A Memory Search Algorithm for Path Finding Problems Compared with a Genetic Algorithm

被引：0

作者：

Kunzli, Michael ^{[1
]}

Meier, Peter ^{[1
]}

Dornberger, Rolf ^{[2
]}

机构：

[1] Univ Appl Sci & Arts Northwestern Switzerland, Inst Informat Syst, Sch Business, Olten, Switzerland

[2] Univ Appl Sci & Arts Northwestern Switzerland, Inst Informat Syst, Sch Business, Basel, Switzerland

来源：

2016 4TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL AND BUSINESS INTELLIGENCE (ISCBI) | 2016年

关键词：

memory search; brute force; genetic algorithm; path planning; robotic path finding problem; optimization; shortest path;

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 proposes a new heuristic called memory search algorithm, extending brute force algorithms, for solving path finding problems. The memory search algorithm, its development and functionality are discussed. A comparison between a genetic algorithm and the memory search algorithm for solving path finding problems is presented. Although genetic algorithms are known to solve complex path finding problems very well, the results in this paper illustrate how efficient the memory search heuristic is. Furthermore, limitations of both algorithms, the genetic algorithm and the memory search algorithm, are identified and possible extensions are discussed.

引用

页码：66 / 73

页数：8