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CEC
2007
IEEE
15 years 7 months ago
On improving approximate solutions by evolutionary algorithms
Abstract—Hybrid methods are very popular for solving problems from combinatorial optimization. In contrast to this the theoretical understanding of the interplay of different opt...
Tobias Friedrich, Jun He, Nils Hebbinghaus, Frank ...
95
Voted
ISNN
2009
Springer
15 years 7 months ago
An Improved Quantum Evolutionary Algorithm with 2-Crossovers
Quantum evolutionary algorithm (QEA) is proposed on the basis of the concept and principles of quantum computing, which is a classical metaheuristic algorithm for the approximate s...
Zhihui Xing, Haibin Duan, Chunfang Xu
66
Voted
EUSFLAT
2003
101views Fuzzy Logic» more  EUSFLAT 2003»
15 years 2 months ago
Improving interpretability in approximative fuzzy models via multi-objective evolutionary algorithms
Antonio F. Gómez-Skarmeta, Fernando Jim&eac...
ICTAI
2009
IEEE
15 years 7 months ago
Evolution Strategies for Constants Optimization in Genetic Programming
Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
César Luis Alonso, José Luis Monta&n...
99
Voted
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
15 years 4 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson