Genetic algorithm
From ACT Wiki
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
- Algorithmic trading
- Artificial intelligence (AI)
- ChatGPT
- Forecast
- Google Gemini
- Hedging
- Heuristic
- Information technology
- Investment
- Iteration
- Optimisation
- Reconciliation
- Stochastic
- Trading
