Genetic Algorithm – An evolutionary optimization method inspired by natural selection. Each “individual” is a backtest pass with a set of parameters (genes) and a fitness score. The algorithm starts with a population of random parameter sets, evaluates fitness, then iteratively creates new generations by selecting the fittest, applying crossover (mixing genes from parents) and mutation (randomly altering genes). cTrader’s optimizer offers a Genetic Algorithm option, which “emulates natural selection” and stops when fitness improvements stagnate. MT5’s “Fast Genetic Algorithm” does the same: it repeatedly selects the best runs by the chosen criterion and crosses/mutates them until no further improvements occur. Genetic optimization is much faster than brute-force for many parameters, while still finding near-optimal solutions.

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