CN118134226A - Freight car capacity allocation method - Google Patents

Freight car capacity allocation method Download PDF

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CN118134226A
CN118134226A CN202410574449.2A CN202410574449A CN118134226A CN 118134226 A CN118134226 A CN 118134226A CN 202410574449 A CN202410574449 A CN 202410574449A CN 118134226 A CN118134226 A CN 118134226A
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goods
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CN118134226B (en
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金志宇
孟健
蒋帅
李越
李强
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Yukuai Chuangling Intelligent Technology Nanjing Co ltd
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Abstract

The invention provides a freight car capacity allocation method, which comprises the following steps: s1, counting the number of all unmatched goods sources and trucks, collecting corresponding coordinate information, and calculating the distance between the goods sources and the trucks; s2, counting the number of trucks needed by each cargo source; s3, judging the supply-demand relationship between the goods source and the truck; s4, when the number of trucks is larger than the demand, all goods sources are required to be pulled away at the lowest cost; and S5, when the supply and the demand of the number of the trucks are not required, the distribution method is that all the trucks are allocated and the goods sources with high benefits are transported preferentially. The invention determines a matching scheme according to the supply and demand relationship of the goods source and the truck. Under the condition of more trucks and fewer trucks, the source with the highest profit is preferentially selected, so that the transportation profit of each truck can be maximized, and the overall transportation efficiency and profit margin are improved; under the condition of more vehicles and less cargoes, the freight car with the lowest transport capacity loss is considered when the freight car is matched with a transport task, so that the waste of energy and time can be reduced, and the transport efficiency is improved.

Description

Freight car capacity allocation method
Technical Field
The invention relates to the technical field of truck transportation, in particular to a truck capacity allocation method.
Background
Freight in cities is one of the key factors in the development of urban economy. Through an effective logistics system, the freight activity can promote circulation of goods and services, meet demands of residents and enterprises, and promote economic growth and prosperity of cities. The good urban logistics can improve the competitiveness of cities, attract investment and business activities, reduce traffic jams, lighten environmental pollution and improve public service efficiency.
In urban freight, trucks play a critical role. The truck has a large cargo carrying capacity and can carry various types and sizes of cargoes. They can freely run on the urban road network and can flexibly meet the goods taking and delivering demands. The flexibility of the truck enables the truck to reach a destination directly, shortens the transportation time of goods, improves the delivery efficiency, and is particularly important in the last mile delivery link. Once the goods reach the urban area, the goods can be quickly delivered to the final receiver by the truck, so that the market supply requirement is met. The goods can be delivered to shops, supermarkets and other retail sites by trucks from production places, warehouses or logistics centers, and the urban commodity supply chain is maintained.
To optimize urban shipment management, the shipping company operates an urban shipment management platform. On the platform, the shipper may issue shipping tasks, while the platform is responsible for assigning tasks to the appropriate trucks. However, how to allocate a large number of trucks on standby to improve the freight efficiency of the trucks, satisfaction of suppliers, and make the company obtain greater profits is a problem.
Currently, there are two main deployment schemes. The first scheme is that the vehicle owner selects the goods to be pulled independently, which is suitable for the situation that the goods in the platform are more and the trucks are less; however, when the sources of goods are reduced, there is a risk of competing between drivers, resulting in wasted capacity and resources of the system as a whole. The second scheme is to match the platform with the freight, and the present scheme generally adopts a nearby principle or orders according to freight cost to arrange the freight sequence; however, the solution cannot uniformly allocate freight resources of the whole platform, and optimal utilization of the resources is difficult to achieve.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides a freight car capacity allocation method.
In order to achieve the above purpose, the invention adopts the following technical scheme: a freight car capacity allocation method, comprising the steps of:
S1, counting the number of all unmatched goods sources and trucks, collecting corresponding coordinate information, and calculating the distance between the goods sources and the trucks;
setting the number of unmatched goods sources as M, wherein M is a positive integer, collecting coordinate information of M goods sources, and recording as ；
Setting the number of unmatched trucks as N, wherein N is a positive integer, collecting coordinate information of N trucks, and recording as；
Calculating the distance between the ith goods source and the jth truckWherein/>，/>The calculation formula is as follows: /(I)。
S2, counting the number of trucks needed by each cargo source;
Counting the number of trucks required by M goods sources respectively, and recording as ；
Calculating the total required truck quantity R of M cargo sources, wherein R is a positive integer, and the calculation formula is as follows:。
s3, judging the supply-demand relationship between the goods source and the truck;
If it is The actual number of trucks is larger than the number of trucks needed by the goods source, the number of trucks is larger than the number of trucks needed by the goods source, and the step S4 is executed;
If it is And step S5 is executed, wherein the actual number of trucks is smaller than the number of trucks needed by the goods source, and the number of trucks is not required.
S4, when the number of trucks is larger than the demand, all goods sources are required to be pulled away at the lowest cost; the distribution method is that the total distance between the matched truck and the cargo source is the shortest.
The method specifically comprises the following substeps:
s41, forming a matrix T by using distance cost factors, namely calculating the distance h between each truck and each cargo source to form the matrix T, wherein ；
Any row in matrix TThe distance between the ith goods source and N trucks respectively;
Starting from the first row of the matrix T, completing matching of a cargo source and a truck by eliminating the matrix array, obtaining a queue Y and a total distance S 1, and putting S 1 into the queue S;
The queue Y is a set of distances between all cargo sources and each matched truck;
The total distance s 1 is the sum of the distances between all the goods sources and each matched truck;
The method specifically comprises the following substeps:
S411, the first row of the matrix T is arranged in sequence Sorting from small to large, selecting the front/>, of the arrayPut the numerical value into the queue Y, correspondingly marked as/>；
S412, selectingDeleting the column where the numerical value is in the matrix T to obtain a new matrixBy matrix/>Replacing the matrix T;
S413, the second row of the matrix T is listed Sorting from small to large, selecting the front of the arrayPut the numerical value into the queue Y, correspondingly marked as/>；
S414, selectingDeleting the column where the numerical value is in the matrix T to obtain a new matrixBy matrix/>Replacing the matrix T;
S415, repeating the imitation steps S411-S414, and so on, sequentially executing the matrix T to the Mth row to finally obtain the matrix Obtain queue/>; Each element in the queue Y, and the subscript of the corresponding element h in the matrix T is the matching scheme of the truck and the cargo source;
S416, calculating a total distance S 1, wherein the calculation formula is as follows: 。
S42, randomly changing the sequence of M rows of the matrix T, and reorganizing Planting new matrixes T, circularly executing steps S411-S416 by each new matrix T to respectively obtain total distances S 2、s3、…、sM!, and putting the total distances S 2、s3、…、sM! into a queue S; finally, a queue/>, with the length of M-。
S43, calculating the minimum value in the queue S, namely the sum of the distances between all trucks and the goods sources at the lowest cost; at this time, each element of the corresponding queue Y corresponds to the index of the corresponding element h in the matrix T, which is the matching scheme of the truck and the cargo source.
S5, when the supply and the demand of the number of the trucks are not required, the distribution method is that all the trucks are allocated and the goods sources with high income are transported preferentially;
The goods source with high income is the goods source with highest acquired cost in the unit distance of truck driving.
The method specifically comprises the following substeps:
s51, forming a profit factor matrix V according to the acquired cost of the unit distance of truck driving;
The method specifically comprises the following substeps:
s511, counting total commissions of each goods source, and calculating transport cost of each truck for transporting the corresponding goods source;
The total commission is recorded as the total transportation cost of each cargo source to the corresponding cargo source ；
By the formulaCalculating the transportation cost of each truck for transporting the corresponding goods source, and recording as；
S512, calculating the total distance required to travel by each truck for transporting each cargo source, thereby obtaining a total distance matrix U;
The method specifically comprises the following substeps:
s5121, counting the transportation distance of each goods source from the starting place to the destination, and marking as ；
S5122, calculating the distance h between each truck and each cargo source to form a matrix T, wherein；
S5123, calculating the total distance required to be travelled by the truck to obtain a total distance matrix U;
I.e. the distance between the truck and the source is added to the transport distance of the source from the origin to the destination, thereby obtaining a total distance matrix 。
S513, calculating the transportation cost obtained by each element unit distance in the total distance matrix U to obtain a profit factor matrix V, whereinCorrespondingly marked as/>；
Any column in matrix VAnd (5) respectively pulling the M goods sources for the jth truck, and obtaining the transportation cost per unit distance.
S52, starting from the first column of the matrix V, completing matching of a cargo source and a truck by eliminating a matrix row, and obtaining a queue Z;
the queue Z is used for conveying matched goods sources for all trucks and collecting fees obtained in unit distance;
The method specifically comprises the following substeps:
s521, the first column of the matrix V Sorting from big to small, and putting the maximum numerical value of the array into a queue Z;
s522, the number of vehicles required by the goods sources corresponding to the maximum value in the row of the matrix V Subtracting 1 to obtain a new matrix；
S5221 if the number of vehicles is requiredDecreasing to 0, indicating that the source has been matched to all trucks, deleting the maximum value from the row in matrix V to obtain a new matrix/>；
S5222 if the number of vehicles is requiredIs not 0 after being subtracted, the goods source is required to be matched/>Vehicle truck, matrix V will not change/>Values of/>Repeating steps S521-S522 until the number of vehicles required by the source/>Step S5221 is performed after the new matrix/>；
S523, matrixReplace matrix V, queue Z put/>The value is correspondingly recorded as/>；
S524, repeating steps S521-S523, sequentially executing the matrix V from the first column to the N column to finally obtain a queueAnd each element in the queue Z, and the subscript of the corresponding element in the matrix V is the matching scheme of the truck and the cargo source.
S53, calculating the total cost W 1 obtained by unit distances of all trucks in the queue Z, and putting W 1 into the queue W;
the calculation formula is as follows: ；
s54, randomly changing the sequence of N columns of the matrix V, and reorganizing Planting new matrixes V, circularly executing steps S51-S53 by each new matrix V, respectively obtaining the total cost W 2、w3、…、wN! obtained by unit distances of all trucks, and putting the total cost W 2、w3、…、wN! into a queue W; finally, a queue W/>, with the length of N-；
S55, calculating the maximum value in the queue W, namely the highest unit distance expense sum; at this time, each element in the corresponding queue Z, and the subscript of the corresponding element in the matrix is the matching scheme of the truck and the cargo source.
Compared with the prior art, the invention has the beneficial effects that: the invention determines a matching scheme according to the supply and demand relationship of the goods source and the truck. Under the condition of more trucks and fewer trucks, the source with the highest profit is preferentially selected, so that the transportation profit of each truck can be maximized, and the overall transportation efficiency and profit margin are improved; under the condition of more vehicles and less cargoes, the freight car with the lowest transport capacity loss is considered when the freight car is matched with a transport task, so that the waste of energy and time can be reduced, and the transport efficiency is improved.
Drawings
FIG. 1 is a flow chart of the embodiment 1 of the present invention;
Detailed Description
For a further understanding of the objects, construction, features, and functions of the invention, reference should be made to the following detailed description of the preferred embodiments.
Example 1:
As shown in fig. 1, a freight capacity allocation method includes the following steps:
S1, counting the number of all unmatched goods sources and trucks, collecting corresponding coordinate information, and calculating the distance between the goods sources and the trucks;
setting the number of unmatched goods sources as M, wherein M is a positive integer, collecting coordinate information of M goods sources, and recording as ；
Setting the number of unmatched trucks as N, wherein N is a positive integer, collecting coordinate information of N trucks, and recording as；
Calculating the distance between the ith goods source and the jth truckWherein/>，/>The calculation formula is as follows: /(I)。
S2, counting the number of trucks needed by each cargo source;
Counting the number of trucks required by M goods sources respectively, and recording as ；
Calculating the total required truck quantity R of M cargo sources, wherein R is a positive integer, and the calculation formula is as follows:。
s3, judging the supply-demand relationship between the goods source and the truck;
If it is The actual number of trucks is larger than the number of trucks needed by the goods source, the number of trucks is larger than the number of trucks needed by the goods source, and the step S4 is executed;
If it is And step S5 is executed, wherein the actual number of trucks is smaller than the number of trucks needed by the goods source, and the number of trucks is not required.
S4, when the number of trucks is larger than the demand, all goods sources are required to be pulled away at the lowest cost; the distribution method is that the total distance between the matched truck and the cargo source is shortest;
The method specifically comprises the following substeps:
s41, forming a matrix T by using distance cost factors, namely calculating the distance h between each truck and each cargo source to form the matrix T, wherein ；
Any row in matrix TThe distance between the ith goods source and N trucks respectively;
Starting from the first row of the matrix T, completing matching of a cargo source and a truck by eliminating the matrix array, obtaining a queue Y and a total distance S 1, and putting S 1 into the queue S;
The queue Y is a set of distances between all cargo sources and each matched truck;
the total distance s 1 is the sum of the distances between all sources and each matched truck.
The method specifically comprises the following substeps:
S411, the first row of the matrix T is arranged in sequence Sorting from small to large, selecting the front/>, of the arrayPut the numerical value into the queue Y, correspondingly marked as/>；
S412, selectingDeleting the column where the numerical value is in the matrix T to obtain a new matrixBy matrix/>Replacing the matrix T;
S413, the second row of the matrix T is listed Sorting from small to large, selecting the front of the arrayPut the numerical value into the queue Y, correspondingly marked as/>；
S414, selectingDeleting the column where the numerical value is in the matrix T to obtain a new matrixBy matrix/>Replacing the matrix T;
in one embodiment of the present invention, Representing that the first source requires two vehicles to be transported and the first row of matrix T is the row/>Middle/>The two minimum values; then handle/>Put into the queue Y, and the queue Y is correspondingly marked as/>; Simultaneously deleting the 1 st column and the 2 nd column of the matrix T to obtain a new matrix/>. At this time, the matching scheme of the trucks and the cargo sources represented by the queue Y is that the first truck clouds the first cargo source and the second truck transports the first cargo source.
S415, repeating the steps, and sequentially executing the matrix T to the M th row to finally obtain the matrixObtain queue/>; Each element in the queue Y, and the subscript of the corresponding element h in the matrix T is the matching scheme of the truck and the cargo source;
S416, calculating a total distance S 1, wherein the calculation formula is as follows: 。
S42, randomly changing the sequence of M rows of the matrix T, and reorganizing Planting new matrixes T, circularly executing steps S411-S416 by each new matrix T to respectively obtain total distances S 2、s3、…、sM!, and putting the total distances S 2、s3、…、sM! into a queue S; finally, a queue/>, with the length of M-；
S43, calculating the minimum value in the queue S, namely the sum of the distances between all trucks and the goods sources at the lowest cost; at this time, each element of the corresponding queue Y corresponds to the index of the corresponding element h in the matrix T, which is the matching scheme of the truck and the cargo source.
S5, when the supply and the demand of the number of the trucks are not required, the distribution method is that all the trucks are allocated and the goods sources with high income are transported preferentially;
the goods source with high income is the goods source with highest cost obtained from the unit distance of truck driving;
The method specifically comprises the following substeps:
s51, forming a profit factor matrix V according to the acquired cost of the unit distance of truck driving;
The method specifically comprises the following substeps:
s511, counting total commissions of each goods source, and calculating transport cost of each truck for transporting the corresponding goods source;
The total commission is recorded as the total transportation cost of each cargo source to the corresponding cargo source ；
By the formulaCalculating the transportation cost of each truck for transporting the corresponding goods source, and recording as；
S512, calculating the total distance required to travel by each truck for transporting each cargo source, thereby obtaining a total distance matrix U;
The method specifically comprises the following substeps:
s5121, counting the transportation distance of each goods source from the starting place to the destination, and marking as ；
S5122, calculating the distance h between each truck and each cargo source to form a matrix T, wherein；
S5123, calculating the total distance required to be travelled by the truck to obtain a total distance matrix U;
I.e. the distance between the truck and the source is added to the transport distance of the source from the origin to the destination, thereby obtaining a total distance matrix 。
S513, calculating the transportation cost obtained by each element unit distance in the total distance matrix U to obtain a profit factor matrix V, whereinCorrespondingly marked as/>；
Any column in matrix VAnd (5) respectively pulling the M goods sources for the jth truck, and obtaining the transportation cost per unit distance.
S52, starting from the first column of the matrix V, completing matching of a cargo source and a truck by eliminating a matrix row, and obtaining a queue Z;
the queue Z is used for conveying matched goods sources for all trucks and collecting fees obtained in unit distance;
The method specifically comprises the following substeps:
s521, the first column of the matrix V Sorting from big to small, and putting the maximum numerical value of the array into a queue Z;
s522, the number of vehicles required by the goods sources corresponding to the maximum value in the row of the matrix V Subtracting 1 to obtain a new matrix；
S5221 if the number of vehicles is requiredDecreasing to 0, indicating that the source has been matched to all trucks, deleting the value in the row matrix V to obtain a new matrix/>；
S5222 if the number of vehicles is requiredIs not 0 after being subtracted, the goods source is required to be matched/>Vehicle truck, matrix V will not change/>Values of/>Repeating steps S521-S522 until the number of vehicles required by the source/>Step S5221 is performed after the new matrix/>。
S523, matrixReplace matrix V, queue Z put/>The value is correspondingly recorded as/>；
S524, repeating steps S521-S523, sequentially executing the matrix V from the first column to the N column to finally obtain a queueAnd each element in the queue Z, and the subscript of the corresponding element in the matrix V is the matching scheme of the truck and the cargo source.
S53, under the matching scheme, calculating the total cost W 1 obtained by unit distances of all trucks, and putting W 1 into a queue W;
the calculation formula is as follows:
s54, randomly changing the sequence of N columns of the matrix V, and reorganizing Planting new matrixes V, circularly executing steps S51-S53 by each new matrix V, respectively obtaining the total cost W 2、w3、…、wN! obtained by unit distances of all trucks, and putting the total cost W 2、w3、…、wN! into a queue W; finally, a queue W/>, with the length of N-；
S55, calculating the maximum value in the queue W, namely the highest unit distance expense sum; at this time, each element in the corresponding queue Z, and the subscript of the corresponding element in the matrix is the matching scheme of the truck and the cargo source.
The invention has been described with respect to the above-described embodiments, however, the above-described embodiments are merely examples of practicing the invention. It should be noted that the disclosed embodiments do not limit the scope of the invention. On the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Claims (6)

1. A freight car capacity allocation method is characterized in that: the method comprises the following steps:
S1, counting the number of all unmatched goods sources and trucks, collecting corresponding coordinate information, and calculating the distance between the goods sources and the trucks;
setting the number of unmatched goods sources as M, wherein M is a positive integer, collecting coordinate information of M goods sources, and recording as ；
Setting the number of unmatched trucks as N, wherein N is a positive integer, collecting coordinate information of N trucks, and recording as；
Calculating the distance between the ith goods source and the jth truckWherein/>，/>The calculation formula is as follows:
；
S2, counting the number of trucks needed by each cargo source;
Counting the number of trucks required by M goods sources respectively, and recording as ；
Calculating the total required truck quantity R of M cargo sources, wherein R is a positive integer, and the calculation formula is as follows:；
s3, judging the supply-demand relationship between the goods source and the truck;
If it is The actual number of trucks is larger than the number of trucks needed by the goods source, the number of trucks is larger than the number of trucks needed by the goods source, and the step S4 is executed;
If it is The actual number of trucks is smaller than the number of trucks needed by the goods source, the supply and the demand of the number of trucks are insufficient, and the step S5 is executed;
S4, when the number of trucks is larger than the demand, all goods sources are required to be pulled away at the lowest cost; the distribution method is that the total distance between the matched truck and the cargo source is shortest;
S5, when the supply and the demand of the number of the trucks are not required, the distribution method is that all the trucks are allocated and the goods sources with high income are transported preferentially;
the goods source with high profit is the goods source 1 with highest cost obtained from the unit distance of truck driving.
2. The trucking capacity allocation method as in claim 1, wherein: the step S4 specifically includes the following substeps:
s41, forming a matrix T by using distance cost factors, namely calculating the distance h between each truck and each cargo source to form the matrix T, wherein ；
Any row in matrix TThe distance between the ith goods source and N trucks respectively;
Starting from the first row of the matrix T, completing matching of a cargo source and a truck by eliminating the matrix array, obtaining a queue Y and a total distance S 1, and putting S 1 into the queue S;
The queue Y is a set of distances between all cargo sources and each matched truck;
The total distance s 1 is the sum of the distances between all the goods sources and each matched truck;
S42, randomly changing the sequence of M rows of the matrix T, and reorganizing Planting new matrixes T, wherein each new matrix T adopts a method of S41 to respectively obtain total distances S 2、s3、…、sM!, and putting the total distances S 2、s3、…、sM! into a queue S; finally, a queue with the length of M-；
S43, calculating the minimum value in the queue S, namely the sum of the distances between all trucks and the goods sources at the lowest cost; at this time, each element of the corresponding queue Y corresponds to the index of the corresponding element h in the matrix T, which is the matching scheme of the truck and the cargo source.
3. The trucking capacity allocation method as in claim 2, wherein: step S41 specifically includes the following substeps:
S411, the first row of the matrix T is arranged in sequence Sorting from small to large, selecting the front/>, of the arrayPut the numerical value into the queue Y, correspondingly marked as/>；
S412, selectingDeleting the column where the numerical value is in the matrix T to obtain a new matrixBy matrix/>Replacing the matrix T;
S413, the second row of the matrix T is listed Sorting from small to large, selecting the front/>, of the arrayPut the numerical value into the queue Y, correspondingly marked as/>；
S414, selectingDeleting the column where the numerical value is in the matrix T to obtain a new matrixBy matrix/>Replacing the matrix T;
S415, repeating the imitation steps S411-S414, and so on, sequentially executing the matrix T to the Mth row to finally obtain the matrix Obtain queue/>; Each element in the queue Y, and the subscript of the corresponding element h in the matrix T is the matching scheme of the truck and the cargo source;
S416, calculating a total distance S 1, wherein the calculation formula is as follows: 。
4. the trucking capacity allocation method as in claim 1, wherein: the step S5 specifically includes the following substeps:
s51, forming a profit factor matrix V according to the acquired cost of the unit distance of truck driving;
s52, starting from the first column of the matrix V, completing matching of a cargo source and a truck by eliminating a matrix row, and obtaining a queue Z;
the queue Z is used for conveying matched goods sources for all trucks and collecting fees obtained in unit distance;
S53, calculating the total cost W 1 obtained by unit distances of all trucks in the queue Z, and putting W 1 into the queue W;
the calculation formula is as follows: ；
s54, randomly changing the sequence of N columns of the matrix V, and reorganizing Planting new matrixes V, circularly executing steps S51-S53 by each new matrix V, respectively obtaining the total cost W 2、w3、…、wN! obtained by unit distances of all trucks, and putting the total cost W 2、w3、…、wN! into a queue W; finally, a queue W/>, with the length of N-；
S55, calculating the maximum value in the queue W, namely the highest unit distance expense sum; at this time, each element in the corresponding queue Z, and the subscript of the corresponding element in the matrix is the matching scheme of the truck and the cargo source.
5. The trucking capacity allocation method as in claim 4, wherein: step S51 specifically includes the following sub-steps:
s511, counting total commissions of each goods source, and calculating transport cost of each truck for transporting the corresponding goods source;
The total commission is recorded as the total transportation cost of each cargo source to the corresponding cargo source ；
By the formulaCalculating the transportation cost of each truck for transporting the corresponding goods source, and recording as；
S512, calculating the total distance required to travel by each truck for transporting each cargo source, thereby obtaining a total distance matrix U;
The method specifically comprises the following substeps:
s5121, counting the transportation distance of each goods source from the starting place to the destination, and marking as ；
S5122, calculating the distance h between each truck and each cargo source to form a matrix T, wherein；
S5123, calculating the total distance required to be travelled by the truck to obtain a total distance matrix U;
I.e. the distance between the truck and the source is added to the transport distance of the source from the origin to the destination, thereby obtaining a total distance matrix ；
S513, calculating the transportation cost obtained by each element unit distance in the total distance matrix U to obtain a profit factor matrix V, whereinCorrespondingly marked as/>；
Any column in matrix VAnd (5) respectively pulling the M goods sources for the jth truck, and obtaining the transportation cost per unit distance.
6. The trucking capacity allocation method as in claim 5, wherein: step S52 specifically includes the following sub-steps:
s521, the first column of the matrix V Sorting from big to small, and putting the maximum numerical value of the array into a queue Z;
s522, the number of vehicles required by the goods sources corresponding to the maximum value in the row of the matrix V Subtracting 1 to obtain a new matrix；
S5221 if the number of vehicles is requiredDecreasing to 0, indicating that the goods source is matched with all trucks, deleting the maximum numerical value in the row in the matrix V to obtain a new matrix/>；
S5222 if the number of vehicles is requiredIs not 0 after being subtracted, the goods source is required to be matched/>Vehicle truck, matrix V will not change/>Values of/>Repeating steps S521-S522 until the number of vehicles required by the source/>Step S5221 is performed after the new matrix/>；
S523, matrixReplace matrix V, queue Z put/>The value is correspondingly recorded as/>；
S524, repeating steps S521-S523, sequentially executing the matrix V from the first column to the N column to finally obtain a queueAnd each element in the queue Z, and the subscript of the corresponding element in the matrix V is the matching scheme of the truck and the cargo source.
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Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020087371A1 (en) * 2000-12-28 2002-07-04 Abendroth John C. Method and system for E-commerce freight management
US20030055693A1 (en) * 2001-03-23 2003-03-20 Restaurant Services, Inc. System, method and computer program product for an transportation equipment supply chain management framework
US20030061084A1 (en) * 2001-03-23 2003-03-27 Restaurant Services, Inc. System, method and computer program product for freight management in a supply chain framework
US20050021346A1 (en) * 2000-08-13 2005-01-27 Nadan Joseph S. Method and system for creating marketplace visibility and administering freight shipments using fuzzy commodity transportation instruments
CN102542395A (en) * 2010-12-31 2012-07-04 北京师范大学 Emergency material dispatching system and calculating method
CN103106571A (en) * 2012-12-28 2013-05-15 何剑 Truck transporting supply and demand matching method based on mobile phone position service
CN108133345A (en) * 2017-12-27 2018-06-08 北京中交兴路车联网科技有限公司 A kind of method and system that off-duty train is judged based on lorry magnanimity track data
CN109214608A (en) * 2018-11-14 2019-01-15 成都英孚克斯科技有限公司 A kind of vehicle scheduling optimization method
CN109740979A (en) * 2018-12-13 2019-05-10 西安微猴电子商务有限责任公司 A kind of staple commodities transportation resources based on cloud, apparatus and system
US20210155221A1 (en) * 2020-01-09 2021-05-27 Jonathan Gottehrer Systems and methods for assigning vehicles to transportation requests
CN112862184A (en) * 2021-02-04 2021-05-28 江苏满运物流信息有限公司 Transportation information prediction method and device, electronic equipment and readable storage medium
US20210304130A1 (en) * 2020-03-27 2021-09-30 Sony Corporation Configuring a system for delivery of goods by unmanned aerial vehicles
CN115829170A (en) * 2023-02-17 2023-03-21 鱼快创领智能科技(南京)有限公司 Driving scheme optimization method, system and storage medium

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050021346A1 (en) * 2000-08-13 2005-01-27 Nadan Joseph S. Method and system for creating marketplace visibility and administering freight shipments using fuzzy commodity transportation instruments
US20020087371A1 (en) * 2000-12-28 2002-07-04 Abendroth John C. Method and system for E-commerce freight management
US20030055693A1 (en) * 2001-03-23 2003-03-20 Restaurant Services, Inc. System, method and computer program product for an transportation equipment supply chain management framework
US20030061084A1 (en) * 2001-03-23 2003-03-27 Restaurant Services, Inc. System, method and computer program product for freight management in a supply chain framework
CN102542395A (en) * 2010-12-31 2012-07-04 北京师范大学 Emergency material dispatching system and calculating method
CN103106571A (en) * 2012-12-28 2013-05-15 何剑 Truck transporting supply and demand matching method based on mobile phone position service
CN108133345A (en) * 2017-12-27 2018-06-08 北京中交兴路车联网科技有限公司 A kind of method and system that off-duty train is judged based on lorry magnanimity track data
CN109214608A (en) * 2018-11-14 2019-01-15 成都英孚克斯科技有限公司 A kind of vehicle scheduling optimization method
CN109740979A (en) * 2018-12-13 2019-05-10 西安微猴电子商务有限责任公司 A kind of staple commodities transportation resources based on cloud, apparatus and system
US20210155221A1 (en) * 2020-01-09 2021-05-27 Jonathan Gottehrer Systems and methods for assigning vehicles to transportation requests
US20210304130A1 (en) * 2020-03-27 2021-09-30 Sony Corporation Configuring a system for delivery of goods by unmanned aerial vehicles
CN112862184A (en) * 2021-02-04 2021-05-28 江苏满运物流信息有限公司 Transportation information prediction method and device, electronic equipment and readable storage medium
CN115829170A (en) * 2023-02-17 2023-03-21 鱼快创领智能科技(南京)有限公司 Driving scheme optimization method, system and storage medium

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
史玉敏;赵庆祯;赵培忻;: "物流配送中双向车辆路径问题(VRP)的研究", 微计算机信息, no. 33, 25 November 2007 (2007-11-25), pages 11 - 13 *

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