CN109389239A - A kind of random walk destruction method for reconstructing, system, equipment - Google Patents
A kind of random walk destruction method for reconstructing, system, equipment Download PDFInfo
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Abstract
The present invention relates to a kind of random walks to destroy method for reconstructing, system, equipment.The random walk destroys method for reconstructing, comprising: S1, the attribute information for obtaining package；S2, multi-C vector corresponding thereto is established according to package attribute information；S3, multi-C vector is inputted into greedy algorithm, obtains original route set；S4, the destruction reconstruction that route is carried out to original route set are handled, and are obtained compared with major path set；S5, objective function will be inputted compared with major path set, and will obtain the pole major path for meeting objective function requirement.With large neighborhood search algorithm, Real-time solution is carried out to the courier packages of input, realizes the path planning of package dispatching, that reduces path planning uses vehicle quantity, to reach high charging ratio.
Description
Technical field
The present invention relates to path plannings more particularly to a kind of random walk to destroy method for reconstructing, system, equipment.
Background technique
With the development of economy and the formation of people's shopping online habit, delivery industry have obtained swift and violent development, fastly
Pass that enterprise is more and more, the express mail amount of generation also increases year by year.On the one hand, the increase of express mail amount cause the dispatching of Express firm at
On the other hand this gradually increases, and, as the logistic distribution vehicle of each Express firm increases, greatly increases urban transportation
Burden.Therefore, to the improvement and innovation of traditional express delivery dis-tribution model, Express firm logistics cost is reduced, alleviation urban transportation is gathered around
It is congested with very important effect.
Large neighborhood search algorithm is one of the method for optimization for solving path.In large neighborhood search algorithm,
Usually used is these three destruction strategies of shaw removal/worst removal/random removal.But on this
Stating three kinds and destroying the factors not can solve in the practical problem of path planning with the problem more than vehicle amount.
Summary of the invention
In order to solve the above-mentioned technical problem, the purpose of the present invention is to provide a kind of random walks to destroy method for reconstructing, is
System, equipment.
According to an aspect of the invention, there is provided a kind of random walk destroys method for reconstructing, comprising:
S1, the attribute information for obtaining package；
S2, multi-C vector corresponding thereto is established according to package attribute information；
S3, multi-C vector is inputted into greedy algorithm, obtains original route set；
S4, the destruction reconstruction that route is carried out to original route set are handled, and are obtained compared with major path set；
S5, objective function will be inputted compared with major path set, and will obtain the pole major path for meeting objective function requirement.
Further, the attribute information of package includes address flow direction, time window.
Further, multi-C vector corresponding with package attribute information includes address flow direction, time window vector.
Further, multi-C vector is inputted into greedy algorithm, obtains original route set, comprising:
Multi-C vector is inputted into following formula, calculates fx1Value,
Wherein,The distance of the point is sent to for express mail,
Duration consumed by the point is sent to for express delivery；
Multi-C vector is inputted into greedy algorithm, calculates fx1' value；
Calculate △ 1=f'x1-fx1, when △ 1 is minimum, obtain original route set.
α, β are the adjustable parameter of cost function respectively, and dij indicates distance, Xijk indicated whether this point ... α, β, d,
It k, is much adjustable parameter in K, S, i, j, A.
Further, the destruction reconstruction for carrying out route to original route set is handled, and is obtained compared with major path set, comprising:
S41, the destruction reconstruction that route is carried out to original route set are handled, and obtain the more excellent set of epicycle；
S42, the more excellent set of epicycle is inputted into simulated annealing, obtains the pole major path set of epicycle；
S43, step S42 iteration are multiple, obtain compared with major path set.
Time of the iteration how many times depending on algorithm setting, for example calculate 5 minutes or 5000 wheel stopping calculating.
Further, the destruction reconstruction for carrying out route to original route set is handled, and obtains the more excellent set of epicycle, comprising:
One or more of original routes are randomly selected, the package of its original route is subjected to whole removals；
By removed package radom insertion into other routes, the more excellent set of epicycle is obtained.
Further, the destruction reconstruction for carrying out route to original route set is handled, and obtains the more excellent set of epicycle, comprising:
Randomly select one or more of original routes；
The f of original route according to the following formulax2,
Wherein,The distance of the point is sent to for express mail,
Duration consumed by the point is sent to for express delivery；
By the package of the original route of selection into row stochastic removal；
By removed package radom insertion into other routes, the corresponding f in every kind of insertion position is calculatedx2'；
Calculate △ 2=f'x2-fx2, when △ 2 is minimum, fx2' corresponding insertion position is optimal insertion position, obtain this
Take turns more excellent set.
Further, the destruction reconstruction for carrying out route to original route set is handled, and obtains also wrapping compared with major path set
It includes: it is adaptively selected to the strategy progress for destroying reconstruction, it obtains compared with destruction Reconstruction Strategy corresponding to major path set.
Further, adaptively selected to the strategy progress for destroying reconstruction, it obtains breaking compared with the corresponding of major path set
Ruin Reconstruction Strategy, comprising:
Epicycle is compared compared with major path and upper wheel pole major path, show that epicycle is corresponding and destroys Reconstruction Strategy score；
Above-mentioned steps iteration is multiple, counts to destruction Reconstruction Strategy score corresponding to every wheel；
The score for counting every kind of destruction Reconstruction Strategy obtains rebuilding compared with destruction corresponding to major path set according to score
Strategy.
Further, epicycle is compared compared with major path and upper wheel pole major path, show that epicycle is corresponding and destroys Reconstruction Strategy
Score, comprising:
Epicycle is better than upper wheel pole major path compared with major path, and epicycle is corresponding to destroy Reconstruction Strategy score；Or,
Epicycle never occurred compared with major path, and epicycle is corresponding to destroy Reconstruction Strategy score；Or,
Epicycle is the acceptable route of simulated annealing compared with major path, and epicycle is corresponding to destroy Reconstruction Strategy score.
Further, objective function is as follows:
Optimal route inputs objective function, and it is minimum to meet fx value.
According to another aspect of the present invention, a kind of random walk destruction reconstructing system is provided, comprising:
Obtain the acquisition unit of the attribute information of multiple packages；
Unit is established according to the multi-C vector that package attribute information establishes multi-C vector corresponding thereto；
Multi-C vector is inputted into greedy algorithm, the original route set for obtaining original route set establishes unit；
The destruction reconstruction processing that route is carried out to original route set, obtains the destruction reconstruction unit compared with major path set；
Objective function will be inputted compared with major path set, the pole major path for obtaining the pole major path for meeting objective function requirement obtains
Take unit.
Further, it is adaptively selected to the strategy progress for destroying reconstruction to destroy reconstruction unit, obtains compared with major path set
Corresponding destruction Reconstruction Strategy.
The system is the system for destroying method for reconstructing based on any of the above-described random walk, therefore the attribute information of package, multidimensional
Multi-C vector is inputted greedy algorithm by the foundation of vector, is obtained original route set, is broken to original route set progress route
Reconstruction processing is ruined, obtains carrying out objective function calculating compared with major path set, to optimal route set, optimal route is obtained, to breaking
Ruin the selection of Reconstruction Strategy and etc. random walk destroy method for reconstructing part as described in.
According to another aspect of the present invention, a kind of random walk destruction reconstructing apparatus is provided, including is stored with calculating
The computer-readable medium of machine program, described program are run for executing:
S1, the attribute information for obtaining package；
S2, multi-C vector corresponding thereto is established according to package attribute information；
S3, multi-C vector is inputted into greedy algorithm, obtains original route set；
S4, the destruction reconstruction that route is carried out to original route set are handled, and are obtained compared with major path set；
S5, objective function will be inputted compared with major path set, and will obtain the pole major path for meeting objective function requirement.
Further, the destruction reconstruction for carrying out route to original route set is handled, and obtains also wrapping compared with major path set
It includes: it is adaptively selected to the strategy progress for destroying reconstruction, it obtains compared with destruction Reconstruction Strategy corresponding to major path set.
The equipment is the equipment for destroying method for reconstructing based on any of the above-described random walk, therefore the attribute information of package, multidimensional
Multi-C vector is inputted greedy algorithm by the foundation of vector, is obtained original route set, is broken to original route set progress route
Reconstruction processing is ruined, obtains carrying out objective function calculating compared with major path set, to optimal route set, optimal route is obtained, to breaking
Ruin the selection of Reconstruction Strategy and etc. random walk destroy method for reconstructing part as described in.
Compared with prior art, the invention has the following advantages:
1, the exemplary random walk of the present invention destroys method for reconstructing, establishes corresponding thereto more according to package attribute information
Dimensional vector；Multi-C vector is inputted into greedy algorithm, obtains original route set；The destruction weight of route is carried out to original route set
Processing is built, is obtained compared with major path set；Optimal route set is inputted into objective function, obtains optimal route.With extensive neighbour
Domain search algorithm carries out Real-time solution to the courier packages of input, realizes the path planning of package dispatching, reduce path planning
With vehicle quantity, to reach high charging ratio.
2, the exemplary random walk of the present invention destroys reconstructing system, is believed by the attribute that acquisition unit obtains multiple packages
Breath；The multi-C vector of unit corresponding thereto according to the foundation of package attribute information is established by multi-C vector；Pass through original route
Set establishes unit and multi-C vector is inputted greedy algorithm, obtains original route set；By destroying reconstruction unit to initial road
Line set carries out the destruction reconstruction processing of route, obtains compared with major path set；It, will be compared with major path by pole major path acquiring unit
Set input objective function, obtains the pole major path for meeting objective function requirement.It is acted synergistically by each unit, realizes that package is matched
The path planning sent, that reduces path planning uses vehicle quantity, improves vehicle loading rate.
3, the exemplary random walk of the present invention destroys reconstructing apparatus, stores, is run for executing following programs: with big
Scale Neighborhood-region-search algorithm carries out Real-time solution to the courier packages of input, realizes the path planning of package dispatching, reduce path
Vehicle quantity is used in planning, to reach high charging ratio, is effectively reduced Express firm logistics cost, is alleviated urban traffic congestion.
Detailed description of the invention
Fig. 1 is the exemplary process diagram that one random walk of the embodiment of the present invention destroys method for reconstructing.
Specific embodiment
In order to be better understood by technical solution of the present invention, the present invention is made furtherly combined with specific embodiments below
It is bright.
Embodiment one:
Present embodiments provide a kind of random walk destruction method for reconstructing, comprising:
S1, the attribute information for obtaining package, the attribute information are address flow direction, time window, wherein address flow direction is package
Starting, termination address, time window is that client posts and the part time and requires delivery time；
S2, multi-C vector corresponding thereto is established according to package attribute information, which is address flow direction, time
Window；
S3, multi-C vector is inputted into greedy algorithm, obtains original route set,
It specifically includes:
Multi-C vector is inputted into following formula, calculates fx1Value,
Wherein,The distance of the point is sent to for express mail,
Duration consumed by the point is sent to for express delivery；
Multi-C vector is inputted into greedy algorithm, calculates fx1' value；
Calculate △ 1=f'x1-fx1, when △ 1 is minimum, obtain original route set.
S4, the destruction reconstruction that route is carried out to original route set are handled, and are obtained compared with major path set, further includes: to breaking
The strategy progress for ruining reconstruction is adaptively selected, obtains compared with destruction Reconstruction Strategy corresponding to major path set.The destruction plan of package
There are three types of slightly common: shaw/random/worst removal/route removal, the Reconstruction Strategy of package have:
regret-2/regret-4/greedy insertion.The present embodiment is broken using 4 × 3 total 12 kinds of arbitrary combinations
Ruin reconstruction.
S41, the destruction reconstruction that route is carried out to original route set are handled, and obtain the more excellent set of epicycle；
S411, one or more of original routes are randomly selected, by the package of its route into row stochastic shaw
Removal/worst removal/random removal/route removal carries out the package of its original route all
It removes；
S412, removed package is inserted into other routes in a manner of greedy/regret at random, is obtained current
Route set.And since there are many selection modes by removal and insertion, and the road of removal and insertion every time
Line position and package information are all random, it is therefore desirable to which it is optimal to obtain that many experiments carry out adjustable strategies.
Further, specifically:
Randomly select one or more of original routes；
The f of original route according to the following formulax2,
Wherein,The distance of the point is sent to for express mail,
Duration consumed by the point is sent to for express delivery；
By the package of the original route of selection into row stochastic removal；
By removed package radom insertion into other routes, the corresponding f in every kind of insertion position is calculatedx2'；
Calculate △ 2=f'x2-fx2, when △ 2 is minimum, fx2' corresponding insertion position is optimal insertion position, obtain this
Take turns more excellent set.
Specific steps are as follows:
(1) P={ p1,p2,...,pmBe current package set, ↑ indicate package addressee node at, ↓ indicate package group
At the node of part.N={ n1,n2,...,niIt is to include all distributing node information including starting point.Assuming that currently calculating
Set of paths R={ the r arrived1,r2..., rn, randomly select a wherein pathsWherein rkThe package information of route
Such as following table one.
Table one: rkRoute citing
(2) by rkWhole route is removed from current route set R, records this route rkThe package and its row being related to
V={ p is combined into for collection1↑,p2↑,p4↑,p5↑,p1↓,p2↓,p4↓,p5↓}.Then, V is fully inserted intoIt will be removed
The package of route is fully inserted into other routes.Package is inserted into the method that other routes take radom insertion, finds function
It is worth optimal insertion position (setting of target function value is usually cost size), reduction vehicle is achieved the purpose that with this.
The part pseudocode is as follows:
1 Function randomRouteRemoval(s∈{solutions},q∈N)
2 while q>0do
3 route:r=a randomly selected route from s
4 remove all the requests D in r
5 put the requests D in unassigned pool
6 q=q-1
7 end while。
S42, the more excellent set of epicycle is inputted into simulated annealing, obtains the pole major path set of epicycle.
Variation route set is specially inputted into simulated annealing, difference is currently solved to receive a ratio with certain probability
Route reaches global optimum's route, as epicycle optimal route.
In simulated annealing, the variation of temperature be initial high-temperature >=temperature slowly decline >=termination in low temperature.The height of temperature
A possibility that low decision receives new explanation size, to prevent from falling into the predicament of locally optimal solution.Simulated annealing is from a certain higher
Initial temperature is set out, and with the continuous decline of temperature parameter, join probability kick characteristic finds objective function at random in solution space
Globally optimal solution can be jumped out probabilityly in locally optimal solution and finally tend to global optimum.
Initial high-temperature is 50% come the probability for guaranteeing to receive poor solution, and temperature is gradually reduced in model iterative process,
After certain condition satisfaction (after such as 5000 wheel iteration), temperature can be reduced to certain value, this when to receive the general of poor solution
Rate is zero, reaches global convergence, to obtain the pole major path of epicycle iteration.
S43, step S42 iteration are multiple, obtain compared with major path set.
It is adaptively selected to the strategy progress for destroying reconstruction, it obtains rebuilding plan compared with the corresponding destruction of major path set
Slightly, comprising:
Epicycle is compared compared with major path and upper wheel pole major path, show that epicycle is corresponding and destroys Reconstruction Strategy score；
Above-mentioned steps iteration is multiple, counts to destruction Reconstruction Strategy score corresponding to every wheel；
The score for counting every kind of destruction Reconstruction Strategy obtains rebuilding compared with destruction corresponding to major path set according to score
Strategy.
Wherein, epicycle is compared compared with major path and upper wheel pole major path, show that epicycle is corresponding and destroys Reconstruction Strategy score,
Include:
Epicycle is better than upper wheel pole major path compared with major path, and epicycle is corresponding to destroy Reconstruction Strategy score；Or,
Epicycle never occurred compared with major path, and epicycle is corresponding to destroy Reconstruction Strategy score；Or,
Epicycle is the acceptable route of simulated annealing compared with major path, and epicycle is corresponding to destroy Reconstruction Strategy score.
The present embodiment utilizes adaptive algorithm simultaneously, corresponding to adjust by the corresponding resource cost size of obtained Route Set
Whole every kind tactful score, comprehensive lot of experimental data, finally obtains optimal policy.
Such as, in adaptive algorithm, by epicycle compared with major path (current solution) compared with upper wheel pole major path (extremely excellent solution) with
It obtains and (gives a mark by following three kinds of grades), at after certain the number of iterations (such as 100 wheel), count every kind of strategy and obtain solution
Score judges out optimal policy according to score.
Three kinds of grade scoring criterions:
Epicycle is compared with major path (current solution) better than upper wheel pole major path (extremely excellent solution) (score 1, such as 10 points)；
Never there is (score 1, such as 8 points) compared with major path (current solution) in epicycle；
The difference solution (score 1, such as 5 points) received according to simulated annealing.
S5, objective function will be inputted compared with major path set, and will obtain the pole major path for meeting objective function requirement,
Wherein, objective function is as follows:
Optimal route inputs objective function, and it is minimum to meet fx value.
The random walk of the present embodiment destroys reconstructing system, comprising:
Obtain the acquisition unit of the attribute information of multiple packages；
Unit is established according to the multi-C vector that package attribute information establishes multi-C vector corresponding thereto；
Multi-C vector is inputted into greedy algorithm, the original route set for obtaining original route set establishes unit；
The destruction reconstruction processing that route is carried out to original route set, obtains the destruction reconstruction unit compared with major path set；
Objective function will be inputted compared with major path set, the pole major path for obtaining the pole major path for meeting objective function requirement obtains
Take unit.
It is adaptively selected to the strategy progress for destroying reconstruction to destroy reconstruction unit, obtains breaking compared with corresponding to major path set
Ruin Reconstruction Strategy.
The system is the system for destroying method for reconstructing based on any of the above-described random walk, therefore the attribute information of package, multidimensional
Multi-C vector is inputted greedy algorithm by the foundation of vector, is obtained original route set, is broken to original route set progress route
Reconstruction processing is ruined, obtains carrying out objective function calculating compared with major path set, to optimal route set, optimal route is obtained, to breaking
Ruin the selection of Reconstruction Strategy and etc. random walk destroy method for reconstructing part as described in.
The random walk destruction reconstructing apparatus of the present embodiment, the computer-readable medium including being stored with computer program,
Described program is run for executing:
S1, the attribute information for obtaining package；
S2, multi-C vector corresponding thereto is established according to package attribute information；
S3, multi-C vector is inputted into greedy algorithm, obtains original route set；
S4, the destruction reconstruction that route is carried out to original route set are handled, and are obtained compared with major path set；
S5, objective function will be inputted compared with major path set, and will obtain the pole major path for meeting objective function requirement.
The destruction reconstruction processing that route is carried out to original route set, obtains compared with major path set, further includes: heavy to destroying
The strategy progress built is adaptively selected, obtains compared with destruction Reconstruction Strategy corresponding to major path set.
The equipment is the equipment for destroying method for reconstructing based on any of the above-described random walk, therefore the attribute information of package, multidimensional
Multi-C vector is inputted greedy algorithm by the foundation of vector, is obtained original route set, is broken to original route set progress route
Reconstruction processing is ruined, obtains carrying out objective function calculating compared with major path set, to optimal route set, optimal route is obtained, to breaking
Ruin the selection of Reconstruction Strategy and etc. random walk destroy method for reconstructing part as described in.
The computer readable storage medium can be computer-readable included in device described in above-described embodiment deposit
Storage media；It is also possible to individualism, without the computer readable storage medium in supplying equipment.Computer readable storage medium
Be stored with one perhaps more than one program described program be used to execute by one or more than one processor.
Embodiment two:
The feature that the present embodiment is the same as example 1 repeats no more, and the present embodiment feature different from embodiment one exists
In:
The random walk of the present embodiment destroys in method for reconstructing,
S41, the destruction reconstruction that route is carried out to original route set are handled, and obtain the more excellent set of epicycle；
S411, an original route is randomly selected, by the package of its route into row stochastic shawremoval/worst
The package of its original route is carried out whole removals by removal/random removal/route removal；
S412, removed package is inserted into other routes in a manner of greedy/regret at random, is obtained current
Route set.And since there are many selection modes by removal and insertion, and the road of removal and insertion every time
Line position and package information are all random, it is therefore desirable to which it is optimal to obtain that many experiments carry out adjustable strategies.
Above description is only the preferred embodiment of the application and the explanation to institute's application technology principle.Those skilled in the art
Member is it should be appreciated that invention scope involved in the application, however it is not limited to technology made of the specific combination of above-mentioned technical characteristic
Scheme, while should also cover in the case where not departing from the inventive concept, it is carried out by above-mentioned technical characteristic or its equivalent feature
Any combination and the other technical solutions formed.Such as features described above has similar function with (but being not limited to) disclosed herein
Energy.
Claims (15)
1. a kind of random walk destroys method for reconstructing, characterized in that include:
S1, the attribute information for obtaining package；
S2, multi-C vector corresponding thereto is established according to package attribute information；
S3, multi-C vector is inputted into greedy algorithm, obtains original route set；
S4, the destruction reconstruction that route is carried out to original route set are handled, and are obtained compared with major path set；
S5, objective function will be inputted compared with major path set, and will obtain the pole major path for meeting objective function requirement.
2. random walk according to claim 1 destroys method for reconstructing, characterized in that the attribute information of package includes address
Flow direction, time window.
3. random walk according to claim 2 destroys method for reconstructing, characterized in that corresponding with package attribute information
Multi-C vector includes address flow direction, time window vector.
4. random walk according to claim 1 destroys method for reconstructing, characterized in that multi-C vector is inputted greedy calculate
Method obtains original route set, comprising:
Multi-C vector is inputted into following formula, calculates fx1Value,
Wherein,The distance of the point is sent to for express mail,
Duration consumed by the point is sent to for express delivery；
Multi-C vector is inputted into greedy algorithm, calculates fx1' value；
Calculate △ 1=f'x1-fx1, when △ 1 is minimum, obtain original route set.
5. random walk according to claim 1 destroys method for reconstructing, characterized in that carry out route to original route set
Destruction reconstruction processing, obtain compared with major path set, comprising:
S41, the destruction reconstruction that route is carried out to original route set are handled, and obtain the more excellent set of epicycle；
S42, the more excellent set of epicycle is inputted into simulated annealing, obtains the pole major path set of epicycle；
S43, step S42 iteration are multiple, obtain compared with major path set.
6. random walk according to claim 5 destroys method for reconstructing, characterized in that carry out route to original route set
Destruction reconstruction processing, obtain the more excellent set of epicycle, comprising:
One or more of original routes are randomly selected, the package of its original route is subjected to whole removals；
By removed package radom insertion into other routes, the more excellent set of epicycle is obtained.
7. random walk according to claim 6 destroys method for reconstructing, characterized in that carry out route to original route set
Destruction reconstruction processing, obtain the more excellent set of epicycle, comprising:
Randomly select one or more of original routes；
The f of original route according to the following formulax2,
Wherein,The distance of the point is sent to for express mail,
Duration consumed by the point is sent to for express delivery；
By the package of the original route of selection into row stochastic removal；
By removed package radom insertion into other routes, the corresponding f in every kind of insertion position is calculatedx2'；
Calculate △ 2=f'x2-fx2, when △ 2 is minimum, fx2' corresponding insertion position is optimal insertion position, obtain epicycle compared with
Excellent set.
8. random walk according to claim 1 destroys method for reconstructing, characterized in that carry out route to original route set
Destruction reconstruction processing, obtain compared with major path set, further includes: to destroy rebuild strategy carry out it is adaptively selected, obtain compared with
Destruction Reconstruction Strategy corresponding to major path set.
9. random walk destruction method for reconstructing according to claim 8, characterized in that carried out certainly to the strategy rebuild is destroyed
Selection is adapted to, the corresponding destruction Reconstruction Strategy compared with major path set is obtained, comprising:
Epicycle is compared compared with major path and upper wheel pole major path, show that epicycle is corresponding and destroys Reconstruction Strategy score；
Above-mentioned steps iteration is multiple, counts to destruction Reconstruction Strategy score corresponding to every wheel；
The score for counting every kind of destruction Reconstruction Strategy is obtained according to score compared with destruction Reconstruction Strategy corresponding to major path set.
10. random walk according to claim 9 destroys method for reconstructing, characterized in that by epicycle compared with major path and upper wheel
Major path comparison in pole show that epicycle is corresponding and destroys Reconstruction Strategy score, comprising:
Epicycle is better than upper wheel pole major path compared with major path, and epicycle is corresponding to destroy Reconstruction Strategy score；Or,
Epicycle never occurred compared with major path, and epicycle is corresponding to destroy Reconstruction Strategy score；Or,
Epicycle is the acceptable route of simulated annealing compared with major path, and epicycle is corresponding to destroy Reconstruction Strategy score.
11. random walk according to claim 1 destroys method for reconstructing, characterized in that
Objective function is as follows:
Optimal route inputs objective function, and it is minimum to meet fx value.
12. a kind of random walk destroys reconstructing system, characterized in that include:
Obtain the acquisition unit of the attribute information of multiple packages；
Unit is established according to the multi-C vector that package attribute information establishes multi-C vector corresponding thereto；
Multi-C vector is inputted into greedy algorithm, the original route set for obtaining original route set establishes unit；
The destruction reconstruction processing that route is carried out to original route set, obtains the destruction reconstruction unit compared with major path set；
Objective function will be inputted compared with major path set, the pole major path for obtaining the pole major path for meeting objective function requirement obtains list
Member.
13. random walk according to claim 12 destroys reconstructing system, characterized in that it is heavy to destroying to destroy reconstruction unit
The strategy progress built is adaptively selected, obtains compared with destruction Reconstruction Strategy corresponding to major path set.
14. a kind of random walk destroys reconstructing apparatus, characterized in that computer-readable Jie including being stored with computer program
Matter, described program are run for executing:
S1, the attribute information for obtaining package；
S2, multi-C vector corresponding thereto is established according to package attribute information；
S3, multi-C vector is inputted into greedy algorithm, obtains original route set；
S4, the destruction reconstruction that route is carried out to original route set are handled, and are obtained compared with major path set；
S5, objective function will be inputted compared with major path set, and will obtain the pole major path for meeting objective function requirement.
15. 4 random walks destroy reconstructing apparatus according to claim 1, characterized in that carry out route to original route set and break
Reconstruction processing is ruined, is obtained compared with major path set, further includes: it is adaptively selected to the strategy progress for destroying reconstruction, obtain more excellent road
Destruction Reconstruction Strategy corresponding to line set.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109816279A (en) * | 2019-03-22 | 2019-05-28 | 武汉大学 | A kind of goods stock Contents in brief Intelligent Dynamic Scheduling method |
| CN111950950A (en) * | 2019-05-17 | 2020-11-17 | 北京京东尚科信息技术有限公司 | Order distribution path planning method and device, computer medium and electronic equipment |
| CN112288347A (en) * | 2020-02-21 | 2021-01-29 | 北京京东振世信息技术有限公司 | Method, device, server and storage medium for determining route of cold chain distribution |
| CN112749822A (en) * | 2019-10-30 | 2021-05-04 | 北京京东振世信息技术有限公司 | Method and device for generating route |
| CN112949887A (en) * | 2019-12-11 | 2021-06-11 | 顺丰科技有限公司 | Dispatching path planning method, device, equipment and computer readable storage medium |
| WO2021135208A1 (en) * | 2019-12-31 | 2021-07-08 | 苏宁云计算有限公司 | Delivery path planning method and system taking order aggregation degree into consideration |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101866384A (en) * | 2010-06-18 | 2010-10-20 | 杭州电子科技大学 | Improved artificial fish school optimization method based on vehicle path planning |
-
2017
- 2017-08-14 CN CN201710691352.XA patent/CN109389239A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101866384A (en) * | 2010-06-18 | 2010-10-20 | 杭州电子科技大学 | Improved artificial fish school optimization method based on vehicle path planning |
Non-Patent Citations (2)
| Title |
|---|
| 张梦颖: "不确定因素下路径规划问题研究", 《中国博士学位论文全文数据库 工程科技Ⅱ辑》 * |
| 苗国强等: "基于自适应大规模邻域搜索算法的带时间窗的车辆路径问题", 《物流技术》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109816279A (en) * | 2019-03-22 | 2019-05-28 | 武汉大学 | A kind of goods stock Contents in brief Intelligent Dynamic Scheduling method |
| CN111950950A (en) * | 2019-05-17 | 2020-11-17 | 北京京东尚科信息技术有限公司 | Order distribution path planning method and device, computer medium and electronic equipment |
| CN112749822A (en) * | 2019-10-30 | 2021-05-04 | 北京京东振世信息技术有限公司 | Method and device for generating route |
| CN112749822B (en) * | 2019-10-30 | 2024-05-17 | 北京京东振世信息技术有限公司 | Method and device for generating route |
| CN112949887A (en) * | 2019-12-11 | 2021-06-11 | 顺丰科技有限公司 | Dispatching path planning method, device, equipment and computer readable storage medium |
| CN112949887B (en) * | 2019-12-11 | 2023-11-28 | 顺丰科技有限公司 | Method, device and equipment for planning dispatch path and computer readable storage medium |
| WO2021135208A1 (en) * | 2019-12-31 | 2021-07-08 | 苏宁云计算有限公司 | Delivery path planning method and system taking order aggregation degree into consideration |
| CN112288347A (en) * | 2020-02-21 | 2021-01-29 | 北京京东振世信息技术有限公司 | Method, device, server and storage medium for determining route of cold chain distribution |
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