Greedy randomized adaptive search for dynamic flexible job-shop scheduling

Baykasoğlu A., Madenoğlu F. S., Hamzadayı A.

JOURNAL OF MANUFACTURING SYSTEMS, cilt.56, ss.425-451, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 56
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.jmsy.2020.06.005
  • Dergi Adı: JOURNAL OF MANUFACTURING SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Compendex, Computer & Applied Sciences, INSPEC
  • Sayfa Sayıları: ss.425-451
  • Anahtar Kelimeler: Flexible job shop scheduling, Rescheduling, Dynamic scheduling, GRASP, MANUFACTURING SYSTEM, GENETIC ALGORITHM, GRASP ALGORITHM, OPTIMIZATION, EVOLUTIONARY, SIMULATION, STRATEGY, MODEL
  • Abdullah Gül Üniversitesi Adresli: Evet

Özet

Dynamic flexible job shop scheduling problem is studied under the events such as new order arrivals, changes in due dates, machine breakdowns, order cancellations, and appearance of urgent orders. This paper presents a constructive algorithm which can solve FJSP and DFJSP with machine capacity constraints and sequence-dependent setup times, and employs greedy randomized adaptive search procedure (GRASP). Besides, Order Review Release (ORR) mechanism and order acceptance/rejection decisions are also incorporated into the proposed method in order to adjust capacity execution considering customer due date requirements. The lexicographic method is utilized to assess the objectives: schedule instability, makespan, mean tardiness and mean flow time. A group of experiments is also carried out in order to verify the suitability of the GRASP in solving the flexible job shop scheduling problem. Benchmark problems are formed for different problem scales with dynamic events. The event-driven rescheduling strategy is also compared with periodical rescheduling strategy. Results of the extensive computational experiment presents that proposed approach is very effective and can provide reasonable schedules under event-driven and periodic scheduling scenarios.