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.
A muhiobjective incremental heuristic search algorithm which combines heuristic search with incremental search is put forward. When the state space of the muhiobjective 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 muhiobjective problems very efficiently when the state space changes continuously.
出处
《吉林大学学报（理学版）》
CAS
CSCD
北大核心
2009年第4期752-758,共7页
Journal of Jilin University:Science Edition
基金
国家自然科学基金(批准号:60773097
60873044
60803102
60873148)
教育部博士学科点基金(批准号:20050183065
20060183044)
吉林省科技发展计划项目基金(批准号:20060532
20080107)
吉林省青年科研基金(批准号:20080617)
关键词
启发式搜索
增量搜索
多目标问题
最优解集
heuristic search
incremental search
muhiobjective problems
set of optimal solutions
