An Improved Cellular Genetic Algorithm with Machine-Coded Operators for Real-Valued Optimisation Problems
Journal of Engineering Research and Applied Science, cilt.13, sa.1, ss.2500-2514, 2024 (Hakemli Dergi)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 13 Sayı: 1
- Basım Tarihi: 2024
- Dergi Adı: Journal of Engineering Research and Applied Science
- Sayfa Sayıları: ss.2500-2514
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- İstanbul Üniversitesi Adresli: Evet
Özet
This research introduces an enhanced cellular genetic algorithm employing machine-coded operators specifically tailored for real-valued optimization problems. The utilization of byte-based operators, designed to handle numerical data in a memory-efficient manner, distinguishes this approach. The study systematically evaluates the performance of the proposed algorithm across various test functions, including Ackley, Bohachevsky, Griewank, Holzman, Rastrigin, Rosenbrock, Schaffer, Chichinadze and Sphere. Simulation results reveal that the byte operators consistently outperform traditional counterparts, demonstrating the effectiveness of this novel approach in real-valued optimization scenarios.