LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

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

Photo by theblowup from unsplash

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… Click to show full 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.

Keywords: supply; replenishment problem; multi objective; inventory replenishment; approach; problem

Journal Title: Omega
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.