Optimization research of distributed fusion system

Now, the SOFF or SFFO ways are generally used to optimize the distributed fusion systems. It can only obtain PBPO Solutions which is suboptimal algorithm. Moreover, the computing is complicated and the corresponding results intensively depend on the initial value. By the study of initial results influence on fusion system, we propose a simultaneous optimization algorithm which is based on ant colony algorithm. As the algorithm not only optimizes the fusion rule of system and decision rules of part, but also doesn't depend initial results. Therefore it's a global optimization algorithm. The results of value tests indicate that the selection of initial value influences the fusion system on large. As independent on the initial value, this algorithm is better than others on performance optimization, undoubtedly, this method proposed in this paper has some reference value on this issue.