Jones, A.
and Rabelo, L.
(1998),
Survey of Job Shop Scheduling Techniques, Encyclopedia of Electrical and Electronics Engineering, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=821200
(Accessed October 31, 2024)
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Survey of Job Shop Scheduling Techniques
Published
Author(s)
, Luis C. Rabelo
Abstract
A large number of approaches to the modeling and solution of job shop scheduling problems have been reported in the Operations Research (OR) literature, with varying degrees of success. These approaches revolve around a series of technological advances that have occurred over the last 35 years. These include mathematical programming, dispatching rules, expert systems, neural networks, genetic algorithms, fuzzy logic, and inductive learning. In this chapter, we will focus on dynamic, job shop problems that are both deterministic and stochastic. We will take anevolutionary view and describe how these technologies have been applied to these problems. To do this, we discuss a few of the most important contributions in each of these technology areas and the most recent trends.Citation
Encyclopedia of Electrical and Electronics Engineering
Pub Type
Encyclopedias
Download Paper
Keywords
manufacturing, operations management, simulation, supply chain management, system integration
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.
Created July 31, 1998, Updated October 12, 2021