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

ÇALIŞ USLU B., BULKAN S.

JOURNAL OF INTELLIGENT MANUFACTURING, cilt.26, sa.5, ss.961-973, 2015 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 26 Sayı: 5
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1007/s10845-013-0837-8
  • Dergi Adı: JOURNAL OF INTELLIGENT MANUFACTURING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.961-973
  • Anahtar Kelimeler: Artificial intelligence, Scheduling, Metaheuristic, ANT COLONY OPTIMIZATION, GENETIC ALGORITHM, NEURAL-NETWORKS, PARALLEL MACHINES, SEARCH, TARDINESS, HEURISTICS, RESOURCE, DESIGN
  • Marmara Üniversitesi Adresli: Evet

Özet

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.