Genetic algorithm: Difference between revisions

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Revision as of 13:26, 30 October 2023

Maths, information technology and management - artificial intelligence (AI).

An algorithm is a set of pre-defined (and often automated) steps for making a calculation or decision.

Genetic algorithms are a further development of algorithms, inspired by genetics and natural selection in biology.

In particular, the evolutionary concepts of "survival of the fittest" and mutation.


Genetic algorithms incorporate:

  • Random elements in generating a group of candidate solutions to a problem; and
  • Iterative testing of candidates to identify the fittest to proceed to the next cycle;
  • Further cycles of modification - including random elements in the modifications - and re-testing of the surviving and modified candidate solutions.


Genetic algorithms can find the best solutions
"Royston Da Costa, assistant treasurer at Ferguson, points out: “ChatGPT has democratised artificial intelligence, making it easier to use for non-technical staff.
This has opened up new opportunities for adoption across treasury.”


According to Da Costa, the possible applications of AI in treasury include reconciliation, forecasting, and optimisation of actions such as hedging, investing, borrowing and trading.
“AI can use optimisation (genetic) algorithms that consider multiple objectives, constraints, and risks to find the best solutions,” he adds."
AI in cash management: what is the smart move? - The Treasurer online - 25 October 2023.


See also