Genetic Algorithms And Job Shop Scheduling

    Authors

    J. E. Biegel;J. J. Davern

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    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

    Share

    COinS