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Genetic Algorithms

GA

259 papers tagged archive 2025-07-28

Introduced by Jan Scholz in Genetic Algorithms and the Traveling Salesman Problem a historical Review

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Genetic Algorithms are search algorithms that mimic Darwinian biological evolution in order to select and propagate better solutions.

PaperSource

Papers archive 2025-07-28

30 shown of 259, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 151 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Evolutionary Algorithms21
Diversity11
Management10
Scheduling10
feature selection10
Reinforcement Learning (RL)9
Combinatorial Optimization8
Deep Learning7
CPU6
Cloud Computing6
regression6
reinforcement-learning6
valid6
Fairness5
Reinforcement Learning5
global-optimization5
Artificial Life4
BIG-bench Machine Learning4
Benchmarking4
Computational Efficiency4

Usage over time archive 2025-07-28

Papers per year tagged with GA: 2017 to 2025, peak 53 53 0 2017: 1 paper 2017 2018: 1 paper 2018 2019: 21 papers 2019 2020: 36 papers 2020 2021: 43 papers 2021 2022: 39 papers 2022 2023: 46 papers 2023 2024: 53 papers 2024 2025: 19 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (259 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Heuristic Search Algorithms

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