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In this paper, by combination of some approaches we propose a new approach of Differential Evolution (DE) algorithm, called DE with nonlinear simplex method and dynamic neighborhood search (DENNS). In our approach the nonlinear simplex method (NSM) is used for population initialization and local neighborhood search. Moreover, local and global neighborhood search operators are employed to generate...
In this paper, the performance of a sequential Differential Evolution (DE) enhanced by neighborhood search (SDENS) is reported on the set of benchmark functions provided for the CEC2010 Special Session on Large Scale Global Optimization. The original DENS was proposed in our previous work, which differs from existing works which are utilizing the neighborhood search in DE, such as DE with neighborhood...
This paper presents a novel Differential Evolution (DE) algorithm, called DE enhanced by neighborhood search (DENS), which differs from pervious works of utilizing the neighborhood search in DE, such as DE with neighborhood search (NSDE) and self-adaptive DE with neighborhood search (SaNSDE). In DENS, we focus on searching the neighbors of individuals, while the latter two algorithms (NSDE and SaNSDE)...
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