Knowledge modeling environment for job-shop scheduling problem

Author

Araki, Dai ; Narimatu, Katsumi ; Kojima, Shoichi

Author_Institution

Res. & Dev. Center, Toshiba Corp., Kawasaki, Japan

fYear

1994

fDate

1-4 Mar 1994

Firstpage

456

Lastpage

457

Abstract

The scheduling model and method must be designed to be application-domain dependent so as to reflect a set of constraints, objectives and preferences which reside in the target problem. We analyzed the scheduling process of human experts in a knowledge-base level and have developed a task-specific shell named ARES/SCH. ARES/SCH possesses a primitive task library that is a collection of domain-independent and generic components of scheduling mechanisms. The whole scheduling method can be described as a combinational flow-chart of primitive tasks. Memory module mounting shop (MMS) scheduling is shown as an example of ARES/SCH applications. It was apparent that ARES/SCH contributes to the rapid development of scheduling systems and supports a wide range of scheduling domains

Keywords

knowledge based systems; manufacturing data processing; resource allocation; scheduling; software tools; ARES/SCH; advanced real-world expert system tool; application-domain dependent; combinational flow-chart; domain-independent components; generic components; human experts; integrated AI shell; job-shop scheduling problem; knowledge modeling environment; knowledge-base level; memory module mounting shop scheduling; primitive task library; primitive tasks; scheduling domains; scheduling mechanisms; scheduling model; scheduling process; target problem; task-specific shell; Air transportation; Airports; Engines; Flowcharts; Humans; Job shop scheduling; Manufacturing; Problem-solving; Vehicles; Voice mail;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence for Applications, 1994., Proceedings of the Tenth Conference on

Conference_Location

San Antonia, TX

Print_ISBN

0-8186-5550-X

Type

conf

DOI

10.1109/CAIA.1994.323640

Filename

323640