@article {10.3844/ajeassp.2009.789.795,
article_type = {journal},
title = {Evolutionary Algorithm Definition},
author = {AL-Salami, Nada M.A.},
volume = {2},
number = {4},
year = {2009},
month = {Dec},
pages = {789-795},
doi = {10.3844/ajeassp.2009.789.795},
url = {https://thescipub.com/abstract/ajeassp.2009.789.795},
abstract = {Problem statement: Most resent evolutionary algorithms work under weak theoretical basis and thus, they are computationally expensive. Approach: This study discussed the use of new evolutionary algorithm for automatic programming, based on theoretical definitions of program behaviors. Evolutionary process adapted fixed and self-organized input-output specification of the problem, to evolve good finite state machine that efficiently satisfies these specifications. Results: The proposed algorithm enhanced evolutionary process by simultaneously solving multi-parts from the same problem. Conclusion: The probability that the algorithm will converge to the optimal solution was highly enhanced when decomposing the main problem into multi-part.},
journal = {American Journal of Engineering and Applied Sciences},
publisher = {Science Publications}
}