Fig 1.
The 4PL logistics pattern can be divided into four routes. Route 1 starts from the departure site of the logistics provider to the destination of the logistics provider, with a loaded logistics vehicle. In this study, Route 1 was not considered, because the route and transportation task are predetermined. Route 2 starts from the original logistics destination to the client’s departure site, with an empty logistics vehicle. Route 3 starts from the client’s departure site to the client’s destination; the client’s goods are delivered by the logistics vehicle. Route 4 starts from the client’s destination to the original departure site of the logistics provider, with an empty logistics vehicle. To reduce the empty-loaded rate, the 4PL platform should minimize the distance of routes 2 and 4 by matching appropriate clients to the logistics vehicles under stable constraints.
Table 1.
Variable notations.
Table 2.
Variables enumeration table.
Table 3.
Setting of indices and parameters of one-to-one stable matching.
Fig 2.
One-to-one matching result chart of 500
× 200 scale.
Fig 3.
Histogram of serval index.
Fig 4.
Statistical chart of preference deviation of the logistics providers and clients.
Table 4.
Setting of indices and parameters of many-to-one stable matching.
Fig 5.
Many-to-one matching result chart of 500
× 200 scale.
Fig 6.
Histogram of serval index.
Fig 7.
Statistical chart of preference deviation of the logistics provider and clients.
Table 5.
Original transportation route data of logistics provider.
Table 6.
Transport demand data of client.
Fig 8.
Histogram of serval index.
Fig 9.
Matching result analysis of the one-to-one matching.
Table 7.
Delivery demand data of client’s bulk goods.
Fig 10.
Matching result analysis of the many-to-one matching.