An Inventory Model with Recovery and Periodic Delivery that Considers Carbon Emission Cost
- DOI
- 10.2991/978-94-6463-014-5_15How to use a DOI?
- Keywords
- Inventory model; recovery; periodic delivery; carbon emission cost
- Abstract
This paper proposes an integrated inventory model that considers three types of inventories: used items, service items, and raw materials. Used items are collected from the market and are restored to a serviceable condition to satisfy demand. If the quantity of the restored items is lacking, then the remaining demand is satisfied by converting raw materials into service items through a production run. Demand is satisfied by shipping periodically in batches of equal size. The warehousing of items incurs a carbon emission cost in addition to the traditional holding costs. Additionally, the transportation of items to the client incurs a carbon emission cost as well. The objective of the model is to provide insights to help determine both the frequency and the size of the batch shipments to minimize the joint total inventory cost and carbon emission cost. This paper also proposes a numerical solution procedure and provides a numerical example to illustrate the model. A numerical sensitivity analysis is performed to derive insights that are potentially beneficial to policy makers.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Ivan Yeo PY - 2022 DA - 2022/12/12 TI - An Inventory Model with Recovery and Periodic Delivery that Considers Carbon Emission Cost BT - Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022) PB - Atlantis Press SP - 150 EP - 162 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-014-5_15 DO - 10.2991/978-94-6463-014-5_15 ID - Yeo2022 ER -