| Issue |
E3S Web of Conf.
Volume 465, 2023
8th International Conference on Industrial, Mechanical, Electrical and Chemical Engineering (ICIMECE 2023)
|
|
|---|---|---|
| Article Number | 02013 | |
| Number of page(s) | 7 | |
| Section | Symposium on Electrical, Information Technology, and Industrial Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202346502013 | |
| Published online | 18 December 2023 | |
A Location-Routing-Inventory (LRI) Model in Cold Chain Logistic Considering Carbon Emissions
1 Department of Industrial Engineering Universitas Sebelas Maret Surakarta, Indonesia
2 Department of Industrial Engineering Universitas Sebelas Maret Surakarta, Indonesia
3 Department of Industrial Engineering Universitas Sebelas Maret Surakarta, Indonesia
Location-Routing-Inventory (LRI) model is used in logistic chain to select the location of facilities (distribution center, warehouse, or store), the transportation routes between facilities, and the allocation of inventory stored in each facility. This paper proposes developing the LRI model by considering carbon emissions through carbon cap & trade policy, carbon cap policy, and carbon tax policy. Cold chain logistics is a type of logistics chains that keeps perishable products in cold temperatures and produces higher carbon emissions than conventional logistics chain. The development of the LRI model in this paper aims not only to optimize the cost of selecting facility locations, transportation routes, and inventory amount, but also includes optimizing the cost of purchasing raw materials from suppliers under the implementation of carbon emission policies in cold chain logistic. The optimal solution is carried out using LINGO 18.0 and shows that this model can optimize the costs in cold chain logistics by considering carbon emission policies. The results show that the carbon cap policy is the most profitable policy for the company because it produces the lowest total cost compared to other carbon emission policies.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.