Increasing the vertical dimesion affects not only functional problems but also the facial appearance. In particular, when restoring the reduced vertical dimension, it is important to evaluate facial appearance because the change affects the patient’s aesthetics. Cephalometric radiographs can predict changes in the facial appearance through skeletal and vertical classifications using anatomical indicators, and the changes before and after treatment can be easily observed, which could serve as good data in evaluating treatment success. In this study, comparative evaluation was performed through cephalometric radiography, and the aesthetic and functional improvement was confirmed.

It is one of the known methods to obtain the optimal solution using the Ant Colony Optimization Algorithm for the Traveling Salesman Problem (TSP), which is a combination optimization problem. In this paper, we solve the TSP problem by proposing an improved new ant colony optimization algorithm that combines genetic algorithm mutations in existing ant colony optimization algorithms to solve TSP problems in many cities. The new ant colony optimization algorithm provides the opportunity to move easily fall on the issue of developing local optimum values of the existing ant colony optimization algorithm to global optimum value through a new path through mutation. The new path will update the pheromone through an ant colony optimization algorithm. The renewed new pheromone serves to derive the global optimal value from what could have fallen to the local optimal value. Experimental results show that the existing algorithms and the new algorithms are superior to those of existing algorithms in the search for optimum values of newly improved algorithms.