Ionospheric Disturbance Optimization

This paper proposes a heuristic optimization algorithm based on the mechanism of planetary ionospheric perturbations, namely the Ionospheric Disturbance Optimization (IDO) algorithm. This algorithm simulates the physical process of electron density perturbations in the planetary ionosphere, introduces local perturbations and propagation mechanisms, and achieves an organic combination of global and local search. The algorithm is modeled and analyzed using plain text mathematical formulas, including core mechanisms such as individual initialization, perturbation updates, propagation attenuation, and fitness selection. This paper describes in detail the algorithm design principles, mathematical model, iterative strategy, and pseudocode implementation. The algorithm's heuristic properties and global convergence capability are analyzed, and its potential application value in continuous optimization problems is explored. This algorithm can be theoretically analyzed without relying on complex experimental data and is suitable for solving multidimensional continuous optimization problems.