Title

Genetic Algorithms And Job Shop Scheduling

Authors

Authors

J. E. Biegel;J. J. Davern

Comments

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Abbreviated Journal Title

Comput. Ind. Eng.

Keywords

Computer Science, Interdisciplinary Applications; Engineering, ; Industrial

Abstract

We describe applications of Genetic Algorithms (GAs) to the Job Shop Scheduling (JSS) problem. More specifically, the task of generating inputs to the GA process for schedule optimization is addressed. We believe GAs can be employed as an additional tool in the Computer Integrated Manufacturing (CIM) cycle. Our technique employs an extension to the Group Technology (GT) method for generating manufacturing process plans. It positions the GA scheduling process to receive outputs from both the automated process planning function and the order entry function. The GA scheduling process then passes its results to the factory floor in terms of optimal schedules. An introduction to the GA process is discussed first. Then, an elementary n-task, one processor (machine) problem is provided to demonstrate the GA methodology in the JSS problem arena. The technique is then demonstrated on an n-task, two processor problem, and finally, the technique is generalized to the n-tasks on m-processors (serial) case.

Journal Title

Computers & Industrial Engineering

Volume

19

Issue/Number

1-4

Publication Date

1-1-1990

Document Type

Article; Proceedings Paper

Language

English

First Page

81

Last Page

91

WOS Identifier

WOS:A1990EQ44400018

ISSN

0360-8352

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