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Development of a Predictive-Reactive Scheduler using Genetic Algorithms and Simulation-based Scheduling Software

Published

Author(s)

Albert T. Jones, Frank H. Riddick, Luis C. Rabelo

Abstract

Simulation-based scheduling packages are widely used in manufacturing plants around the world. These packages include a large number of canned dispatching rules which produce schedules for both simple and complex production environments. Users can extend these canned rules by adding their own plant-specific rules. In this paper we describe an iterative approach in which we first generate schedules using an optimal search technique called genetic algorithms and then predict how well those schedules perform using the simulation-based scheduling software. We also describe a preliminary information model for a status database which provides the basis for using this iterative approach for reactive scheduling as well.
Proceedings Title
AMPST 96
Conference Location
, USA

Keywords

genetic algorithms, manufacturing, neural networks, scheduling, simulation

Citation

Jones, A. , Riddick, F. and Rabelo, L. (1996), Development of a Predictive-Reactive Scheduler using Genetic Algorithms and Simulation-based Scheduling Software, AMPST 96, , USA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=821206 (Accessed February 23, 2024)
Created June 30, 1996, Updated October 12, 2021