ADEMO/D: Multiobjective optimization by an adaptive differential evolution algorithm

2014 ◽  
Vol 127 ◽  
pp. 65-77 ◽  
Author(s):  
Sandra M. Venske ◽  
Richard A. Gonçalves ◽  
Myriam R. Delgado
Keyword(s):  
Multiobjective Optimization ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Adaptive Differential Evolution ◽  
Evolution Algorithm

scholarly journals A Modified Multiobjective Self-Adaptive Differential Evolution Algorithm and Its Application on Optimization Design of the Nuclear Power System

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Yunjia Yang ◽  
Shinian Peng ◽  
Li Zhu ◽  
Dan Zhang ◽  
Zhifang Qiu ◽  
...  
Keyword(s):  
Optimal Design ◽  
Multiobjective Optimization ◽  
Power System ◽  
Differential Evolution ◽  
Nuclear Power ◽  
Optimization Design ◽  
Differential Evolution Algorithm ◽  
Nuclear Power System ◽  
Adaptive Differential Evolution ◽  
Evolution Algorithm

A modified multiobjective self-adaptive differential evolution algorithm (MMOSADE) is presented in this paper to improve the accuracy of multiobjective optimization design in the nuclear power system. The performance of the MMOSADE is tested by the ZDT test function set and compared with classical evolutionary algorithms. The results indicate that MMOSADE has a better performance in convergence and diversity. Based on the MMOSADE, a multiobjective optimization design platform for the nuclear power system is proposed, and the application of which is carried out. The evaluation program of the PRHR-HX in AP1000 is developed, and its reliability is verified. The optimal design schemes of PHHR-HX are obtained by utilizing the multiobjective optimization design platform. The results show that the optimal design schemes can envelop the prototype design scheme. This conclusion proves that the optimization design platform proposed in this paper is effective and feasible.

Sign in / Sign up

Export Citation Format

Share Document