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

页码：228 / 238

页数：11

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