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, vol.80, pp.153-165, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 80
  • Publication Date: 2018
  • Doi Number: 10.1016/j.omega.2017.08.016
  • Journal Name: OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Page Numbers: pp.153-165
  • Keywords: Inventory replenishment, Supply chain risk, Premium freight, Multi-objective optimization, Simulation-based optimization, Differential evolution, SERVICE PARTS, DISRUPTIONS, FRAMEWORK, ALGORITHM, DESIGN, RISK
  • Dokuz Eylül University Affiliated: Yes

Abstract

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.