Knowledge-based decision support system for scheduling in a flexible flow system

Decision Support Systems (DSSs) are necessary resources for most complex decision making situations. The environment under which the DSSs function are, for the most part, evolving and, hence the DSSs should have the capability to adapt themselves as per the changes in the characteristics of the environment. An adaptive DSS that can function in a dynamic environment is proposed in this thesis, incorporating simulation modeling and inductive learning, to improve the overall performance of the system.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Business Administration

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Piramuthu, Selwyn

Contributors dc:contributor

• Shaw, Michael J.

• Business Administration, General
• Artificial Intelligence
• Computer Science

Statement dc:rights

• Copyright 1992 Piramuthu, Selwyn

Language dc:language

eng

Identifier

AAI9236571
(UMI)AAI9236571

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/20587