Akpan, Whyte Asukwo and Essien, Godwin Daniel and Orazulume, Chikodili Martha and Edet, Francis Etebong and Inyang, Nsikakabasi Nsedu and Effeng, Ndifreke Ikemesit (2025) Genetic algorithm encoding and problems solving for enthusiasts. Global Journal of Engineering and Technology Advances, 16 (1). 087-096. ISSN 2582-5003
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Abstract
Genetic algorithm has emerged as one of the evolutionary computation techniques to solve complex problems that are not continuous, lacking linearity, derivatives and non-deterministic polynomial time problem(NP-Hard).It is a heuristic search and optimization technique that mimics the biological natural selection and survival of the fittest theory and terminates when either a maximum number of generations or a satisfactory level of fitness level has been reached for the population. The algorithm utilizes probability techniques and when structured satisfactory results could be achieved. Care is needed to eliminate convergence to local optimum by applying proper codes and encoding technique, selection and mutation.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/gjeta.2025.24.1.0203 |
Uncontrolled Keywords: | Genetic algorithm; Gene; Mutation; Crossover; Genotype; Fitness function |
Depositing User: | Editor Engineering Section |
Date Deposited: | 22 Aug 2025 09:14 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/5711 |