Knowledge base maintenance using cultural algorithms: Application to the DLMS manufacturing process planning system at Ford Motor Company

被引：0

作者：

Rychtyckyj, N ^{[1
]}

Reynolds, RG ^{[1
]}

机构：

[1] Ford Motor Co, Informat Technol Serv, Dearborn, MI 48121 USA

来源：

CEC'02: PROCEEDINGS OF THE 2002 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2 | 2002年

关键词：

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：

Ford's Direct Labor Management System (DLMS) is a fully deployed application that is being utilized at Ford's assembly plants throughout the world. DLMS has been in production since 1990 and maintainability of the knowledge base has become very difficult over time due to changes in the following areas: business environment, processes and physical concepts being modeled, and underlying hardware and software architecture. We have previously described how Cultural Algorithms can be used in a top-down and bottom-up fashion to re-engineer a dynamic semantic network-based knowledge base. [1][2] In this paper we compare the two approaches and discuss how they can be used in tandem to re-engineer a semantic network.

引用

页码：855 / 860

页数：6