游戏引擎最短路径搜索优化遗传算法设计

为满足游戏地图中最短路径搜索求解, 提出了一种优化的自适应遗传算法。该算法采用与游戏地图中节点数和弧段数相关联的节点复杂度算子, 结合种群的整体情况和进化潜力来设定自适应遗传算法的交叉率和变异率。实验表明, 该算法避免了搜索结果陷入局部最优解, 确保最短路径的搜索成功率及提高搜索速度, 在游戏引擎设计中具有一定的实用价值。...

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Bibliographic Details
Published in计算机应用研究 Vol. 31; no. 1; pp. 76 - 79
Main Author 黎忠文 覃志东 王全宇 倪仲余
Format Journal Article
LanguageChinese
Published 西华大学数学与计算机学院,成都610039 2014
成都大学信息科学与技术学院,成都,610106%东华大学计算机科学与技术学院,上海,201620%成都大学信息科学与技术学院,成都610106
Subjects
交叉率
地图
最短路径
节点复杂度算子
遗传算法
genetic algorithm
遗传算法
交叉率
地图
最短路径
node complexity operator
crossover probability
map
节点复杂度算子
shortest path
Online AccessGet full text
ISSN1001-3695
DOI10.3969/j.issn.1001-3695.2014.01.017

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Summary:为满足游戏地图中最短路径搜索求解, 提出了一种优化的自适应遗传算法。该算法采用与游戏地图中节点数和弧段数相关联的节点复杂度算子, 结合种群的整体情况和进化潜力来设定自适应遗传算法的交叉率和变异率。实验表明, 该算法避免了搜索结果陷入局部最优解, 确保最短路径的搜索成功率及提高搜索速度, 在游戏引擎设计中具有一定的实用价值。
Bibliography:51-1196/TP
genetic algorithm shortest path node complexity operator crossover probability map
In order to meet the shortest-path searching in game map, this paper presented an optimized adaptive genetic algorithm. It used the environment operator which was associated with the number of nodes and arcs of the graph to set the crossover probability and the mutation probability considering the whole population distribution and evolutionary potential. Experiments show that the algorithm can avoid falling into local optimal solutions, ensure the search success rate, and improve the search speed. It provides some valuable work in game engine designing.
LI Zhong-wen, QIN Zhi-dong, WANG Quan-yu, NI Zhong-yu （1. School of h（ormation Science ＆ Technology, Chengdu University, Chengdu 610106, China; 2. School of Computer Science ＆, Technology, Donghua University, Shanghai 201620, China; 3. School of Mathematics ＆ Computer Engineering, Xihua University, Chengdu 610039, China）
ISSN:1001-3695
DOI:10.3969/j.issn.1001-3695.2014.01.017