Adaptive Ant Colony Optimization Algorithm for Earth Observing Satellites Scheduling

Earth observing satellites are platforms equipped with imaging instruments that orbit the Earth in order to take photographs of specific areas. This paper addresses the problem of scheduling observations for a collection of earth observing satellites. This scheduling task is a difficult optimization problem, potentially involving many satellites, hundreds of requests, constraints on when and how to service each request. It is NP-hard in computational complexity. We adopt an adaptive ant colony optimization algorithm to solve it. Its positive feedback mechanism and random search ability make it effective in the search of trade space. Numerical results demonstrate that the algorithm is efficient and can generate a near-optimal feasible schedule for the imaging operations of the satellites.