项目名称: 头脑风暴优化算法研究及在无线传感器网络中的应用
项目编号: No.61273367
项目类型: 面上项目
立项/批准年度: 2013
项目学科: 自动化技术、计算机技术
项目作者: 史玉回
作者单位: 西交利物浦大学
项目金额: 78万元
中文摘要: 个体聚类和个体更新是头脑风暴优化算法的两大核心部分。本课题首先分析和验证不同个体聚类方法和个体更新方法对头脑风暴优化算法性能的影响,在此基础上设计能更好平衡算法收敛和发散的头脑风暴优化算法;然后分析、研究和设计能求解约束优化问题或多目标优化问题的头脑风暴优化算法,使之能更好地解决更为广泛的实际应用问题;最后,本课题将设计改进的头脑风暴优化算法来优化设计无线传感器网络。头脑风暴优化算法是受人类集思广益方法之一头脑风暴方法的启发提出来的。人是世界上最高等、最智能的动物,因而基于头脑风暴方法提出的优化算法应具有一定的求解优化问题的优势,有望成为一有效的新算法。预期的研究成果是群体智能研究领域的开拓性研究,具有一定的前瞻性。研究成果将在理论研究和实际应用中取得创新成果,为商业应用奠定坚实基础。
中文关键词: 头脑风暴优化算法;群体智能;演化计算;机器学习;无线传感器网络
英文摘要: Individual clustering and individual updating are two key operations in the brain storm optimization algorithm. In this project, we first will analyze the influence of individual clustering methods and/or individual updating methods on the performance of the brain storm optimization algorithm,then we will design a brain storm optimization algorithm which can better balance between the convergence and divergence. Second, we will modify the brain storm optimizton algorithm to solve optimization problems with constraints and multi-objective optimization problems in order to to suit for solving wider range of real application problems. Finally, the brain storm optimization algorithm will be applied to solve optimization problems existed in the wireless sensor networks. The brain storm optimization algorithm is inspired by the human brainstorming process. Human being is the most intelligent animals in the world, therefore, intuitively, it should be superior to other swarm intelligence algorithms which are inspired by animals with lower level intelligence. The project is expected to make progress in both theory and applications.
英文关键词: brain storm optimization algorithm;swarm intelligence;evolutionary computation;machine learning;wireless sensor network