing environment. In the tracking problem, the optimizer should be able to follow the optimum’s changes ov...
Claudio Rossi, Antonio Barrientos, Jaime del Cerro
114
Voted
GECCO
2005
Springer
109views Optimization» more  GECCO 2005»
15 years 9 months ago
A hybrid evolutionary algorithm for the p-median problem
A hybrid evolutionary algorithm (EA) for the p-median problem consist of two stages, each of which is a steady-state hybrid EA. These EAs encode selections of medians as subsets o...
István Borgulya
CEC
2009
IEEE
15 years 10 months ago
Examination timetabling using late acceptance hyper-heuristics
— A hyperheuristic is a high level problem solving methodology that performs a search over the space generated by a set of low level heuristics. One of the hyperheuristic framewo...
Ender Özcan, Yuri Bykov, Murat Birben, Edmund...
145
Voted
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 7 months ago
Dominance learning in diploid genetic algorithms for dynamic optimization problems
This paper proposes an adaptive dominance mechanism for diploidy genetic algorithms in dynamic environments. In this scheme, the genotype to phenotype mapping in each gene locus i...
Shengxiang Yang
GECCO
2006
Springer
282views Optimization» more  GECCO 2006»
15 years 7 months ago
A genetic algorithm for the longest common subsequence problem
A genetic algorithm for the longest common subsequence problem encodes candidate sequences as binary strings that indicate subsequences of the shortest or first string. Its fitnes...
Brenda Hinkemeyer, Bryant A. Julstrom