论文部分内容阅读
分布式约束优化问题在多Agent系统中应用十分广泛,它已经作为多Agent分布式推理的一项关键技术,既能够最优化一组分布约束,又能够在一定程度上保护Agent的信息,同时提高解决问题的效率。首先介绍分布式约束优化问题的背景及其算法的发展,对现有解决问题的一些完全算法和不完全算法作出了具体论述,通过从效率、质量、隐私等方面这些算法进行比较和分析,然后介绍在分布式约束优化问题在具体领域中的应用,最后论述分布式约束优化算法目前存在的问题及未来发展方向。
Distributed Constrained Optimization is widely used in multi-agent system. It has been used as a key technology in distributed reasoning of multi-Agent. It can not only optimize a set of distribution constraints but also protect Agent information to a certain extent, Solve the problem of efficiency. Firstly, the background of distributed constrained optimization and the development of its algorithms are introduced. Some existing algorithms and incomplete algorithms for solving problems are discussed in detail. By comparing and analyzing these algorithms from the aspects of efficiency, quality and privacy, The application of distributed constrained optimization in specific fields is introduced. Finally, the existing problems and the future development of distributed constrained optimization are discussed.