Journal
MATHEMATICS
Volume 10, Issue 16, Pages -Publisher
MDPI
DOI: 10.3390/math10162942
Keywords
auto parts supply chain; sustainable logistics; robust optimization; location-inventory-routing optimization; multi-period demand
Categories
Funding
- National Natural Science Foundation of China [61873109]
- Natural Science Foundation of Jilin Province [20210101055JC]
- FAW Technology Innovation Project [KF2020-20006]
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This paper proposes a unified framework that addresses the transportation capacity issue in auto parts supply logistics by considering the location-inventory-routing problem. By establishing distribution centers and optimizing the location, inventory, and routing decisions, it is possible to reduce the total system cost and carbon emissions.
A great loss of transportation capacity has been caused in auto parts supply logistics due to the independent transportation from auto parts suppliers (APSs) to the automobile production line (APL). It is believed that establishing distribution centers (DCs) for centralized collection and unified distribution is one effective way to address this problem. This paper proposes a unified framework simultaneously considering the location-inventory-routing problem (LIRP) in auto parts supply logistics. Integrating the idea of sustainable development, a multi-objective MIP model is developed to determine the location and inventory capacity of DCs and routing decisions to minimize the total system cost and carbon emissions while concerning multi-period production demand. In addition, a robust optimization model is developed further in the context of uncertain demand. Numerical experiments and sensitivity analyses are conducted to verify the effectiveness of our proposed deterministic and robust models. The results show that synergistically optimizing the location and capacity of DCs and routing decisions are beneficial in reducing total system cost and carbon emissions. The analysis can provide guidelines to decision-makers for the effective management of auto parts supply logistics.
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