Genetic Algorithm

28.11.2023 · AE531128
A Genetic Algorithm is a method in evolutionary optimization that solves problems by mimicking natural evolution. Imagine a survival contest where each participant (solution) has traits (parameters). These solutions breed and mutate, creating new generations. The fittest solutions, judged by a fitness function, survive to breed again. Over time, this process 'evolves' increasingly effective solutions. It's like nature's trial-and-error but used for complex problems like route planning, where finding the best or a good-enough solution is essential.
28.11.2023 · AE531128

Selection

In evolutionary optimization, selection is like a survival test for candidate solutions, deciding which ones get to 'reproduce.' Selection operators are the rules determining wh...
28.11.2023 · AE531128

Variation

In evolutionary optimization, variation is the process of introducing diversity into the population of solutions. Like genetic mutations and breeding in nature, it involves alte...
28.11.2023 · AE531128

Replication

In evolutionary optimization, replication is like making copies of the best solutions. Imagine a survival contest where top performers are cloned. These copies then undergo chan...