In this issue, I propose a specific solution to the reconstruction challenge that arises during the implementation of evolutionary algorithms.
The idea is outlined as follows:
Following certain perturbation operations (or their equivalent in genetic programming), the vector typically containing all vertices within a circle would be divided into what we'll refer to as "paths." Each path would consist of a vector with a minimum size of 2 (or possibly 1, depending on further considerations) - representing the initial cycle. Subsequently, we would iteratively apply the nearest neighbor heuristic to each path, attaching the closest vertex to the given path. If a vertex is already assigned to a different path (associated with the appropriate cycle), the paths would be combined to form a new, longer path. This iterative process would continue until both cycles are fully reconstructed.
In this issue, I propose a specific solution to the reconstruction challenge that arises during the implementation of evolutionary algorithms.
The idea is outlined as follows:
Following certain perturbation operations (or their equivalent in genetic programming), the vector typically containing all vertices within a circle would be divided into what we'll refer to as "paths." Each path would consist of a vector with a minimum size of 2 (or possibly 1, depending on further considerations) - representing the initial cycle. Subsequently, we would iteratively apply the nearest neighbor heuristic to each path, attaching the closest vertex to the given path. If a vertex is already assigned to a different path (associated with the appropriate cycle), the paths would be combined to form a new, longer path. This iterative process would continue until both cycles are fully reconstructed.