article

A research survey: review of AI solution strategies of job shop scheduling problem

Authors:

Serol BulkanAuthors Info & Claims

Journal of Intelligent Manufacturing, Volume 26, Issue 5

Pages 961 - 973

https://doi.org/10.1007/s10845-013-0837-8

Published: 01 October 2015 Publication History

Abstract

This paper focus on artificial intelligence approaches to NP-hard job shop scheduling (JSS) problem. In the literature successful approaches of artificial intelligence techniques such as neural network, genetic algorithm, multi agent systems, simulating annealing, bee colony optimization, ant colony optimization, particle swarm algorithm, etc. are presented as solution approaches to job shop scheduling problem. These studies are surveyed and their successes are listed in this article.

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cover image Journal of Intelligent Manufacturing

Journal of Intelligent Manufacturing Volume 26, Issue 5

October 2015

216 pages

ISSN:0956-5515

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