Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Multicriteria fuzzy control using evolutionary programming
Information Sciences: an International Journal
Intelligence through simulated evolution: forty years of evolutionary programming
Intelligence through simulated evolution: forty years of evolutionary programming
EVERA: an evolutionary programming environment for adaptive speech processing
Information Sciences: an International Journal - Special issue on frontiers in evolutionary algorithms
Evolutionary programming Kalman filter
Information Sciences—Informatics and Computer Science: An International Journal
System Identification through Simulated Evolution: A Machine Learning Approach to Modeling
System Identification through Simulated Evolution: A Machine Learning Approach to Modeling
Adapting Self-Adaptive Parameters in Evolutionary Algorithms
Applied Intelligence
Scaling Up Evolutionary Programming Algorithms
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Global Optimisation by Evolutionary Algorithms
PAS '97 Proceedings of the 2nd AIZU International Symposium on Parallel Algorithms / Architecture Synthesis
An overview of evolutionary algorithms for parameter optimization
Evolutionary Computation
EP-based kinematic control and adaptive fuzzy sliding-mode dynamic control for wheeled mobile robots
Information Sciences: an International Journal
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Combining mutation operators in evolutionary programming
IEEE Transactions on Evolutionary Computation
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
Evolutionary programming techniques for economic load dispatch
IEEE Transactions on Evolutionary Computation
Evolutionary programming using mutations based on the Levy probability distribution
IEEE Transactions on Evolutionary Computation
Ensemble of niching algorithms
Information Sciences: an International Journal
Information Sciences: an International Journal
A dynamic classifier ensemble selection approach for noise data
Information Sciences: an International Journal
Differential evolution in constrained numerical optimization: An empirical study
Information Sciences: an International Journal
On-the-fly calibrating strategies for evolutionary algorithms
Information Sciences: an International Journal
Optimal depth estimation by combining focus measures using genetic programming
Information Sciences: an International Journal
A three-strategy based differential evolution algorithm for constrained optimization
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Self-adaptive learning based particle swarm optimization
Information Sciences: an International Journal
Dynamic classifier ensemble model for customer classification with imbalanced class distribution
Expert Systems with Applications: An International Journal
Eigenclassifiers for combining correlated classifiers
Information Sciences: an International Journal
Ockham's Razor in memetic computing: Three stage optimal memetic exploration
Information Sciences: an International Journal
Information Sciences: an International Journal
A genetic algorithm with the heuristic procedure to solve the multi-line layout problem
Computers and Industrial Engineering
An Intelligent Tuned Harmony Search algorithm for optimisation
Information Sciences: an International Journal
Taboo evolutionary programming approach to optimal transfer from earth to mars
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part II
Function optimisation by learning automata
Information Sciences: an International Journal
Information Sciences: an International Journal
Adaptive population tuning scheme for differential evolution
Information Sciences: an International Journal
A novel fuzzy Dempster-Shafer inference system for brain MRI segmentation
Information Sciences: an International Journal
Fixed-point digital IIR filter design using two-stage ensemble evolutionary algorithm
Applied Soft Computing
Co-Evolutionary Algorithms Based on Mixed Strategy
Journal of Information Technology Research
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
Computers and Electronics in Agriculture
Adaptive learning algorithm of self-organizing teams
Expert Systems with Applications: An International Journal
An analysis on separability for Memetic Computing automatic design
Information Sciences: an International Journal
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Mutation operators such as Gaussian, Levy and Cauchy have been used with evolutionary programming (EP). According to the no free lunch theorem, it is impossible for EP with a single mutation operator to outperform always. For example, Classical EP (CEP) with Gaussian mutation is better at searching in a local neighborhood while the Fast EP (FEP) with the Cauchy mutation performs better over a larger neighborhood. Motivated by these observations, we propose an ensemble approach where each mutation operator has its associated population and every population benefits from every function call. This approach enables us to benefit from different mutation operators with different parameter values whenever they are effective during different stages of the search process. In addition, the recently proposed Adaptive EP (AEP) using Gaussian (ACEP) and Cauchy (AFEP) mutations is also evaluated. In the AEP, the strategy parameter values are adapted based on the search performance in the previous few generations. The performance of ensemble is compared with a mixed mutation strategy, which integrates several mutation operators into a single algorithm as well as against the AEP with a single mutation operator. Improved performance of the ensemble over the single mutation-based algorithms and mixed mutation algorithm is verified using statistical tests.