Xuesong Yan

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The traveling salesman problem (TSP) is one of the most widely studied NP-hard combinatorial optimization problems and traditional genetic algorithm trapped into the local minimum easily for solving this problem. Particle Swarm Optimization (PSO) algorithm was developed under the inspiration of behavior laws of bird flocks, fish schools and human(More)
Optimization problems arise in many real-world applications. Cultural Algorithms are a class of computational models derived from observing the cultural evolution process in nature, compared with genetic algorithm the cultural algorithms have high convergence speed. Aiming at the disadvantages of basic cultural algorithms like being trapped easily into a(More)
During the space electronic system in carries out the exploratory mission in the deep space, it maybe faced with kinds of violent natural environment, to electric circuit's performance, the volume, the weight and the stability proposed a higher request, the traditional circuit design method already more and more with difficulty satisfied this kind of(More)
Many engineering optimization problems can be state as function optimization with constrained, intelligence optimization algorithm can solve these problems well. Cultural Algorithms are a class of computational models derived from observing the cultural evolution process in nature, cultural algorithms in the optimization of the complex constrained functions(More)
Since data and resources have massive feature and feature of data are increasingly complex, traditional data structures are not suitable for current data anymore. Therefore, traditional single-label learning method cannot meet the requirements of technology development and the importance of multi-label leaning method becomes more and more highlighted.(More)