Eksperimen Perbandingan Evolutionary Programming dan Evolutionary Strategies dalam Permasalahan Maximization Fungsi Polinomial

Nugroho, Ahmad
Siregar, Maria

CSRID
Vol. 15 No. 3 (2023): October 2023

Evolutionary Programming and Evolutionary Strategies are two techniques in Evolutionary Computation. Both are relatively similar but in Evolutionary Strategies, crossover is not used and only mutation is performed using normally distributed noise. To determine which is better in solving the problem of maximizing a polynomial function, this study aims to compare both. Implementation will be made using the Python programming language with the DEAP (Distributed Evolutionary Algorithms in Python) library. Then both are run 100 times to find the average number of generations needed to achieve an accuracy of at least 1e-5. Based on the research, it was found that Evolutionary Strategies provides more efficient performance by 4%.