Minimizing the earliness/tardiness costs on parallel machine with learning effects and deteriorating jobs: a mixed nonlinear integer programming approach

TOKSARI M. D., Guener E.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, cilt.38, ss.801-808, 2008 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1007/s00170-007-1128-3
  • Dergi Adı: INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.801-808
  • Anahtar Kelimeler: scheduling, earliness, tardiness, learning effect, deterioration jobs, parallel machine, sequence-dependent setup time, common due date, EARLINESS-TARDINESS PENALTIES, DEPENDENT PROCESSING TIMES, TOTAL COMPLETION-TIME, DUE-DATE ASSIGNMENT, SINGLE-MACHINE, SCHEDULING JOBS, FLOW-SHOP, SHAPED POLICIES, ALGORITHMS, MAKESPAN
  • Erciyes Üniversitesi Adresli: Hayır

Özet

In this study, we introduce a mixed nonlinear integer programming formulation for parallel machine earliness/tardiness (ET) scheduling with simultaneous effects of learning and linear deterioration, sequence-dependent setups, and a common due-date for all jobs. By the effects of learning and linear deterioration, we propose that the processing time of a job is defined by increasing function of its execution start time and position in the sequence. The developed model allows sequence-dependent setups and sequence-dependent early/tardy penalties. The model can easily provide the optimal solution to problems involving about eleven jobs and two machines.