
Mathematics, Год журнала: 2024, Номер 12(23), С. 3815 - 3815
Опубликована: Дек. 2, 2024
This paper presents an effective hybrid metaheuristic algorithm combining the genetic (GA) and a simple based on evolutionary computation. The approach (EA) is applied to form initial population of GA, thus improving algorithm’s performance, especially its convergence speed. To assess effectiveness, proposed algorithm, EAGA, evaluated selected benchmark functions, as well real optimisation process. EAGA used identify parameters in nonlinear system differential equations modelling E. coli fed-batch fermentation obtained results are compared against published from algorithms problems. outperforms competing due generation strategy. risk premature reduced. Better numerical outcomes achieved. investigations validate potential for solving complex tasks.
Язык: Английский