Mutual information based Pso and its application in travel route optimization

Abstract

To improve the performance of Particle Swarm algorithm in high dimension space, a hybrid Particle Swarm algorithm is proposed based medical image registration. To express the mutual entropy, the current paths are compared with the history paths in an effort to utilize the nature of parallel paradigm of harmony search in order to improve the global search capability and accelerate the search speed. Besides, the formulas are simplified in its application of the traveling salesman problem to make some kind of simplification of time complexity. Compared with the traditional algorithms through experiments, the results demonstrate that the proposed algorithm has been improved to some extent in terms of solution performance and the capacity of jumping out of local minimum.