A multi-objective simulation-based optimization approach for inventory replenishment problem with premium freights in convergent supply chains

AVCI M. G., SELİM H.

OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, cilt.80, ss.153-165, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 80
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.omega.2017.08.016
  • Dergi Adı: OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.153-165
  • Anahtar Kelimeler: Inventory replenishment, Supply chain risk, Premium freight, Multi-objective optimization, Simulation-based optimization, Differential evolution, SERVICE PARTS, DISRUPTIONS, FRAMEWORK, ALGORITHM, DESIGN, RISK
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

In this study, a multi-objective simulation-based optimization approach is developed to solve inventory replenishment problem with premium freights in convergent supply chains. In this context, a decomposition-based multi-objective differential evolution algorithm (MODE/D) is used to determine demand forecast adjustment factor, safety stock and supplier flexibility parameters that minimize total holding cost, inbound and outbound premium freight ratios simultaneously. The proposed approach is applied a set of problem instances and the performance of the proposed approach is evaluated in comparison with the performance of non-dominated sorting genetic algorithm-II (NSGA-II). Furthermore, the proposed approach is applied to a multi-national automotive supply chain spread on Europe. The results reveal that the proposed approach is effective in solving inventory replenishment problem with premium freights in convergent supply chains. (C) 2017 Elsevier Ltd. All rights reserved.