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Publication summary

Author(s): Albert Jones and Luis C. Rabelo

Publication date: August 1998

Citation: Albert Jones and Luis C. Rabelo: "Survey of Job Shop Scheduling Techniques," NISTIR, National Institute of Standards and Technology, Gaithersburg, MD, 1998.

Key words: manufacturing, operations management, simulation, system integration, supply chain management

Availability:

• Postscript
• Portable Document Format
• A paper copy of this document is available by contacting Kristy Thompson [web,email]

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.

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