Polyhedron and Polyhedra Vol.2 vs Genetic Algorithms

Polyhedron and Polyhedra Volume 2 is a collection of 4 kepler-poinsot polyhedra, 53 uniform star polyhedra, their duals and polyhedral compounds of them. This is also an application which helps you to learn about or explore these mathematical solids. Without knowledge of mathematics or polyhedron, you can easily interact with the 3d solids by this application. So, you will become more familiar with the polyhedrons, and you may enjoy these abstract solids as fascinating formative arts. The main advantage of this app is that it offers a large variety of polyhedral compounds of identical uniform star polyhedra and their duals. By choosing a model, and by setting colors and parameters optionally, you will find various types of 3d shapes including wonderful shapes, mysterious artistic shapes, and strange eccentric shapes, which will be interesting for you. Features: - Swipe or touch gesture will rotate, zoom or move the object. So, you can observe it from various angles or positions. (You can observe it even from inside.) - Switches between showing and hiding each face of the polyhedron, and switches between showing and hiding each component of the compound - Function to display the edges of the polyhedra with selectable thickness and color - For each kepler-poinsot polyhedron, each uniform star polyhedron and each dual of uniform star polyhedron, the app can provide the compound from 14 to 22 kinds (more than 1200 in total). - Many color patterns for the faces of the polyhedron. - Functions to display basic informations about the polyhedron, and to access the wikipedia sites about the related items - Slider controllers to reduce z-fighting (screen flicker) - Save PNG images to camera roll

Genetic algorithms are one of the search and optimisation methods. The aim of optimisation is to increase efficiency in reaching a certain optimal value. Genetic algorithms are based on the mechanisms of natural selection and heredity. The basic genetic algorithm is built from three operations: reproduction, crossing, and mutation. Genetic algorithms operate on populations of coding sequences and use random selection rules to search for the global optimal value. However, these random rules are defined to give the appropriate direction of the search (through various selection mechanisms or scaling of fitness functions). This basic procedure is enhanced by certain genetic manipulations, such as those seen in nature. They include the mechanisms of dominance, diploidy, inversion, and other reconfiguration mechanisms that occur at the chromosome level. Users can design textual or graphical scaling patterns for the fitness function and then use them in simulations. The application also provides a preliminary analysis of statistical data concerning the distribution of the fitness function in the population. The program allows the user to compare non-random procedures (e.g. scaling of fitness functions) by using the same pseudorandom sequence (for procedures requiring randomization, such as selection, etc.) in successive simulations. In order to better visualize the genetic processes taking place during the simulation, some of them are presented to the user using animations. Additionally, some of the data obtained from simulations can be saved and shared.