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 new generation alternation model for differential evolution
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Differential Evolution: In Search of Solutions (Springer Optimization and Its Applications)
Differential Evolution: In Search of Solutions (Springer Optimization and Its Applications)
Advances in Differential Evolution
Advances in Differential Evolution
Differential evolution using a neighborhood-based mutation operator
IEEE Transactions on Evolutionary Computation
A statistical study of the differential evolution based on continuous generation model
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Multi-objective optimum design of balanced SAW filters using generalized differential evolution
WSEAS TRANSACTIONS on SYSTEMS
System design by constraint adaptation and differential evolution
IEEE Transactions on Evolutionary Computation
Accelerating Differential Evolution Using an Adaptive Local Search
IEEE Transactions on Evolutionary Computation
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Many of the conventional Differential Evolutions (DEs) have employed the discrete generation model that uses two populations, namely, old one and new one. Recently, a new DE based on the continuous generation model is proposed. The new DE is sometimes called Sequential DE (SDE). In the continuous generation model, only one population is used. In this paper, besides SDE, two types of extended SDEs are presented. The first one is called Transversal Differential Evolution (TDE). The second one is called Dispersive Differential Evolution (DDE). In both extended SDEs, more than one trial vectors are generated from a target vector. Then each of the trial vectors is compared with the target vector. However, the place that makes a set of the trial vectors is different in TDE and DDE. In order to evaluate the performances of the three new DEs, namely, SDE, TDE and DDE, not only the numerical experiment but also the statistical test is conducted on various benchmark problems.