Multi-objective fuzzy parallel machine scheduling problems under fuzzy job deterioration and learning effects

ARIK O. A., TOKSARI M. D.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, sa.7, ss.2488-2505, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1080/00207543.2017.1388932
  • Dergi Adı: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.2488-2505
  • Anahtar Kelimeler: parallel machines, fuzzy deterioration, fuzzy learning, due date assignment, local search, DEPENDENT PROCESSING TIMES, TOTAL COMPLETION-TIME, SINGLE-MACHINE, MINIMIZING MAKESPAN, FLOW-SHOP, EARLINESS/TARDINESS COSTS, COMPLEXITY ANALYSIS, PRECEDENCE RELATION, GENETIC ALGORITHMS, 2-MACHINE FLOWSHOP
  • Erciyes Üniversitesi Adresli: Evet

Özet

This paper investigates a multi-objective parallel machine scheduling problem under fully fuzzy environment with fuzzy job deterioration effect, fuzzy learning effect and fuzzy processing times. Due dates are decision variables for the problem and objective functions are to minimise total tardiness penalty cost, to minimise earliness penalty cost and to minimise cost of setting due dates. Due date assignment problems are significant for Just-in-Time (JIT) thought. A JIT company may want to have optimum schedule by minimising cost combination of earliness, tardiness and setting due dates. In this paper, we compare different approaches for modelling fuzzy mathematical programming models with a local search algorithm based on expected values of fuzzy parameters such as job deterioration effect, learning effect and processing times.