So sánh phương pháp

	Thuật toán Di truyền Xác định	Thuật toán di truyền
Lĩnh vực	Mô phỏng	Tối ưu hóa
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1975–1989	1975
Người khởi xướng	Goldberg, D. E.; Holland, J. H.	John Henry Holland
Loại	Deterministic evolutionary optimization	Population-based metaheuristic
Công trình gốc	Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading, MA. ISBN: 9780201157673	Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
Tên gọi khác	DGA, Deterministic EA, Deterministic Evolutionary Algorithm, Deterministic Selection GA	GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
Liên quan	5	5
Tóm tắt	A Deterministic Genetic Algorithm (DGA) applies the structural framework of evolutionary computation — population, selection, crossover, and replacement — using entirely deterministic operators and fixed decision rules instead of stochastic sampling. By eliminating randomness, the algorithm becomes fully reproducible: running it twice on the same problem yields identical solutions, making it tractable for rigorous benchmarking, reproducibility studies, and systems where stochasticity is undesirable.	A genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail.