CN107832872A - Dynamic programming method for scenic spot route - Google Patents
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Abstract
The invention provides the dynamic programming method for scenic spot route, belongs to data processing field, including：Determine the initial value of scenic spot Zhong Ge sight spots value；Map comprising relative distance data between the Zhong Ge sight spots of scenic spot is handled, obtains routing information between each sight spot；Obtain the time requirement that visitor goes sight-seeing to scenic spot, the routing information for obtaining meeting between desired acquiescence exact value and remaining sight spot of the optimal path based on remaining sight spot in current point in time, visitor's selection demand of visitor carries out optimal value derivation, obtains the optimal path for current point in time.By the way that on the basis of given data is obtained, with reference to the Algorithm for Solving optimal path defined more, the optimal tour matched with current location can be obtained in real time according to the actual visit mode of visitor, so as to avoid waste of time, visit experience is improved.
Description
Technical field
The invention belongs to data processing field, the more particularly to dynamic programming method for scenic spot route.
Background technology
Current national vacation more concentrates on the Spring Festival and period on National Day, causes each sight spot stream of people because vacation excessively concentrates
Amount is very big, the experience of playing of visitor has been had a strong impact on, additionally, due to every visitor sight spot interested or to the inclined of multiple sight spots
Good difference, visitor can not get the tourism route of the customization for itself under scenic spots plan, reduce the visit of visitor
Experience.
The content of the invention
In order to solve shortcoming and defect present in prior art, obtained and visitor's current location the invention provides real-time
Corresponding programme path, so as to avoid the time from wasting, improve the dynamic programming method for scenic spot route of visit experience.
In order to reach above-mentioned technical purpose, the invention provides the dynamic programming method for scenic spot route, the dynamic
Planing method, including：
The initial value of scenic spot Zhong Ge sight spots value is determined, selects demand to be adjusted initial value according to visitor, is obtained each
The exact value of sight spot value；Map comprising relative distance data between the Zhong Ge sight spots of scenic spot is handled, obtains each sight spot
Between routing information；
Obtain time requirement go sight-seeing to scenic spot of visitor, based on time requirement, the exact value of each sight spot value, each sight spot it
Between routing information carry out optimal value derivation, obtain meeting the desired acquiescence optimal path of visitor, optimal road is given tacit consent in extraction
The material time point that the feasibility in path can be impacted in footpath；
Current point in time is obtained after prefixed time interval, based on remaining sight spot in current point in time, visitor's selection demand
Exact value and remaining sight spot between routing information carry out optimal value derivation, obtain optimal for current point in time
Path；
Acquiescence optimal path and the optimal path for current point in time are subjected to the comparison based on compatible degree, if agreed with
Degree is higher than predetermined threshold value, then continues, using acquiescence optimal path, otherwise to replace using the optimal path for current point in time silent
Optimal path is recognized as the optimal path for continuing visit at scenic spot.
Optionally, the dynamic programming method, in addition to：
Hobby grade of the visitor to each sight spot is obtained, obtains representing amount of the visitor to the hobby at each sight spot for hobby grade
Change result；
Based on the quantized result at each sight spot, the exact value of each sight spot value is adjusted, obtains representing each sight spot true
The correction value of each sight spot value of value.
Optionally, the dynamic programming method, in addition to：
Start in route planning, ambient parameter can adjust different numerical value according to corresponding situation
Optionally, the dynamic programming method, in addition to：
The setting means of sight spot value is divided into default setting and visitor actively sets；
Data related to value that default setting is provided by scenic spot are set, actively setting then by visitor for
The fancy grade at sight spot, which carries out quantization, can be used for model calculating.
Optionally, the dynamic programming method, in addition to：
There is provided value basis z0,
Pass through corresponding power function h according to visitor's hobby that scene data and market are collected1Value handle
Sight spot value after to processing
Optionally, the dynamic programming method, in addition to：
The node cost v at sight spot is obtained by function g (z)i；
Wherein z isOrAccording to whether the sight spot for visitor's selection makes a choice.
Optionally, the dynamic programming method, in addition to：
Map abstract model inputs the actual map map at sight spot,
Then it is triple by cartographic representation<G,Sstart,Sgoal>, wherein G=(N, A, c) represents state space graph, and N is
State node set, A are the set of arc.
By the relation of parameter setting above and graph abstraction between point and line in figure on assign path and be worth,
Wherein calculation is f (p)=g (p)+hmFor path p cost valuation, the cost vector that g (p) is path p, hm
For SmOn heuristic information；
The set that the cartographic information obtained afterwards is characterized as data is converted, draws numerical value most for path value calculation model
Excellent solution.
The beneficial effect that technical scheme provided by the invention is brought is：
, can be according to visitor with reference to the Algorithm for Solving optimal path defined more by the basis of given data is obtained
Actual visit mode, obtain the optimal tour matched with current location in real time, so as to avoid waste of time, improve
Visit experience.
Brief description of the drawings
In order to illustrate more clearly of technical scheme, the required accompanying drawing used in being described below to embodiment
It is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present invention, general for this area
For logical technical staff, on the premise of not paying creative work, other accompanying drawings can also be obtained according to these accompanying drawings.
Fig. 1 is the schematic flow sheet provided by the present invention for the dynamic programming method of scenic spot route.
Embodiment
To make the structure of the present invention and advantage clearer, the structure of the present invention is made further below in conjunction with accompanying drawing
Description.
Embodiment one
The invention provides the dynamic programming method for scenic spot route, as shown in figure 1, the dynamic programming method, bag
Include：
11st, the initial value of scenic spot Zhong Ge sight spots value is determined, selects demand to be adjusted initial value according to visitor, obtains
The exact value of each sight spot value；Map comprising relative distance data between the Zhong Ge sight spots of scenic spot is handled, obtains each scape
Routing information between point；
12nd, the time requirement that visitor goes sight-seeing to scenic spot is obtained, exact value, each scape being worth based on time requirement, each sight spot
Routing information between point carries out optimal value derivation, obtains meeting the desired acquiescence optimal path of visitor, extraction acquiescence is most
The material time point that the feasibility in path can be impacted in shortest path；
13rd, current point in time is obtained after prefixed time interval, based on remaining scape in current point in time, visitor's selection demand
Routing information between the exact value of point and remaining sight spot carries out optimal value derivation, obtains for current point in time most
Shortest path.
In force, the optimal value derivation in step 13, the computing of the optimal path for current point in time is obtained
Mode is：
The related definition of multi-goal path planning problem, the weight in vector representation path are provided, vectorial dimension is expression
The number (being here 2 dimensions) for the object function for needing to optimize.The Optimality Criteria in a single target is portrayed per one-dimensional element,
Dominance relation is a kind of partial ordering relation between vector.
Multi-goal path planning problem can formally be expressed as triple<G,Sstart,Sgoal>, wherein G=(N, A,
C) state space graph is represented, N is state node set, and A is the set of arc, and c (m, n) is transfer value function, is represented by state
Node SmIt is transferred to state node SnQ dimensional vector costs, when G is non-directed graph, c (m, n)=c (n, m)；Sstart∈ N are initial
State node；Sgoal∈NFor dbjective state node.
Predefined first against the key message in algorithm：
Define 1. and set vector f1And f2The two K dimensional vectors in position, claim f1Weak domination f2And if only if1≤i≤K meets f1i≤
f2i, it is denoted as f1≤f2, wherein f1iAnd f2iRepresent vector f1And f2I-th of element.
Define 2. and set vector f1And f2The two K dimensional vectors in position, claim f1It is strong to dominate f2And if only if1≤i≤K meets f1i≤
f2iAnd f1≠f2, it is denoted as f1<f2, wherein f1iAnd f2iRepresent vector f1And f2I-th of element.
It is referred to as that non-dominant and if only if for vector set X, vector x ∈ X to define 3.So that y<X, claim
For all non-dominant vectorial collection in set X
Close.
Define 4. and set PmnIt is state node SmWith state node SnBetween all paths set, path p1, p2∈Pmn,
Claim p1Dominate p2, and if only if g1<g2, it is denoted as p1<p2, wherein g1And g2It is path p respectively1And p2Cost vector.
Define 5. and set PmnIt is state node SmWith state node SnBetween all paths set, path p1, p2∈Pmn,
Claim p1For non-dominant path, and if only ifp2∈PmnSo that p2<p1, i.e., it is better than in the absence of other paths in all targets
Path p1
Two kinds of dominance relations are defined, reason is as follows：
(1) there is two all equal paths of weight equal qualification to do further on each object function in search procedure
Consider, now compared using strong dominance relation and need to be extended path candidate；
(2), should when the weight for a solution path of the assessment values with having obtained of the paths in search procedure is equal
What any path that Path extension goes out necessarily was dominated by force by this solution path, the necessity not further expanded is now sharp
Compare path candidate and solution path with loose government.
But problem is appointed as the original state uniquely determined and dbjective state, when state space graph is non-directed graph, can adopt
With reverse search method, search procedure is performed since dbjective state, solves the optimal road between original state and dbjective state
Gather in footpath.
The base unit extended every time using the multiple target heuristic search of Path extension method is a paths, profit
With the heuristic information guiding search process in path to improve search efficiency.
Definition 6. reaches state node S in setting p as search proceduremA paths, claim f (p)=g (p)+hmFor path p's
The cost vector that cost valuation, wherein g (p) are path p, hmFor SmOn heuristic information, estimate on each object function from shape
State node SmReach the minimum cost of dbjective state.
Path extension method makes a distinction for reaching each path of same state, search procedure set Gop(m)
It recorded and reach state SmThe path for extension, set Gcl(m) recorded up to state SmThe path extended, therefore, inversely
G in the expansion process of searchop(m)∪Gcl(m) record and be the current dbjective state found out and SmAll non-dominant paths,
All non-extensions paths of the current each state node of table OPEN records, each entry is triple (Sm, g (p), f (p))
The paths p represented.
Define 7. and set p1, p2For a non-extensions path, f (p in table OPEN1) it is path p1Cost valuation, claim p1For one
And if only if in bar non-dominant OPEN pathsSo that f (p2)<f(p1)。
Multiple target heuristic search selects a non-dominant OPEN road using the dominance relation between vector from OPEN tables
Footpath is extended, and the path expanded is inserted into OPEN tables as the path candidate extended next time, in the process, is used
COSTS records have currently tried to achieve non-domination solution set of paths.
Based on above-mentioned defined numerous parameters, reverse multiple target heuristic search algorithm BMHS basic procedure is
Input：Multi-goal path planning problem<G,Sstart,Sgoal>, initial OPEN tables and COSTS gather
Output：Optimal path set
1. step 1.1~1.3 are performed repeatedly, until OPEN tables are sky
All non-branch that time quantum exceeds TL (the limitation time that timelimit, i.e. visitor play) are selected in OPEN tables
With path, then these paths are deleted from OPEN tables.
1.1 Path selections, one non-dominant OPEN paths p is selected according to path cost valuation from OPEN tablesxExpanded
Exhibition, makes g (px) it is path pxCost vector, by pxCorresponding entry (Sm, g (px), f (px)) deleted from OPEN tables,
And by pxFrom Gop(m) G is moved on tocl(m)；
If 1.2 Sm=Sstart, then pxFor a solution path, g (px) it is solution path pxCost, by g (px) add COSTS
And deleted from OPEN tables by g (px) dominate non-extensions path；
If 1.3 Sm≠Sstart, then to SmAll forerunner's state Sn, it is generated to up to SnPath py, delete FTL (final
Time limit) ungratified path FTL=TL-HTL (wherein HTL is the time that visitor has spent).
Make g (py)=g (px)+c (m, n), if g (py) not by Gop(n)∪Gcl(n) free routing cost dominates in, then
1.3.1. by pyInsert Gop(n), and G is deletedop(n)∪Gcl(n) it is all by p inyThe path of domination；
1.3.2. calculate path pyCost valuation f (py), if f (py) do not dominated by any solution path in COSTS, then will
(Sn, g (py), f (py)) insert OPEN tables and record the predecessor information of correlation.
2. the required S of outputstartWith SgoalBetween optimal path set.
Optionally, the dynamic programming method, in addition to：
Hobby grade of the visitor to each sight spot is obtained, obtains representing amount of the visitor to the hobby at each sight spot for hobby grade
Change result；
Based on the quantized result at each sight spot, the exact value of each sight spot value is adjusted, obtains representing each sight spot true
The correction value of each sight spot value of value.
Optionally, the dynamic programming method, in addition to：
Start in route planning, ambient parameter can adjust different numerical value according to corresponding situation
In force, the mathematical modeling in software and parameter configuration can be adjusted, (namely model is at the beginning
Ambient parameter can adjust different numerical value according to corresponding situation) to adapt to the conditions such as different environment, position.
Optionally, the dynamic programming method, in addition to：
The setting means of sight spot value is divided into default setting and visitor actively sets；
Data related to value that default setting is provided by scenic spot are set, actively setting then by visitor for
The fancy grade at sight spot, which carries out quantization, can be used for model calculating.
In force, the setting means that sight spot is worth in the appraisal Model of sight spot is divided into default setting and visitor actively sets
It is fixed：Data related to value that default setting is provided by scenic spot are set, and actively setting is then by visitor for sight spot
Fancy grade carry out quantization can be used for model calculating.
Optionally, the dynamic programming method, in addition to：
There is provided value basis z0,
Pass through corresponding power function h according to visitor's hobby that scene data and market are collected1Value handle
Sight spot value after to processing
In force, it is provided with value basis z firstly for all sight spots0, then collected according to scene data and market
Visitor's hobby pass through corresponding power function h1Sight spot after being handled value is worthIn order to protrude
Sight spot priority selected by visitor, has carried out following Technology design：Visitor successively selects several target scapes in operation interface
Point, the sight spot value at these selected sight spotsInput data is handled function by (wherein j is that the sight spot of corresponding selection is numbered)
h2Sight spot value after being correctedThe exact numerical of the value at all sight spots is thus obtained.And the node at sight spot
Cost viThen obtain that (wherein z is by function g (z)OrAccording to whether the sight spot for visitor's selection makes a choice.(this
Its interior joint cost is worth inversely with node).
Optionally, the dynamic programming method, in addition to：
The node cost v at sight spot is obtained by function g (z)i；
Wherein z isOrAccording to whether the sight spot for visitor's selection makes a choice.
In force,
Optionally, the dynamic programming method, in addition to：
Map abstract model inputs the actual map map at sight spot,
Then it is triple by cartographic representation<G,Sstart,Sgoal>, wherein G=(N, A, c) represents state space graph, and N is
State node set, A are the set of arc.
By the relation of parameter setting above and graph abstraction between point and line in figure on assign path and be worth,
Wherein calculation is f (p)=g (p)+hmFor path p cost valuation, the cost vector that g (p) is path p, hm
For SmOn heuristic information；
The set that the cartographic information obtained afterwards is characterized as data is converted, draws numerical value most for path value calculation model
Excellent solution.
In force, the actual map map at map abstract model input sight spot, is then triple by cartographic representation<G,
Sstart,Sgoal>, wherein G=(N, A, c) expression state space graphs, N is state node set, and A is the set of arc.
Make it possible to assign path in figure by the relation of parameter setting above and graph abstraction between point and line
Value, wherein calculation is f (p)=g (p)+hmFor path p cost valuation, the cost vector that wherein g (p) is path p, hm
For SmOn heuristic information.Whole map just becomes the set of data after conversion, can be used directly to path value meter
Calculate model and draw numerical value optimal solution.
Except above-mentioned steps are, the dynamic programming method of the present embodiment proposition, in addition to implement appraisal procedure and value master
Dynamic amendment step.
Wherein, the former processing method is：The optimal route being calculated is output into material time point computation model to obtain
Go out in predetermined optimal route p that path optimality and feasibility may be caused the time point t of crucial effecti.Then by this
A little material time node input path value calculation models (time namely inputted is different with time requirement), draw current
Optimal path p under timing nodeiAnd it is compared with predetermined optimal route p：If compatible degree exceedes established standardses B so
Using former route, the optimal route that simulation assessment models obtain otherwise is set as optimal route.Pass through the segmentum intercalaris when corresponding
Route and the Desired Height of visitor agree with point constantly selected by amendment contrast guarantee.
The processing method of the latter is：Visitor (is obtained for the fancy grade at sight spot by program itself and external data storehouse
) data feedback model is input to so as to obtain quantized result.Then the data input obtained after quantization to node is worth and counted
Calculate and amended node value is drawn in model, obtained node is finally worth data input into default setting.By not
Disconnected ground autonomous learning, model can be worth constantly amendment to node so as to improve the authenticity of data.
The invention provides the dynamic programming method for scenic spot route, including：Determine the first of scenic spot Zhong Ge sight spots value
Initial value；Map comprising relative distance data between the Zhong Ge sight spots of scenic spot is handled, obtains routing information between each sight spot；
The time requirement that visitor goes sight-seeing to scenic spot is obtained, obtains meeting the desired acquiescence optimal path of visitor based on current point in time, trip
Routing information in objective selection demand between the exact value at remaining sight spot and remaining sight spot carries out optimal value derivation, obtains
For the optimal path of current point in time.It is optimal with reference to the Algorithm for Solving defined more by the basis of given data is obtained
Path, the optimal tour matched with current location can be obtained in real time, so as to avoid according to the actual visit mode of visitor
Waste of time, improve visit experience.
Each sequence number in above-described embodiment is for illustration only, does not represent the elder generation during the assembling or use of each part
Order afterwards.
Embodiments of the invention are the foregoing is only, are not intended to limit the invention, it is all in the spirit and principles in the present invention
Within, any modification, equivalent substitution and improvements made etc., it should be included in the scope of the protection.
Claims (7)
1. the dynamic programming method for scenic spot route, it is characterised in that the dynamic programming method, including：
The initial value of scenic spot Zhong Ge sight spots value is determined, selects demand to be adjusted initial value according to visitor, obtains each sight spot
The exact value of value；Map comprising relative distance data between the Zhong Ge sight spots of scenic spot is handled, obtained between each sight spot
Routing information；
The time requirement that visitor goes sight-seeing to scenic spot is obtained, based between time requirement, the exact value of each sight spot value, each sight spot
Routing information carries out optimal value derivation, obtains meeting the desired acquiescence optimal path of visitor, extraction is given tacit consent in optimal path
The material time point that the feasibility in path can be impacted；
Current point in time is obtained after prefixed time interval, the essence based on remaining sight spot in current point in time, visitor's selection demand
Really the routing information between value and remaining sight spot carries out optimal value derivation, obtains the optimal road for current point in time
Footpath.
2. the dynamic programming method according to claim 1 for scenic spot route, it is characterised in that the Dynamic Programming side
Method, in addition to：
Hobby grade of the visitor to each sight spot is obtained, obtains representing quantization knot of the visitor to the hobby at each sight spot for hobby grade
Fruit；
Based on the quantized result at each sight spot, the exact value of each sight spot value is adjusted, obtains representing each sight spot true value
Each sight spot value correction value.
3. the dynamic programming method according to claim 1 for scenic spot route, it is characterised in that the Dynamic Programming side
Method, in addition to：
Start in route planning, ambient parameter can adjust different numerical value according to corresponding situation.
4. the dynamic programming method according to claim 1 for scenic spot route, it is characterised in that the Dynamic Programming side
Method, in addition to：
The setting means of sight spot value is divided into default setting and visitor actively sets；
Data related to value that default setting is provided by scenic spot are set, and actively setting is then by visitor for sight spot
Fancy grade carry out quantization can be used for model calculating.
5. the dynamic programming method according to claim 1 for scenic spot route, it is characterised in that the Dynamic Programming side
Method, in addition to：
There is provided value basis z0；
Pass through corresponding power function h according to visitor's hobby that scene data and market are collected1Value is handled
Sight spot value afterwards
6. the dynamic programming method according to claim 1 for scenic spot route, it is characterised in that the Dynamic Programming side
Method, in addition to：
The node cost v at sight spot is obtained by function g (z)i；
Wherein z isOrAccording to whether the sight spot for visitor's selection makes a choice.
7. the dynamic programming method according to claim 1 for scenic spot route, it is characterised in that the Dynamic Programming side
Method, in addition to：
Map abstract model inputs the actual map map at sight spot,
Then it is triple by cartographic representation<G,Sstart,Sgoal>, wherein G=(N, A, c) expression state space graphs, N is state
Node set, A are the set of arc；
By the relation of parameter setting above and graph abstraction between point and line in figure on assign path and be worth；
Wherein calculation is f (p)=g (p)+hmFor path p cost valuation, the cost vector that g (p) is path p, hmFor Sm
On heuristic information；
The set that the cartographic information obtained afterwards is characterized as data is converted, show that numerical value is optimal for path value calculation model
Solution.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109063914A (en) * | 2018-08-10 | 2018-12-21 | 湖北文理学院 | A kind of tourism route planing method based on space-time data perception |
| CN109242214A (en) * | 2018-10-25 | 2019-01-18 | 中国联合网络通信集团有限公司 | Distribution route planing method and distribution route device for planning |
| CN109409612A (en) * | 2018-11-12 | 2019-03-01 | 平安科技（深圳）有限公司 | A kind of paths planning method, server and computer storage medium |
| CN109726864A (en) * | 2018-12-26 | 2019-05-07 | 杭州优行科技有限公司 | Layout of roads method, apparatus, server-side and storage medium |
| CN111222667A (en) * | 2018-11-27 | 2020-06-02 | 中国移动通信集团辽宁有限公司 | Route planning method, device, equipment and storage medium |
| CN112179370A (en) * | 2020-11-06 | 2021-01-05 | 思创数码科技股份有限公司 | Continuous optimal route planning method based on dynamic road network |
| CN112985413A (en) * | 2021-03-18 | 2021-06-18 | 河南工业大学 | Scenic spot path planning method and device based on improved A-x algorithm |
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| CN109409612B (en) * | 2018-11-12 | 2024-05-28 | 平安科技（深圳）有限公司 | Path planning method, server and computer storage medium |
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| CN111222667B (en) * | 2018-11-27 | 2023-09-19 | 中国移动通信集团辽宁有限公司 | Route planning method, device, equipment and storage medium |
| CN109726864A (en) * | 2018-12-26 | 2019-05-07 | 杭州优行科技有限公司 | Layout of roads method, apparatus, server-side and storage medium |
| CN109726864B (en) * | 2018-12-26 | 2021-04-09 | 杭州优行科技有限公司 | Route planning method, device, server and storage medium |
| CN112179370A (en) * | 2020-11-06 | 2021-01-05 | 思创数码科技股份有限公司 | Continuous optimal route planning method based on dynamic road network |
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