A tri-level optimization model for inventory control with uncertain demand and lead time

Abstract

We propose an inventory control model for an uncapacitated warehouse in a manufacturing facility under demand and lead time uncertainty. The objective is to make ordering decisions to minimize the total system cost. We introduce a two-stage tri-level optimization model with a rolling horizon to address the uncertain demand and lead time regardless of their underlying distributions. In addition, an exact algorithm is designed to solve the model. We compare this model in a case study with three decisionmaking strategies: optimistic, moderate, and pessimistic. Our computational results suggest that the performances of these models are either consistently inferior or highly sensitive to cost parameters (such as holding cost and shortage cost), whereas the new tri-level optimization model almost always results in the lowest total cost in all parameter settings. AbstractWe propose an inventory control model for an uncapacitated warehouse in a manufacturing facility under demand and lead time uncertainty. The objective is to make ordering decisions to minimize the total system cost. We introduce a two-stage tri-level optimization model with a rolling horizon to address the uncertain demand and lead time regardless of their underlying distributions.In addition, an exact algorithm is designed to solve the model. We compare this model in a case study with three decision-making strategies: optimistic, moderate, and pessimistic. Our computational results suggest that the performances of these models are either consistently inferior or highly sensitive to cost parameters (such as holding cost and shortage cost), whereas the new trilevel optimization model almost always results in the lowest total cost in all parameter settings.

Strategic rationing and freshness keeping of perishable products under transportation disruptions and demand learning

“…With respect to uncontrollable delivery lead time, the majority of existing research focuses on examining how delivery lead time plays an important role in decisions such as inventory controlling, order placement, pricing, etc. [30][31][32][33].…”

Implementasi Model Stokastik Pada Permasalahan Optimasi Persediaan Kelapa Pada Tingkat Distributor

“…Metode modifikasi fruit fly algorithm diperkenalkan oleh (Mousavi, Alikar, Niaki, & Bahreininejad, 2015) untuk menyelesaikan permasalahan optimasi alokasi dan inventori. (Rezaeian, Haghayegh, & Mahdavi, 2016) (Rahdar, Wang, & Hu, 2018) dengan memperkenalkan model TriLevel Optimization dan model stokastik. Berikut diberikan model stokastik yang diperkenalkan oleh (Rahdar, Wang, & Hu, 2018).…”

“…(Rezaeian, Haghayegh, & Mahdavi, 2016) (Rahdar, Wang, & Hu, 2018) dengan memperkenalkan model TriLevel Optimization dan model stokastik. Berikut diberikan model stokastik yang diperkenalkan oleh (Rahdar, Wang, & Hu, 2018). Penelitian ini bertujuan untuk mengetahui distribusi peluang dari data permintaan, total biaya persediaan dan persediaan kelapa optimal di tingkat distributor yang berlokasi di kota Palembang selama dua periode pemesanan menggunakan model persediaan stokastik yang diperkenalkan oleh (Rahdar, Wang, & Hu, 2018).…”

“…Berikut diberikan langkah penyelesaian masalah optimasi persediaan kelapa di tingkat distributor. (Rahdar, Wang, & Hu, 2018) dengan .…”

An Approximate Method for Integrated Stochastic Replenishment Planning with Supplier Selection

“…At the same time the optimal solution of a MSSP with few stages is usually a myopic solution of the global problem. Therefore, a compromise can be made between the computation time and solution quality by implementing the decisions in a rolling horizon manner (Rahdar et al, 2018). Second justification is that, with demand information farther in the future the forecast quality is usually less accurate.…”