Unlock instant, AI-driven research and patent intelligence for your innovation.

A collaborative vehicle routing optimization method based on shared carrier and shared warehouse

A vehicle route and optimization method technology, applied in the field of logistics, can solve problems such as single goal, inability to fully reflect logistics factors, and neglect of transportation schemes

Active Publication Date: 2021-11-30
ZHEJIANG UNIV OF FINANCE & ECONOMICS
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the above model based on carrier collaboration only considers unilateral supply-side collaboration, while ignoring the bilateral collaboration between supply and demand sides, which may lead to the neglect of potentially more optimal transportation solutions
In addition, most of these collaborative vehicle routing literatures take cost or time as the optimization goal, and the goal is relatively single, which cannot fully reflect logistics factors

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A collaborative vehicle routing optimization method based on shared carrier and shared warehouse
  • A collaborative vehicle routing optimization method based on shared carrier and shared warehouse
  • A collaborative vehicle routing optimization method based on shared carrier and shared warehouse

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0153] As an example with two carriers and four warehouses, Figure 4 (a) A transport scheme solution for this example is given. Figure 4 (b) The transportation scheme solution based on matrix representation is given. like Figure 4 As shown in (b), the first row in the carrier coordination matrix shows that the goods delivered by carrier A to warehouse 1 are delivered by carrier A itself, and the goods delivered by carrier A to warehouse 2 and warehouse 4 are delivered by carrier B , warehouse 3 has no cargo demand for carrier A. Likewise, the second row in the carrier coordination matrix represents the shipment by carrier B.

[0154] The first row in the warehouse coordination matrix indicates that warehouse 1 and warehouse 2’s cargo demand for carrier A is delivered to warehouse 2, warehouse 4’s cargo demand for carrier A is delivered to warehouse 3, and warehouse 3 has no cargo for carrier need. Similarly, the second row in the warehouse coordination matrix represent...

Embodiment 2

[0174] like Figure 5 As shown, the solution of two carriers and six warehouses is taken as an example. First, split a carrier vector into two vectors of zeros and non-zeros, keeping the relative positions of these elements unchanged. This splitting guarantees that the position of the zeros is fixed (see splitting stages). Then, a reallocation operation is taken on the non-zero vector and a new non-zero vector is produced (see reallocation phase). Finally, the new non-zero and zero vectors are combined into a complete vector according to their relative positions (see combine phase). Perform the reallocation sub-operation on another carrier in a similar manner, and the solution after the reallocation operation is obtained after completion.

[0175] Although the exchange sub-operation and reallocation sub-operation included in the vibration operation can generate new solutions, the solution space is not large enough because the elements that make up each carrier, warehouse, o...

Embodiment 3

[0212] Select two groups of experimental cases. The first group contains 12 experimental cases, numbered #1001 to #1012. All warehouses in this group of cases are randomly distributed within 100 square meters. The second group also contains 12 experimental cases, numbered from #2001 to #2012, and the warehouses in this group of cases are generated by clustering. The number of clusters in the second group of cases is set to 3 or 5, and within each class, the distance between any two warehouses is less than 15.

[0213] In two sets of cases, the number of warehouses is set to be 10, 15, 20, 25, 30 or 100; the vehicle loading capacity is 100, 200, 1000 or 2000; and the warehouse storage capacity is 200, 300, 2000 or 3000. Each case contains two carriers. Compared with the traditional shared customer collaborative vehicle routing model SCC-VRP model, the CVRP-SCD model of this embodiment adds some new objectives, such as transit time, service quality and service reliability, ther...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a collaborative vehicle route optimization method based on a shared carrier and a shared warehouse, comprising: establishing a collaborative vehicle route optimization model based on a shared carrier and a shared warehouse; initializing to obtain a current solution, and using a block code to represent the current solution; Vibration operation is performed on the current solution to obtain a neighborhood set containing multiple neighborhood solutions; mutation operations are performed on each neighborhood solution to update the neighborhood set; local search operations are performed on the updated neighborhood set to obtain the global optimal solution; If the function value of the global optimal solution is greater than the function value of the current solution, the global optimal solution will be taken as the current solution; otherwise, the current solution will remain unchanged; judge whether the preset termination condition is satisfied, and if the termination condition is satisfied, the latest output The current solution, that is, the optimal transportation plan; otherwise, continue to iterate. The invention considers the bilateral logistics cooperation between the supply side and the demand side, and combines multi-objective analysis to obtain a more comprehensive and optimal transportation scheme.

Description

technical field [0001] The application belongs to the technical field of logistics, and in particular relates to a collaborative vehicle route optimization method based on shared carriers and shared warehouses. Background technique [0002] In recent years, with the increasing awareness of sustainable development, green supply chain has received more and more attention. As an important part of the green supply chain, the transportation industry should strive to realize the sustainable development of logistics and transportation in order to improve transportation efficiency. In general, carriers provide delivery services independently, resulting in high transportation costs, pollution, vehicle space occupation, and high traffic volumes. Although some efficient optimization algorithms and data mining methods have been used to solve this problem, due to the limitations of the model, the logistics efficiency has not been effectively improved. Therefore, researchers are increas...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/08
CPCG06Q10/047G06Q10/08355Y02T10/40
Inventor 张帅蔡怡帅张文宇陈子旋
Owner ZHEJIANG UNIV OF FINANCE & ECONOMICS