Integrating simulation modelling and multi criteria decision making for customer focused scheduling in job shops

GÜÇDEMİR H., SELİM H.

SIMULATION MODELLING PRACTICE AND THEORY, cilt.88, ss.17-31, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 88
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.simpat.2018.08.001
  • Dergi Adı: SIMULATION MODELLING PRACTICE AND THEORY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.17-31
  • Anahtar Kelimeler: Job shop scheduling, Multi-criteria decision making, Simulation, Customer relationship management, ANALYTIC HIERARCHY PROCESS, TABU SEARCH ALGORITHM, LOT STREAMING PROBLEM, BUSINESS MARKETS, FLOW-TIME, TRANSPORTATION, ENVIRONMENTS, COLONY, RULES
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Today, customer centricity is an important strategy in business-to-business markets and manufacturing companies need decision support systems that provide adequate information for customer centric applications. This study proposes an integrated decision support system that combines simulation modelling and multi-criteria decision making. More specifically, job shop lot streaming problem is dealt with, and it is aimed to determine the best dispatching rules to schedule batches on machines. To this aim, three renowned performance-oriented criteria; (i) mean flow time, (ii) percentage of tardy orders, (iii) makespan and one customer-oriented criterion; (iv) mean percentage deviation from the customer expectations are considered. Effect of different classical and customer-oriented dispatching rules on these performance criteria are investigated. The performance criteria are weighted using analytical hierarchy process by considering the level of bottleneck resource utilization and customer importance weights. The results reveal that customer-oriented dispatching rules provide better outcomes in case of high level of bottleneck resource utilization and high fluctuation amongst the customer importance weights.