Application of Real Ant Colony Optimization Algorithm to Solve Space and Time Fractional Heat Conduction Inverse Problem
This paper describes method of solution of space fractional and 2D time fractional heat conduction inverse problem. In paper authors considered two models – 1D space fractional heat conduction equation and 2D time fractional heat conduction equation with initial-boundary conditions. To solve inverse heat conduction problem, a functional defining the error of approximate solution must be minimized. To minimize this functional Real Ant Colony Optimization (ACO) algorithm is used. In order to reduce the computational time, the calculations were performed in a parallel (multi-threaded) way. The paper presents examples to illustrate the accuracy and stability of the presented algorithm.