Solving comprehensive dynamic job shop scheduling problem by using a GRASP-based approach


Baykasoglu A., Karaslan F. S.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, cilt.55, sa.11, ss.3308-3325, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 55 Sayı: 11
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1080/00207543.2017.1306134
  • Dergi Adı: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.3308-3325
  • Anahtar Kelimeler: dynamic job shop scheduling, GRASP, combinatorial optimisation, rescheduling, job shop control, VARIABLE NEIGHBORHOOD SEARCH, DEPENDENT SETUP TIMES, DISPATCHING RULES, MACHINE BREAKDOWNS, GENETIC ALGORITHMS, SIMULATION, OPTIMIZATION, ENVIRONMENT, METAHEURISTICS, PERFORMANCE
  • Abdullah Gül Üniversitesi Adresli: Hayır

Özet

There are many dynamic events like new order arrivals, machine breakdowns, changes in due dates, order cancellations, arrival of urgent orders etc. that makes static scheduling approaches very difficult. A dynamic scheduling strategy should be adopted under such production circumstances. In the present study an event driven dynamic job shop scheduling mechanism under machine capacity constraints is proposed. The proposed method makes use of the greedy randomised adaptive search procedure (GRASP) by also taking into account orders due dates and sequence-dependent set-up times. Moreover, order acceptance/rejection decision and Order Review Release mechanism are integrated with scheduling decision in order to meet customer due date requirements while attempting to execute capacity adjustments. We employed a goal programming-based logic which is used to evaluate four objectives: mean tardiness, schedule unstability, makespan and mean flow time. Benchmark problems including number of orders, number of machines and different dynamic events are generated. In addition to event-driven rescheduling strategy, a periodic rescheduling strategy is also devised and both strategies are compared for different problems. Experimental studies are performed to evaluate effectiveness of the proposed method. Obtained results have proved that the proposed method is a feasible approach for rescheduling problems under dynamic environments.