关键词:
Evolutionary algorithm
Epigenetics
Epigenetic algorithm
Probabilistic environmental vector
Variable nucleosome reorganization
摘要:
Epigenetics’flexibility in terms of finer manipulation of genes renders unprecedented levels of refined and diverse evolutionary mechanisms *** the epigenetic perspective,the main limitations to improving the stability and accuracy of genetic algorithms are as follows:(1)the unchangeable nature of the external environment,which leads to excessive disorders in the changed phenotype after mutation and crossover;(2)the premature convergence due to the limited types of epigenetic *** this paper,a probabilistic environmental gradientdriven genetic algorithm(PEGA)considering epigenetic traits is *** enhance the local convergence efficiency and acquire stable local search,a probabilistic environmental gradient(PEG)descent strategy together with a multi-dimensional heterogeneous exponential environmental vector tendentiously generates more offsprings along the gradient in the solution ***,to balance exploration and exploitation at different evolutionary stages,a variable nucleosome reorganization(VNR)operator is realized by dynamically adjusting the number of genes involved in mutation and *** on the above-mentioned operators,three epigenetic operators are further introduced to weaken the possible premature problem by enriching genetic *** experimental results on the open Congress on Evolutionary Computation-2017(CEC’17)benchmark over 10-,30-,50-,and 100-dimensional tests indicate that the proposed method outperforms 10 state-of-the-art evolutionary and swarm algorithms in terms of accuracy and stability on comprehensive *** ablation analysis demonstrates that for accuracy and stability,the fusion strategy of PEG and VNR are effective on 96.55%of the test functions and can improve the indicators by up to four orders of ***,the performance of PEGA on the real-world spacecraft trajectory optimization problem is the best in terms of quality of the solution.