Developing a neural network approach for intelligent scheduling in GUESS

被引：4

作者：

Liebowitz, J

Rodens, I

Zeide, J

Suen, C

机构：

[1] Univ Maryland Baltimore Cty, Dept Informat Syst, Baltimore, MD 21250 USA

[2] Amer Minor Engn Corp, Kensington, NSW 20895, Australia

[3] Concordia Univ, Ctr Pattern Recognit & Machine Intelligence, Montreal, PQ H3G 1M8, Canada

来源：

EXPERT SYSTEMS | 2000年 / 17卷 / 04期

关键词：

intelligent scheduling; neural networks; expert systems; intelligent systems;

D O I：

10.1111/1468-0394.00140

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The generically used expert scheduling system (GUESS) intelligent scheduling toolkit has been built and applied in various scheduling domains. Previously, GUESS included three major scheduling approaches: a heuristic-based (suggestion tabulator) approach, a hill-climbing algorithm, and a genetic algorithm approach. GUESS has now been expanded to include a neural network scheduling approach. This paper discusses the development, implementation and testing results of the neural network scheduling method within GUESS.

引用

页码：185 / 190

页数：6

共 20 条

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