Traits are codings the domain knowledge, i.e. the genes. A series of these combine to make a path. The path is evaluated, based on how close the end-point is to the target. The GA continues the iteration of generations until the goal is found or some other end criterea occurs. Mutation helps prevent a degenerate population, which tends to settle prematurely at a non-optimum solution.
Optimization can improve both the GAs speed and capability to solve problems.
About - Maze Solver Maze solver is a configurable genetic algorithm. It does not find the optimal path, but usually finds a path to the target. If the cell is free, the step is successful, and the current standing point is updated. Then it repeats the same for the rest of the gene's values. The standing point after all steps is called the end-point.