Journals / Sigma Mühendislik ve Fen Bilimleri Dergisi / 2013 / Cilt: 31 - Sayı: 4

MULTI OBJECTIVE FLEXIBLE JOB SHOP SCHEDULING PROBLEMS

Pages
605–623
Publication Date
2013-12-01
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Especially, the meta-heuristic methods used by researchers are rigorously investigated; and meta-heuristic methods for solving multi-objective flexible job shop scheduling problems are suggested.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Flexible job shop scheduling problem, is an extension of the classical job shop scheduling problem.
📊
Key Findings & Data:In Flexible job shop scheduling problem, there are more than one machine with the same features for the same purpose.
💡
Conclusion & Impact:Especially, the meta-heuristic methods used by researchers are rigorously investigated; and meta-heuristic methods for solving multi-objective flexible job shop scheduling problems are suggested.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Flexible job shop scheduling · multi objective scheduling · scheduling

Abstract

Flexible job shop scheduling problem, is an extension of the classical job shop scheduling problem. In Flexible job shop scheduling problem, there are more than one machine with the same features for the same purpose. The problem can be defined as appointing the jobs to the machines (assignment) and ordering the jobs at each machine (sequencing) to serve the desired purpose. Multi-objective flexible job shop scheduling problem is of great importance in production management and combinatorial optimization. Because of the calculation complexity, finding the optimal solution for the actual situation of medium-sized problems is very difficult with traditional optimization methods. In this study, recent works on multi-objective flexible job shop scheduling problems is examined and a comprehensive literature review is presented. Especially, the meta-heuristic methods used by researchers are rigorously investigated; and meta-heuristic methods for solving multi-objective flexible job shop scheduling problems are suggested.

🔖

Cite This Article

KAYA, S., FIĞLALI, N. (2013). MULTI OBJECTIVE FLEXIBLE JOB SHOP SCHEDULING PROBLEMS. Sigma Mühendislik ve Fen Bilimleri Dergisi, Cilt: 31 - Sayı: 4, 605–623. https://ajindex.com/articles/419487

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (12)

  1. Pinedo, M.L., “Scheduling Theory, Algorithms, and Systems”, ISBN: 978-0-387-78934-7 e-ISBN: 978-0-387-78935-4, DOI: 10.1007/978-0-387-78935-4, 2008
  2. Fattahi, P., Mehrabad, M.S., Jolai F., “Mathematical modeling and heuristic approaches to flexible job shop scheduling problems”, J Intell Manuf, 18:331–342, DOI 10.1007/s10845-007-0026-8, 2007
  3. Ho, N.B., Tay, J.C., “Solving Multiple-Objective Flexible Job Shop Problems by Evolution and Local Search”, IEEE Transactions On Systems, Man, And Cybernetics—Part C: Applications And Reviews, Vol. 38, No. 5, 1094-6977, 2008
  4. Kacem, I., Hammadi, S., Borne, P., “Approach by Localization and Multiobjective Evolutionary Optimization for Flexible Job-Shop Scheduling Problems”, IEEE transactions on Systems,Man, and Cybernetics—Part c: Applications and Reviews, Vol. 32, No. 1, 2002
  5. Kacem, I., Hammadi, S., Borne, P., “Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic”, Mathematics and Computers in Simulation 60, 245–276, 2002
  6. Pezzella, F., Morganti, G., Ciaschetti, G., “A genetic algorithm for the Job-Shop Scheduling Problem”, Computers & Operations Research 35, 3202 – 3212, 2008
  7. Chiang, T.C., Lin, H.J., “A simple and effective evolutionary algorithm for multiobjective flexible job shop scheduling”, International Journal of Production Economics, http://dx.doi.org/10.1016/j.ijpe.2012.03.034, (2012)
  8. Li, J., Pan, Q., Xie, S., “An effective shuffled frog-leaping algorithm for multi-objective flexible job shop scheduling problems”, Applied Mathematics and Computation, 218, 9353-9371, (2012)
  9. Li, J., Pan, Q., “Chemical-reaction optimization for flexible job-shop scheduling problems with maintenance activity”, Applied Soft Computing 12, 2896–2912, http://dx.doi.org/10.1016/j.asoc.2012.04.012, (2012)
  10. Wang, L., Zhou, G., Xu, Y., Liu, M., “An enhanced Pareto-based artificial bee colony algorithm for the multi-objective flexible job-shop scheduling”, International Journal Advanced Manufacturing Technology, 60:1111–1123, DOI 10.1007/s00170-011-3665-z, (2012)
  11. Davarzani, Z., Akbarzadeh, M., Khairdoost, N., “Multiobjective Artificial Immune Algorithm for Flexible Job Shop Scheduling Problem”, International Journal of Hybrid Information Technology, Vol. 5, No. 3, July, (2012)
  12. Xiong, J., Tan, X., Yang, K., Xing, L., Chen Y., “A Hybrid Multiobjective Evolutionary Approach for Flexible Job-Shop Scheduling Proble