An Improved Cellular Genetic Algorithm with Machine-Coded Operators for Real-Valued Optimisation Problems

  • Sevgi Akten Karakaya Istanbul University
  • Mehmet Hakan Satman Istanbul University
Keywords: Cellular Genetic Algorithm, Machine-Coded (Byte-Based) Operators, Real-Valued Optimization

Abstract

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.

Author Biographies

Sevgi Akten Karakaya, Istanbul University

Istanbul, Turkey

Mehmet Hakan Satman, Istanbul University

Istanbul, Turkey

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Published
2024-06-30
How to Cite
Akten Karakaya, S., & Satman, M. H. (2024). An Improved Cellular Genetic Algorithm with Machine-Coded Operators for Real-Valued Optimisation Problems. Journal of Engineering Research and Applied Science, 13(1), 2500-2514. Retrieved from http://journaleras.com/index.php/jeras/article/view/334
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Articles