Approach of remotely sensed data processing task scheduling problem based on ant colony optimization

With the development of remote sensing technology, remote sensing data frequency-intensive has received and processed, the demand of remote sensing applications has kept an increasing growth. The management and planning for multi-source remote sensing data processing became very complicated with the evolution of remote sensed application requests. The way of effect management and scheduling can improve utility of processing resources and sufficiently exert abilities of remote sensing processing center. Based on the multi-objective optimization characteristic of the problem, this paper presents the mathematical model of the problem. An ant colony optimization algorithm is proposed for solving this problem. At last, experiments results show the effectiveness of our approach compared with the results of heuristic algorithm and simulated annealing algorithm.