Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
The particle swarm: social adaptation in information-processing systems
New ideas in optimization
Journal of Global Optimization
An Electromagnetism-like Mechanism for Global Optimization
Journal of Global Optimization
The particle swarm optimization algorithm: convergence analysis and parameter selection
Information Processing Letters
Population set-based global optimization algorithms: some modifications and numerical studies
Computers and Operations Research
Journal of Global Optimization
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
A Differential Free Point Generation Scheme in the Differential Evolution Algorithm
Journal of Global Optimization
A differential evolution algorithm with intersect mutation operator
Applied Soft Computing
Multiple documents summarization based on evolutionary optimization algorithm
Expert Systems with Applications: An International Journal
Adaptive Memetic Differential Evolution with Global and Local neighborhood-based mutation operators
Information Sciences: an International Journal
| Hi-index | 7.30 |
In this paper, we study the mutation operation of the differential evolution (DE) algorithm. In particular, we propose the differential of scaled vectors, called the 'generalized differential', as opposed to the existing scaled differential vector in the mutation of DE. We derive the probability distribution of points generated by the mutation with 'generalized differentials'. We incorporate a vector-projection-based exploratory method within the new mutation scheme. The vector projection is not mandatory and it is only invoked if trial points continue to be unsuccessful. An algorithm is then proposed which implements the mutation strategy based on the difference of the scaled vectors as well as the vector projection technique. A numerical study is carried out using a set of 50 test problems, many of which are inspired by practical applications. Numerical results suggest that the new algorithm is superior to DE.