Optimizing winner determination for sustainability and timeliness in fresh agricultural product logistics service procurement auctions: insights from a fourth-party logistics perspective
With the rapid development of e-commerce in the field of fresh agricultural products and the growing prominence of environmental issues, delivery timeliness and low-carbon concepts are critical considerations in the development of cold chain logistics. From the perspective of fourth-party logistics...
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| Hauptverfasser: | , , , , , |
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| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
Frontiers Media S.A.
2025-07-01
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| Schriftenreihe: | Frontiers in Sustainable Food Systems |
| Schlagworte: | |
| Online-Zugang: | https://www.frontiersin.org/articles/10.3389/fsufs.2025.1585053/full |
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| Zusammenfassung: | With the rapid development of e-commerce in the field of fresh agricultural products and the growing prominence of environmental issues, delivery timeliness and low-carbon concepts are critical considerations in the development of cold chain logistics. From the perspective of fourth-party logistics (4PL), this paper studies the logistics services procurement auction problem of fresh agricultural product logistics considering timeliness and sustainability under demand uncertainty, aiming to achieve efficient and sustainable development of fresh agricultural product transportation through collaborative cooperation among third-party logistics (3PL). To address this problem, a two-stage stochastic model for winner determination with timeliness and sustainability under uncertain demand in fresh agricultural products logistics service procurement auction. The first stage determines the winning 3PLs, while the second stage determines the transportation volume of the 3PLs based on the decision results in the first stage. Through the sample average approximation (SAA) technology, the proposed two-stage stochastic programming is approximated as a mixed-integer linear programming model. Since winner determination problem is NP-hard, the increasing number of decision variables and demand scenarios poses challenges to the problem. Based on Latin hypercube sampling approach, this paper reconstructs the traditional SAA algorithm framework, and combines the dual decomposition and Lagrangian relaxation algorithm to develop a sampling-based approximate algorithm to solve the proposed model. The effectiveness of the proposed model and algorithm is demonstrated through a real case from a logistics enterprise in Shenzhen, China, revealing the complex coupling relationship between carbon caps, time window sizes, and decision outcomes, thereby providing insights for 4PL management practices in fresh agricultural product transportation. |
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| ISSN: | 2571-581X |