CN107798439A - A kind of method for examining goods' transportation routing optimum results - Google Patents
A kind of method for examining goods' transportation routing optimum results Download PDFInfo
- Publication number
- CN107798439A CN107798439A CN201711183257.5A CN201711183257A CN107798439A CN 107798439 A CN107798439 A CN 107798439A CN 201711183257 A CN201711183257 A CN 201711183257A CN 107798439 A CN107798439 A CN 107798439A
- Authority
- CN
- China
- Prior art keywords
- time
- event
- optimum results
- probability
- section
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
- G06Q10/0835—Relationships between shipper or supplier and carriers
- G06Q10/08355—Routing methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
- G06Q10/0838—Historical data
Abstract
The invention discloses a kind of method for examining goods' transportation routing optimum results, including shipment events data acquisition, shipment events are simulated, adjust transportation route, evaluation optimum results four part；The present invention can rapidly, batch simulation actual shipment event, significantly reduce desk checking cost；The present invention can prejudge shipment events in advance, and provide dispatching circuit and order after adjustment, drastically increase the punctuality rate in actual dispatching, save transport power cost；The present invention can also efficiently avoid according to hundreds thousand of in system true lorry trajectory calculation shipment events probability and manually gather, record mistake that may be present so that modeling event and actual similarity are high, ensured optimum results can degree of implementation accuracy.
Description
Technical field
The present invention relates to logistics transportation technical field, specially a kind of method for examining goods' transportation routing optimum results.
Background technology
One good transportation route optimum results can substantially reduce cost, improve operating efficiency, improve customer satisfaction.
And in real process, because actual road conditions, parking stall is not found, customer is temporarily busy, and the laytime extends, and misses Gu
The reasons such as objective time window, often vehicle can not be according to the path and order dispatching arranged properly, and that thus brings detours, can not be punctual
The problem of being sent to greatly wastes time and transport power cost.
There is presently no the special confirmation technology for examining goods' transportation routing optimum results.It is existing to examine mainly
Rely on artificial means：Driver is actual defeated with shipping according to optimum results.This method of inspection is feasible.But defect be driver without
The all situations that method simulation is likely to occur, and cost is higher.
The content of the invention
It is an object of the invention to provide a kind of method for examining goods' transportation routing optimum results, to solve above-mentioned background
The problem of being proposed in technology.
To achieve the above object, the present invention provides following technical scheme：A kind of inspection goods' transportation routing optimum results
Method, including shipment events data acquisition, simulation shipment events, adjustment transportation route, evaluation optimum results four part, including with
Lower step：
A, by hundreds thousand of lorry wheelpaths of Correspondent world DSP lane database, with history vehicle transport event
Match somebody with somebody, history vehicle transport event includes section congestion, the adjustment of order time window, delivery service time-out, obtains every in delivery process
Secondary dispatching triggering shipment events probability, generates the probability of happening matrix being grouped on a time period；
B, the probability factor of event is produced, for each circuit in optimum results, according to the transit time of circuit, road
Section, customer, simulate the event that may occur in this transportation route；The event that may occur wherein in transportation route includes：Road
Section congestion, Gu Kequ, the adjustment of delivery period window, the adjustment of delivery service time；
C, when modeling event triggers, wherein trigger event includes time, section, time-consuming change, according to vehicle in way shape
State, congested link is set to entry region, evades congested link, using new time window and service time, call existing road
Footpath optimized algorithm, vehicle delivery order and circuit are planned again；
If the order and circuit after D, adjusting remain to the time window demand that meets customer, assert result be it is healthy and strong and
It is enforceable, pass through inspection；If can not meet customer demand, it is risky, not verified, need to assert optimum results
Route, adjustment quantity on order or time are recalculated, untill new optimum results are by inspection.
Preferably, in the step A probability of happening matrix include it is as follows：
A, congestion event in section refers to which period of the vehicle on the day of, which section, congestion duration.Long-press is gathered around during congestion
Stifled time length packet；
B, the adjustment of order time window refers to which period of the customer on the day of, and original time window is adjusted into the new time
Window；Temporally length is grouped respectively for earliest distribution time and the adjustment of distribution time the latest；
C, delivery service time-out refers to which period of the customer on the day of, and the time ratio that unloading is decorated in dispatching is estimated time-consuming
Add how many, time-out time is grouped by length；
D, shipment events probability is in certain historical time, each period on the day of, shipment events occurs
Number and same period in historical track, same section, the ratio of same customer's trace bar number.
Preferably, in the step B, long-press probability obtains from event probability matrix during the congestion of section；Delivery period adjusts
When the congestion of long-press section when long-press probability from event probability matrix obtain；Long-press is general during the congestion of long-press section when service time increases
Rate obtains from event probability matrix.
Preferably, in the step C, vehicle delivery order and circuit are planned again：Entry region is set, using it is new when
Between window and service time, be existing route optimized algorithm part input parameter, this algorithm can provide original path optimization
As a result, the dynamic path optimization adjustment on way while is also supported.
Compared with prior art, the beneficial effects of the invention are as follows：The present invention can rapidly, batch simulation actual shipment
Event, significantly reduce desk checking cost；The present invention can prejudge shipment events in advance, and provide and match somebody with somebody line sending after adjustment
Road and order, the punctuality rate in actual dispatching is drastically increased, save transport power cost；The present invention can also be according in system
Hundreds thousand of true lorry trajectory calculation shipment events probability, efficiently avoid and manually gather, record mistake that may be present,
So that modeling event and actual similarity are high, ensured optimum results can degree of implementation accuracy.
Embodiment
The technical scheme in the embodiment of the present invention is clearly and completely described below, it is clear that described embodiment
Only part of the embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, the common skill in this area
The every other embodiment that art personnel are obtained under the premise of creative work is not made, belong to the model that the present invention protects
Enclose.
The present invention provides following technical scheme：A kind of method for examining goods' transportation routing optimum results, including transport thing
Part data acquisition, shipment events are simulated, adjust transportation route, evaluation optimum results four part, comprise the following steps：
A, by hundreds thousand of lorry wheelpaths of Correspondent world DSP lane database, with history vehicle transport event
Match somebody with somebody, history vehicle transport event includes section congestion, the adjustment of order time window, delivery service time-out, obtains every in delivery process
Secondary dispatching triggering shipment events probability, generates the probability of happening matrix being grouped on a time period；
B, the probability factor of event is produced, for each circuit in optimum results, according to the transit time of circuit, road
Section, customer, simulate the event that may occur in this transportation route；The event that may occur wherein in transportation route includes：Road
Section congestion, Gu Kequ, the adjustment of delivery period window, the adjustment of delivery service time；
C, when modeling event triggers, wherein trigger event includes time, section, time-consuming change, according to vehicle in way shape
State, congested link is set to entry region, evades congested link, using new time window and service time, call existing road
Footpath optimized algorithm, vehicle delivery order and circuit are planned again；
If the order and circuit after D, adjusting remain to the time window demand that meets customer, assert result be it is healthy and strong and
It is enforceable, pass through inspection；If can not meet customer demand, it is risky, not verified, need to assert optimum results
Route, adjustment quantity on order or time are recalculated, untill new optimum results are by inspection.Same circuit will be through
Excessive wheel modeling event, ratio up to standard can just pass through inspection after reaching setting value；Only all circuits are all by examining, whole road
Footpath optimum results can just be implemented.
In the present invention, probability of happening matrix includes as follows in step A：
A, congestion event in section refers to which period of the vehicle on the day of, which section, congestion duration.Long-press is gathered around during congestion
Stifled time length packet；
B, the adjustment of order time window refers to which period of the customer on the day of, and original time window is adjusted into the new time
Window；Temporally length is grouped respectively for earliest distribution time and the adjustment of distribution time the latest；
C, delivery service time-out refers to which period of the customer on the day of, and the time ratio that unloading is decorated in dispatching is estimated time-consuming
Add how many, time-out time is grouped by length；
D, shipment events probability is in certain historical time, each period on the day of, shipment events occurs
Number and same period in historical track, same section, the ratio of same customer's trace bar number.
In the present invention, in step B, long-press probability obtains from event probability matrix during the congestion of section；When delivery period adjusts
Long-press probability obtains from event probability matrix during the congestion of long-press section；Long-press probability during the congestion of long-press section when service time increases
Obtained from event probability matrix.
In the present invention, in step C, vehicle delivery order and circuit are planned again：Entry region is set, using the new time
Window and service time, are the part input parameters of existing route optimized algorithm, and this algorithm can provide original path optimization's knot
Fruit, while also support the dynamic path optimization adjustment on way.
The shipment events period can be grouped, every 10 minutes points of congestion duration by the present invention in practice by half an hour
One group, every 10 minutes points one group of dispatching time-out, the probability of happening factor is preferably every circuit between 1.2-1.5 times of actual probabilities
By 10 wheel modeling events, compliance rate>=90% is thought circuit by examining, in the case where meeting that the degree of accuracy occurs for event
Lifting obtains the efficiency of assay.
The present invention can rapidly, batch simulation actual shipment event, significantly reduce desk checking cost；This hair
It is bright to prejudge shipment events in advance, and dispatching circuit and order after adjustment are provided, drastically increase in actual dispatching
Punctuality rate, save transport power cost；The present invention can also be according to hundreds thousand of in system true lorry trajectory calculation shipment events
Probability, it efficiently avoid and manually gather, record mistake that may be present so that modeling event is high with actual similarity, ensures
Optimum results can degree of implementation accuracy.
Although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of changes, modification can be carried out to these embodiments, replace without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (4)
1. a kind of method for examining goods' transportation routing optimum results, including shipment events data acquisition, simulate shipment events, adjust
Whole transportation route, evaluation optimum results four part, it is characterised in that：Comprise the following steps：
A, by hundreds thousand of lorry wheelpaths of Correspondent world DSP lane database, with history vehicle transport event matches, go through
History vehicle transport event includes section congestion, the adjustment of order time window, delivery service time-out, obtains and is dispensed every time in delivery process
Shipment events probability is triggered, generates the probability of happening matrix being grouped on a time period；
B, the probability factor of event is produced, for each circuit in optimum results, according to the transit time of circuit, section,
Customer, simulate the event that may occur in this transportation route；The event that may occur wherein in transportation route includes：Gather around in section
It is stifled, Gu Kequ, the adjustment of delivery period window, the adjustment of delivery service time；
C, when modeling event triggers, wherein trigger event includes time, section, time-consuming change, according to vehicle in way state, general
Congested link is set to entry region, evades congested link, using new time window and service time, calls existing path optimization
Algorithm, vehicle delivery order and circuit are planned again；
If the order and circuit after D, adjusting remain to the time window demand for meeting customer, identification result is healthy and strong and can be real
Apply, pass through inspection；If customer demand can not be met, assert optimum results be it is risky, it is not verified, it is necessary to weight
It is new to calculate route, adjustment quantity on order or time, untill new optimum results are by inspection.
A kind of 2. method for examining goods' transportation routing optimum results according to claim 1, it is characterised in that：The step
Probability of happening matrix includes as follows in rapid A：
A, congestion event in section refers to which period of the vehicle on the day of, which section, congestion duration.During congestion during long-press congestion
Between length be grouped；
B, the adjustment of order time window refers to which period of the customer on the day of, and original time window is adjusted into new time window；Most
Temporally length is grouped respectively for the adjustment of early distribution time and the latest distribution time；
C, delivery service time-out refers to which period of the customer on the day of, and the estimated time-consuming increase of time ratio of unloading is decorated in dispatching
How many, time-out time is by length packet；
D, shipment events probability is each period on the day of in certain historical time, and the number of shipment events occurs
With same period in historical track, same section, the ratio of same customer's trace bar number.
A kind of 3. method for examining goods' transportation routing optimum results according to claim 1, it is characterised in that：The step
In rapid B, long-press probability obtains from event probability matrix during the congestion of section；Long-press is general during the congestion of long-press section when delivery period adjusts
Rate obtains from event probability matrix；Long-press probability obtains from event probability matrix during the congestion of long-press section when service time increases.
A kind of 4. method for examining goods' transportation routing optimum results according to claim 1, it is characterised in that：The step
In rapid C, vehicle delivery order and circuit are planned again：Entry region is set, is existing using new time window and service time
The part input parameter of path optimization's algorithm, this algorithm can provide original path optimization's result, while also support on way
Dynamic path optimization adjusts.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711183257.5A CN107798439A (en) | 2017-11-23 | 2017-11-23 | A kind of method for examining goods' transportation routing optimum results |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711183257.5A CN107798439A (en) | 2017-11-23 | 2017-11-23 | A kind of method for examining goods' transportation routing optimum results |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107798439A true CN107798439A (en) | 2018-03-13 |
Family
ID=61535666
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711183257.5A Pending CN107798439A (en) | 2017-11-23 | 2017-11-23 | A kind of method for examining goods' transportation routing optimum results |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107798439A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109190837A (en) * | 2018-09-17 | 2019-01-11 | 江苏满运软件科技有限公司 | The method, apparatus of Optimizing Transport route, electronic equipment, storage medium |
| CN109636213A (en) * | 2018-12-19 | 2019-04-16 | 拉扎斯网络科技（上海）有限公司 | Order splitting, evaluation method and device, electronic equipment and storage medium |
| CN112150076A (en) * | 2020-09-29 | 2020-12-29 | 陕西科技大学 | Workshop material dynamic distribution model design and implementation method based on station sequencing |
| CN112309118A (en) * | 2020-11-03 | 2021-02-02 | 广州市交通规划研究院 | Vehicle trajectory calculation method based on space-time similarity |
| CN113847910A (en) * | 2020-06-28 | 2021-12-28 | 阿里巴巴集团控股有限公司 | Generation method, monitoring method, device, electronic equipment and readable medium |
| WO2022266827A1 (en) * | 2021-06-22 | 2022-12-29 | Beijing Jingdong Zhenshi Information Technology Co., Ltd. | Logistics network simulation method and system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3057014A1 (en) * | 2015-02-13 | 2016-08-17 | Kozo Keikaku Engineering Inc. | Evacuation simulation device, evacuation simulation method, and program |
| CN106096762A (en) * | 2016-06-01 | 2016-11-09 | 四川九洲电器集团有限责任公司 | A kind of paths planning method and electronic equipment |
-
2017
- 2017-11-23 CN CN201711183257.5A patent/CN107798439A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3057014A1 (en) * | 2015-02-13 | 2016-08-17 | Kozo Keikaku Engineering Inc. | Evacuation simulation device, evacuation simulation method, and program |
| CN106096762A (en) * | 2016-06-01 | 2016-11-09 | 四川九洲电器集团有限责任公司 | A kind of paths planning method and electronic equipment |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109190837A (en) * | 2018-09-17 | 2019-01-11 | 江苏满运软件科技有限公司 | The method, apparatus of Optimizing Transport route, electronic equipment, storage medium |
| CN109636213A (en) * | 2018-12-19 | 2019-04-16 | 拉扎斯网络科技（上海）有限公司 | Order splitting, evaluation method and device, electronic equipment and storage medium |
| CN113847910A (en) * | 2020-06-28 | 2021-12-28 | 阿里巴巴集团控股有限公司 | Generation method, monitoring method, device, electronic equipment and readable medium |
| CN112150076A (en) * | 2020-09-29 | 2020-12-29 | 陕西科技大学 | Workshop material dynamic distribution model design and implementation method based on station sequencing |
| CN112150076B (en) * | 2020-09-29 | 2023-11-21 | 陕西科技大学 | Workshop material dynamic distribution model design and implementation method based on station sequencing |
| CN112309118A (en) * | 2020-11-03 | 2021-02-02 | 广州市交通规划研究院 | Vehicle trajectory calculation method based on space-time similarity |
| WO2022266827A1 (en) * | 2021-06-22 | 2022-12-29 | Beijing Jingdong Zhenshi Information Technology Co., Ltd. | Logistics network simulation method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107798439A (en) | A kind of method for examining goods' transportation routing optimum results | |
| CN108335485B (en) | License plate recognition data-based method for predicting dynamic simulation congestion of traffic at major incident | |
| CN107147621B (en) | Method for realizing risk control of internet medical cattle | |
| CN104332064B (en) | The method and device of road information is updated based on user trajectory | |
| CN108622142A (en) | A kind of train intelligent operation adjustment system and method based on real-time passenger flow | |
| CN107451673A (en) | Dispense region partitioning method and device | |
| CN108320494B (en) | Bus dynamic scheduling method, storage medium and device | |
| CN106127344A (en) | A kind of network bus arrival time Forecasting Methodology | |
| CN114715228B (en) | Railway passenger station shunting plan comprehensive management method and system | |
| WO2023279409A1 (en) | Path optimization method based on logistics tracking | |
| EP1550623A4 (en) | Inventory management method, inventory management system, and inventory management program | |
| CN116863708B (en) | Smart city scheduling distribution system | |
| CN109871423A (en) | The update method and device of public bus network crestal line | |
| CN105761008A (en) | Intelligent production management method for signal equipment maintenance | |
| CN116384853B (en) | Digital twin intelligent logistics management method and device | |
| CN107665417A (en) | A kind of vehicle dispatching method of goods delivery | |
| CN115331467B (en) | Video monitoring-based garbage disposal full-process monitoring method | |
| CN110031018A (en) | A kind of multi-destination multi-route method and system for planning | |
| CN113538143B (en) | Vegetable supply system based on block chain technology | |
| KR101151261B1 (en) | Train operation forecast and concentrated run prevention system and method | |
| Nesheli et al. | Use of real-time operational tactics to synchronize transfers in headway-based public transport service | |
| Gonçalves et al. | The impact of the ring road conclusion to the city of Guimarães, Portugal: Analysis of variations of traffic flows and accessibilities | |
| CN114548719A (en) | Bus shift acquisition method, device, equipment and storage medium | |
| CN114333212A (en) | Charging station monitoring and control method and system, electronic equipment and storage medium | |
| CN107894970A (en) | Terminal leaves the port the Forecasting Methodology and system of number |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180313 |
|
| RJ01 | Rejection of invention patent application after publication |