%0 Conference Proceedings
%T Inventory and Commitment Decisions for On-Demand Warehousing System
%+ Department of Industrial Engineering [Seoul]
%A Lee, Junhyeok
%A Park, Junseok
%A Moon, Ilkyeong
%Z Part 8: Modern Analytics and New AI-Based Smart Techniques for Replenishment and Production Planning Under Uncertainty
%< avec comité de lecture
%@ 978-3-030-85873-5
%( IFIP Advances in Information and Communication Technology
%B IFIP International Conference on Advances in Production Management Systems (APMS)
%C Nantes, France
%Y Alexandre Dolgui
%Y Alain Bernard
%Y David Lemoine
%Y Gregor von Cieminski
%Y David Romero
%I Springer International Publishing
%3 Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems
%V AICT-630
%N Part I
%P 455-463
%8 2021-09-05
%D 2021
%R 10.1007/978-3-030-85874-2_48
%K Shared warehouse;Inventory model;On-demand warehousing;Commitment decisions
%Z Computer Science [cs]Conference papers
%X The on-demand warehousing system is a service that makes a connection between e-commerce sellers and warehouse providers who have excess capacity for sharing warehouse spaces. The e-commerce sellers can create a distribution network strategy and manage the varying demands of customers by utilizing this system. In this study, we focused on inventory and commitment decisions that impacted the use of shared warehouses from the standpoint of e-commerce sellers. We proposed a mathematical model, which incorporated inventory and commitment decisions to maximize total profits. A small-scale experiment was conducted, and the result showed that the commitment decisions could affect total profits of e-commerce sellers considerably.
%G English
%Z TC 5
%Z WG 5.7
%2 https://inria.hal.science/hal-04030377v1/document
%2 https://inria.hal.science/hal-04030377v1/file/509923_1_En_48_Chapter.pdf
%L hal-04030377
%U https://inria.hal.science/hal-04030377
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-APMS
%~ IFIP-WG5-7
%~ IFIP-AICT-630