J4 ›› 2009, Vol. 47 ›› Issue (4): 752-758.

• 计算机科学 • 上一篇    下一篇

一种多目标增量启发式搜索算法

魏唯1,2, 欧阳丹彤1,2, 吕帅1,2, 殷明浩3   

  1. 1. 吉林大学 计算机科学与技术学院, 长春 130012;2. 吉林大学 符号计算与知识工程教育部重点实验室, 长春 130012;3. 东北师范大学 计算机学院, 长春 130024
  • 收稿日期:2008-11-13 出版日期:2009-07-26 发布日期:2009-08-24
  • 通讯作者: 欧阳丹彤 E-mail:ouyang@jlu.edu.cn

A Multiobjective Incremental Heuristic Search Algorithm

WEI Wei1,2, OUYANG Dantong1,2, LV Shuai1,2, YIN Minghao3   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China|2. Key Laboratory ofSymbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China;3. School of Computer Science, Northeast Normal University, Changchun 130024, China
  • Received:2008-11-13 Online:2009-07-26 Published:2009-08-24
  • Contact: OUYANG Dantong E-mail:ouyang@jlu.edu.cn

摘要:

提出一种多目标增量启发式搜索算法, 该算法结合启发式搜索与增量搜索的思想, 当多目标问题搜索图的状态格局发生改变时, 该算法并不是对变化后的问题进行完全重新求解, 而是部分利用了先前搜索保留的信息求解新问题的最优解集, 从而提高了问题求解的效率. 通过Gridworld标准测试问题上的实验测试, 验证了算法的效率.

关键词: 启发式搜索; 增量搜索; 多目标问题; 最优解集

Abstract:

A multiobjective incremental heuristic search algorithm which combines heuristic search with incremental search is put forward. When the state space of the multiobjective problem changes, the algorithm will not resolve the new problem from scratch, but reuse the parts of the information of the previous search to find the set of optimal solutions of the new problem and thus
 the efficiency of resolution is improved. The experiment results of the Gridworld benchmark problem show that the algorithm can solve a series of similar multiobjective problems very efficiently when the state space changes continuously.

Key words: heuristic search, incremental search, multiobjective problems, set of optimal solutions

中图分类号: 

  • TP18