Title

Rapid modeling and discovery of priority dispatching rules: An autonomous learning approach

Authors

Authors

C. D. Geiger; R. Uzsoy;H. Aytug

Comments

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Abbreviated Journal Title

J. Sched.

Keywords

priority dispatching rules; single machine; rule discovery; genetic; programming; BATCH-PROCESSING MACHINE; INCOMPATIBLE JOB FAMILIES; GENETIC ALGORITHM; MANUFACTURING SYSTEMS; SHOP PROBLEM; METHODOLOGY; ENVIRONMENT; TARDINESS; Engineering, Manufacturing; Operations Research & Management Science

Abstract

Priority-dispatching rules have been studied for many decades, and they form the backbone of much industrial scheduling practice. Developing new dispatching rules for a given environment, however, is usually a tedious process involving implementing different rules in a simulation model of the facility under study and evaluating the rule through extensive simulation experiments. In this research, an innovative approach is presented, which is capable of automatically discovering effective dispatching rules. This is a significant step beyond current applications of artificial intelligence to production scheduling, which are mainly based on learning to select a given rule from among a number of candidates rather than identifying new and potentially more effective rules. The proposed approach is evaluated in a variety of single machine environments, and discovers rules that are competitive with those in the literature, which are the results of decades of research.

Journal Title

Journal of Scheduling

Volume

9

Issue/Number

1

Publication Date

1-1-2006

Document Type

Article

Language

English

First Page

7

Last Page

34

WOS Identifier

WOS:000234552900002

ISSN

1094-6136

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