Fitness Function Optimized in Genetic Algorithm for Fabric Dynamic Simulation

This paper proposes an improved algorithm to optimize the fitness function, with which the iteration times can be efficiently reduced in simulating fabric pattern deformation when it flags in the wind. Relying on a genetic algorithm model used to its deformation, an iteration method is employed and performed when genes are substituted with positions and color values of each point on the fabric surface. Relations are found during optimization between variables of the fitness function and the fabric attributes. The optimization is performed and improved to enhance the simulation. The result occurs in effectively reducing the iteration times while the actual visual effect is still satisfactory.