摘要
本文介绍优化问题求解的启发式搜索技术及优化问题的神经网络求解技术.前者论述了目前常见的四类启发式搜索技术的原理,并讨论了各类技术的特点;后者论述了神经网络求解优化问题的基本方法,并例举了旅行商、图的划分等优化问题的神经网络求解方法.最后,本文对优化问题求解的启发式搜索和神经网络方法作了比较,并指出了针对这二种方法的进一步研究方向.
Introduces heuristic search techniques and neurocomputing techniques for solving optimization problems. The former deals with the principles and features of the four common kinds of heuristic search techniques. The latter describes the basic method of neurocomputation,and illustrates some optimization problems mapped to neural networks including traveling salesman problem,graph partitioning problem etc. At last,this paper summarizes these two methods,i. e. the AI's method and the neurocomputational method,and points out further research directions.
出处
《华东船舶工业学院学报》
1993年第3期61-67,共7页
Journal of East China Shipbuilding Institute(Natural Science Edition)
关键词
人工智能
启发式算法
神经网络
artificial intelligence
heuristic algorithm
neural networks
