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


ÇALIŞ USLU B. , BULKAN S.

JOURNAL OF INTELLIGENT MANUFACTURING, vol.26, no.5, pp.961-973, 2015 (Journal Indexed in SCI) identifier

  • Publication Type: Article / Review
  • Volume: 26 Issue: 5
  • Publication Date: 2015
  • Doi Number: 10.1007/s10845-013-0837-8
  • Title of Journal : JOURNAL OF INTELLIGENT MANUFACTURING
  • Page Numbers: pp.961-973

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.