A Multi-Objective A* Search Based on Non-dominated Sorting

被引：0
|
作者：
Haqqani, Mohammad [1 ]
Li, Xiaodong [1 ]
Yu, Xinghuo [1 ]
机构：
[1] RMIT Univ, Sch Comp Sci & Informat Technol, Melbourne, Vic, Australia
来源：
SIMULATED EVOLUTION AND LEARNING (SEAL 2014) | 2014年 / 8886卷
关键词：
A* Search; Multi-Objective Optimization; Non-dominated Sorting; PATHS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper present a Non-dominated Sorting based Multi Objective A* Search (NSMOA*) algorithm for multi-objective search problem. It is an extension of the New Approach for Multi Objective A* Search (NAMOA*). This study aims to improve the selection phase of the NAMOA* algorithm which can affect the performance of the algorithm considerably, especially when the number of non-dominated solutions increases to a large number during the search. This research proposes a new sorting method that allows selection and expansion of the partial solutions be carried out more efficiently. The results demonstrate that our algorithm expands fewer nodes and explores a smaller region of solution space using the same heuristic.
引用
收藏
页码：228 / 238
页数：11
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