CN103336824B - Dynamic monitoring method and system for inquiring minimum distance and position - Google Patents

Abstract

The invention provides a dynamic monitoring method and system for inquiring the minimum distance and position. The method comprises the step: giving a customer point set C, a facility point set F and a candidate position set P, wherein the minimized distance and position is that , is the weighted attracting distance of a customer point c, w(c) is the weight of the customer point c, if the distance d (c and f) between the customer point c and a facility point f in a road network is the minima value of the point c and the point f, the point f is defined to be an attractor of the point c, the point c is attracted by the point f, a(c)= d(c and f), and the d(c and f) is the attracting distance; obtaining p according to the initial facility point set F and the initial customer point set C in the road network; dynamically monitoring the p at any time according to updating of the facility point set F or the customer point set C in the road network. The dynamic monitoring method and system can rapidly and dynamically inquire the minimum distance and position.

Description

Inquiry minimum range and the dynamic monitoring and controlling method and system of position

Technical field

The present invention relates to the dynamic monitoring and controlling method and system of a kind of inquiry minimum range and position.

Background technology

In the past few years, have the class of many work sutdies one in the case where there is client's point set " facility place ask Topic "（Referring to document 8：Farahani,R.Z.,Hekmatfar,M.:Facility Location:Concepts,Models, Algorithms and Case Studies, 1st edn.Physica-Verlag HD (2009), document 15：Nickel,S., Puerto,J.:Location Theory:A Unified Approach,1st edn.Springer(2005)）.Most universal In the case of, problem is included：（1）The set C of one client's point and facility point candidate collection P, and（2）K is inquired about in P The position of new facility point is so as to meeting the optimum condition of a predefined.Such issues that in the case where k is constant exist it is many Algorithm in the item formula time, is NP-hard problems in the case where k is general variance（Referring to document 8 and 15）, existed Its approximate data is mainly studied in work.

Optimum position inquiry problem can be seen as a mutation of facility Placement Problems, and P first is a unlimited set； Then usual k=1, that is to say, that only need to carry out chosen position for a newly-built facility point；Finally generally have one in advance Individual facility point set F.The above is difference of the optimum position inquiry problem relative to general " facility Placement Problems ".

The research work of problem is inquired about in optimum position before（Referring to document 2：Cabello,S., J.M.,Langerman,S.,Seara,C.,Ventura,I.:Reverse facility location problems.In: CCCG, pp.68-71 (2005), document 6：Du,Y.,Zhang,D.,Xia,T.:The optimal-location query.In:SSTD, pp.163-180 (2005), document 21：Wong,R.C.W.,¨Ozsu,T.,Yu,P.S.,Fu,A.W.C., Liu,L.:Efficient method for maximizing bichromatic reverse nearest Neighbor.PVLDB2 (1), 1126-1137 (2009), document 24：Zhang,D.,Du,Y.,Xia,T.,Tao,Y.: Progressive computation of the min-dist optimal-location query.In:VLDB, pp.643–654(2006)）Middle consideration is distance between facility point and client's point in Lp spaces.Wherein Cabello et al. （Referring to document 2）With Wong et al.（Referring to document 21）Research based on L2 spaces, and Du et al.（Referring to document 6）With Zhang et al.（Referring to document 24）Research based on L1 spaces.Optimum position inquiry problem is not studied in these work Situation in road network.

Existing research work includes other two kinds of problems relevant with the position selection of facility point：Single facility point is inquired about Problem（Referring to document 8 and 15）And facility point sets up in real time problem（Referring to document 9：Fotakis,D.:Incremental algorithms for facility location and kmedian.Theor.Comput.Sci.361(2-3),275– 313 (2006), document 13：Meyerson,A.:Online facility location.In:FOCS,pp.426–431 (2001)）, but both Study on Problems contents are similar different with optimum position inquiry problem.Single facility point inquires about problem Research, gives the set of client's point, finds a facility and sets up point so as to meet an optimum condition, asks at this In topic, the facility point set not having built up in input data, but in optimum position inquiry problem, need to consider one The set of existing facility point.Facility point sets up in real time Study on Problems, with being continuously increased for client's point, position is chosen in real time Set up vertical new facility point to meet a given optimal conditions, with optimum position inquiry problem similarly, such issues that When new facility point is found, it is also considered that existing facility point set, but the method that [9] and [13] are adopted can not be solved Problem is inquired about in optimum position, this is because setting up in real time in problem in facility point, the candidate locations for setting up new facility point are one Limited set, but in optimum position inquiry problem, the candidate locations for setting up new facility point are a unlimited set, example Such as the set in all places in Lp spaces or all places on all sides in road network.Research work in our prior In we have proposed the method for optimum position in static one query road network（Referring to document 22：Xiao,X.,Yao,B.,Li,F.: Optimal location queries in road network databases.In:ICDE,pp.804–815(2011)）, Compared with that article, our invention proposes the solution of optimum position in new Dynamic Maintenance road network, and for three Different optimum position inquiry problems devise concrete implementation method.

Finally, many researchs with regard to querying method in Traffic network database are there are in existing research work（Referring to 3： Chen,Z.,Shen,H.T.,Zhou,X.,Yu,J.X.:Monitoring path nearest neighbor inroad networks.In:SIGMOD, pp.591-602 (2009), document 4：Deng,K.,Zhou,X.,Shen,H.T.,Sadiq,S., Li,X.:Instance optimal query processing in spatial networks.VLDBJ18(3),675– 693 (2009), document 11：Jensen,C.S.,Kol′aˇrvr,J.,Pedersen,T.B.,Timko,I.:Nearest neighbor queries in road networks.In:GIS, pp.1-8 (2003), document 12：Kolahdouzan, M.R.,Shahabi,C.:Voronoi-based k-nearest neighbor search for spatial network databases.In:VLDB, pp.840-851 (2004), document 14：Mouratidis,K.,Yiu,M.L.,Papadias,D., Mamoulis,N.:Continuous nearest neighbor monitoring in road networks.In:VLDB, Pp.43-54 (2006), document 16：Papadias,D.,Zhang,J.,Mamoulis,N.,Tao,Y.:Query processing in spatial network databases.In:VLDB, pp.802-813 (2003), document 17： Samet,H.,Sankaranarayanan,J.,Alborzi,H.:Scalable network distance browsing in spatial databases.In:SIGMOD, pp.43-54 (2008), document 18：Sankaranarayanan,J.,Samet, H.:Distance oracles for spatial networks.In:ICDE, pp.652-663 (2009), document 19： Sankaranarayanan,J.,Samet,H.,Alborzi,H.:Path oracles for spatial Networks.PVLDB2 (1), 1210-1221 (2009), document 23：Yiu,M.L.,Mamoulis,N.,Papadias,D.: Aggregate nearest neighbor queries in road networks.TKDE17(6),820–833(2005)）. But these research work are all the inquiries for paying close attention to closest approach in Traffic network database（Referring to document 12,16 and 17）And its mutation: Closest approach approximate query（Referring to document 18 and 19）, aggregate query（Referring to document 23）, continuous closest approach inquiry（Referring to document 14）, the inquiry of path closest approach（Referring to document 3）Etc..Technology in these research work can not solve optimum position inquiry Problem, because closest approach inquiry problem is inherently different with optimum position inquiry problem.

In addition, the related bibliography of the present invention is also including as follows：

Document 1：de Berg,M.,Cheong,O.,van Kreveld,M.,Overmars,M.:Computational Geometry:Algorithms and Applications,3rd edn.Springer-Verlag(2008)；

Document 5：Dijkstra,E.W.:A note on two problems in connexion with graphs.Numerische Mathematik1,269–271(1959)；

Document 7：Erwig,M.,Hagen,F.:The graph voronoi diagram with applications.Networks36,156–163(2000)；

Document 10：Hershberger,J.:Finding the upper envelope of n line segments in o(n log n)time.Inf.Process.Lett.33(4),169–174(1989)；

Document 20：Shekhar,S.,Liu,D.R.:CCAM:A connectivity-clustered access method for networks and network computations.TKDE9(1),102–119(1997)。

The content of the invention

It is an object of the invention to provide the dynamic monitoring and controlling method and system of a kind of inquiry minimum range and position, can be fast Speed and dynamically inquiry minimum range and position.

To solve the above problems, the present invention provides the dynamic monitoring and controlling method of a kind of inquiry minimum range and position, including：

Give the set C of the client's point and set F of a facility point, and a location candidate set P, most narrow spacing It is from positionWhereinWeighting for client point c attracts distance, and w (c) is visitor The weight of family point c, if client point c and facility point f in road network be apart from d (c, f) point in c and F minimum, The attraction person that f is c is then defined, c is attracted by f, a (c)=d (c, f) is the attraction distance of c；

P is obtained according to facility point set F initial in road network and client's point set C;

According to the renewal p of dynamic monitoring at any time that facility point set F in road network or client's point set C occur.

Further, in the above-mentioned methods, obtain p's according to facility point set F initial in road network and client's point set C Step includes：

By the Connected undigraph G to expression road network^o=(V^o,E^o) all of facility point f and client point c are inserted by E^oIn When being divided into new, for each point ρ ∈ C ∪ F, first consider the side e ∈ E that ρ is located^o, two end points for making e are v_lWith v_r, it is then two parts i.e. from v by e point_lTo ρ and from ρ to v_r, so that ρ becomes a new summit of Connected undigraph, add institute Some new summits are generating a new Connected undigraph G=(V, E), and V=V^o∪C∪F；

For every a line e ∈ E_cInitialization calculates its local optimum positions I and corresponding financial value m, wherein, E_cBe comprising In location candidate set P side a little set, the financial value of certain position σ is Local optimum positions I is all point sets with maximum return value on the e of side；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as maximum contention power position p。

Further, in the above-mentioned methods, for every a line e ∈ E_cInitialization calculate its local optimum positions I and The step of corresponding financial value m, includes：

By the algorithm of Erwig and Hagen to calculate G in each vertex v nearest facility point f and apart from d (v, f)；

Two end points v of e are calculated respectively_lAnd v_rAttraction set A (v_l) and A (v_r), wherein, give a vertex v, A V () is the set of all client point c and respective distances d (c, v) that can be attracted to comprising v；

According to the A (v for having calculated_l) and A (v_r) calculate e local optimum positions I and corresponding financial value m.

Further, in the above-mentioned methods, it is known that a vertex v, A (v) is obtained as follows：

Initialization A (v) is empty set；

All summits in G are traveled through with dijkstra's algorithm apart from ascending order according to v；

For the vertex v ' that each is traversed, a (v ') is made to be distances of the v ' to its nearest facility point f, if d (v, V ')≤a (v '), and v ' is client's point, then will be<v′,d(v′,v)>Vertex v is added to attract after set A (v)；If d (v,v′)>A (v '), then ignore all sides with v ' as end points.

Further, in the above-mentioned methods, according to the A (v for having calculated_l) and A (v_r) calculate e local optimum positions I And the step of corresponding financial value m includes：

Calculate the financial value of two end points of e；

If the financial value of two end points is different, that larger end points of financial value is returned as the local optimum position of e I is put, the larger corresponding financial value m as e in two financial values；Otherwise, using the two equal financial values as e correspondence Financial value m, and investigate the financial value at the midpoint of e, if less than end points financial value, using two end points as e local optimum Position I, if the financial value at the midpoint of e is equal with the financial value of two end points, using whole piece side e all as local optimum positions I。

Further, in the above-mentioned methods, the renewal for being occurred according to facility point set F in road network or client's point set C with When dynamic monitoring p the step of include：

The renewal of facility point and client's point in road network can be attributed to one client's point of increase（AddC(c)）, reduce one Client's point DelC (c), increases facility point AddF (f), reduces by facility point DelF (f) totally four kinds of basic operation；

When one updates operation arrives, the set for attracting distance to be updated affected client's point is calculated first V_cIf operation is AddC (c) or DelC (c), V_c={c}；If operation is AddF (f) or DelF (f), V_c={c|<c,d (c,v)>∈A(f)}；

For each client point c ∈ V_c, the attraction before client's point is found out apart from a⁰C () and new attraction are apart from a' (c), and set up two setWith

For each client point c ∈ V_c, according to a⁰(c), a'(c),Come update every a line e local most Best placement I and corresponding financial value m, the local optimum positions and corresponding financial value before order renewal are respectively I₀And m₀；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as minimum range and position p。

Further, in the above-mentioned methods, it is known that the local optimum positions and corresponding financial value before renewal are respectively I₀And m₀, according to a⁰(c), a'(c),To update the local optimum positions I and corresponding financial value m of every a line e The step of include：

Set up a vertex set

For each vertex v in S：IfAndThen set m (v)=m (v)- w(c)(a⁰(c)-d(v,c))；IfAndThen set m (v)=m (v)+w (c) (a ' (c)-d(v,c))；IfWithAll set up, then set m (v)=m (v)+w (c) (a ' (c)-a⁰(c))；Wherein m (v) represents the financial value of vertex v；

For every a line e, if at least one changed in the financial value of two end points of e：

Read e two end points update after financial value, if the financial value of two end points is different, return financial value compared with Local optimum positions I, in two financial values larger corresponding financial value m as e of that the big end points as e；Otherwise, will The two equal financial values and investigate the financial value at the midpoint of e as the corresponding financial value m of e, if than end points financial value It is little, then using two end points as e local optimum positions I, if the financial value phase of the financial value at the midpoint of e and two end points Deng then using whole piece side e all as local optimum positions I.

A kind of another side of the invention, there is provided the dynamic monitoring system of inquiry minimum range and position, including：

Definition module, for giving the set C of the client's point and set F of a facility point, and a candidate bit Set P is put, minimum range and position areWhereinWeighting for client point c is inhaled Draw distance, w (c) is the weight of client point c, if client point c and facility point f in road network apart from d (c, f) be c and F In point minimum, then define the attraction person that f is c, c attracted by f, a (c)=d (c, f) for c attraction distance；

Acquisition module, for obtaining p according to facility point set F initial in road network and client's point set C;

Update module, for the renewal dynamic monitoring at any time occurred according to facility point set F in road network or client's point set C p。

Further, in said system, the acquisition module is used for：

By the Connected undigraph G to expression road network^o=(V^o,E^o) all of facility point f and client point c are inserted by E^oIn When being divided into new, for each point ρ ∈ C ∪ F, first consider the side e ∈ E that ρ is located^o, two end points for making e are v_lWith v_r, it is then two parts i.e. from v by e point_lTo ρ and from ρ to v_r, so that ρ becomes a new summit of Connected undigraph, add institute Some new summits are generating a new Connected undigraph G=(V, E), and V=V^o∪C∪F；

For every a line e ∈ E_cInitialization calculates its local optimum positions I and corresponding financial value m, wherein, E_cFor bag In P containing location candidate set side a little set, the financial value of certain position σ is Local optimum positions I is all point sets with maximum return value on the e of side；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as maximum contention power position p。

Further, in said system, the acquisition module is used for：

By the algorithm of Erwig and Hagen to calculate G in each vertex v nearest facility point f and apart from d (v, f)；

Two end points v of e are calculated respectively_lAnd v_rAttraction set A (v_l) and A (v_r), wherein, give a vertex v, A V () is the set of all client point c and respective distances d (c, v) that can be attracted to comprising v；

According to the A (v for having calculated_l) and A (v_r) calculate e local optimum positions I and corresponding financial value m.

Further, in said system, the acquisition module is used for：

Initialization A (v) is empty set；

All summits in G are traveled through with dijkstra's algorithm apart from ascending order according to v；

For the vertex v ' that each is traversed, a (v ') is made to be distances of the v ' to its nearest facility point f, if d (v, V ')≤a (v '), and v ' is client's point, then will be<v′,d(v′,v)>Vertex v is added to attract after set A (v)；If d (v,v′)>A (v '), then ignore all sides with v ' as end points.

Further, in said system, the acquisition module is used for：

Calculate the financial value of two end points of e；

If the financial value of two end points is different, that larger end points of financial value is returned as the local optimum position of e I is put, the larger corresponding financial value m as e in two financial values；Otherwise, using the two equal financial values as e correspondence Financial value m, and investigate the financial value at the midpoint of e, if less than end points financial value, using two end points as e local optimum Position I, if the financial value at the midpoint of e is equal with the financial value of two end points, using whole piece side e all as local optimum positions I。

Further, in said system, the update module is used for：

The renewal of facility point and client's point in road network can be attributed to one client's point of increase（AddC(c)）, reduce one Client's point DelC (c), increases facility point AddF (f), reduces by facility point DelF (f) totally four kinds of basic operation；

When one updates operation arrives, the set for attracting distance to be updated affected client's point is calculated first V_cIf operation is AddC (c) or DelC (c), V_c={c}；If operation is AddF (f) or DelF (f), V_c={c|<c,d (c,v)>∈A(f)}；

For each client point c ∈ V_c, the attraction before client's point is found out apart from a⁰C () and new attraction are apart from a' (c), and set up two setWith

For each client point c ∈ V_c, according to a⁰(c), a'(c),Come update every a line e local most Best placement I and corresponding financial value m, the local optimum positions and corresponding financial value before order renewal are respectively I₀And m₀；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as minimum range and position p。

Further, in said system, it is known that the local optimum positions and corresponding financial value before renewal are respectively I₀And m₀, the update module is used for：

Set up a vertex set

For each vertex v in S：IfAndThen set m (v)=m (v)- w(c)(a⁰(c)-d(v,c))；IfAndThen set m (v)=m (v)+w (c) (a ' (c)-d(v,c))；IfWithAll set up, then set m (v)=m (v)+w (c) (a ' (c)-a⁰(c))；Wherein m (v) represents the financial value of vertex v；

For every a line e, if at least one changed in the financial value of two end points of e：

Read e two end points update after financial value, if the financial value of two end points is different, return financial value compared with Local optimum positions I, in two financial values larger corresponding financial value m as e of that the big end points as e；Otherwise, will The two equal financial values and investigate the financial value at the midpoint of e as the corresponding financial value m of e, if than end points financial value It is little, then using two end points as e local optimum positions I, if the financial value phase of the financial value at the midpoint of e and two end points Deng then using whole piece side e all as local optimum positions I.

Compared with prior art, the set F of the set C and a facility point by giving client's point of the invention, with And a location candidate set P, minimum range and position areWhereinFor visitor The weighting of family point c attracts distance, and w (c) is the weight of client point c, if client point c and facility point f in road network away from It is the minimum of the point in c and F from d (c, f), then defines the attraction person that f is c, c is attracted by f, a (c)=d (c, f) is the attraction of c Distance；P is obtained according to facility point set F initial in road network and client's point set C;According to facility point set F or visitor in road network The renewal that family point set C the occurs p of dynamic monitoring at any time, can quickly and dynamically inquire about minimum range and position.

Description of the drawings

Fig. 1 is the flow chart of the dynamic monitoring and controlling method of the inquiry minimum range and position of one embodiment of the invention.

Specific embodiment

It is understandable to enable the above objects, features and advantages of the present invention to become apparent from, it is below in conjunction with the accompanying drawings and concrete real The present invention is further detailed explanation to apply mode.

Embodiment one

As shown in figure 1, the present invention provides the dynamic monitoring and controlling method of a kind of inquiry minimum range and position, including step S1 is extremely Step S3.

Step S1, gives the set C of the client's point and set F of a facility point, and a location candidate set P, minimum range and position areWhereinWeighting for client point c attracts distance, W (c) is the weight of client point c, if client point c and facility point f in road network apart from d (c, f) be point in c and F Minimum, then define the attraction person that f is c, c attracted by f, a (c)=d (c, f) for c attraction distance；

Step S2, according to facility point set F initial in road network and client's point set C p is obtained;

Preferably, step S2 includes：

Included the step of obtaining p according to facility point set F initial in road network and client's point set C：

By the Connected undigraph G to expression road network^o=(V^o,E^o) all of facility point f and client point c are inserted by E^oIn When being divided into new, for each point ρ ∈ C ∪ F, first consider the side e ∈ E that ρ is located^o, two end points for making e are v_lWith v_r, it is then two parts i.e. from v by e point_lTo ρ and from ρ to v_r, so that ρ becomes a new summit of Connected undigraph, add institute Some new summits are generating a new Connected undigraph G=(V, E), and V=V^o∪C∪F；

For every a line e ∈ E_cInitialization calculates its local optimum positions I and corresponding financial value m, wherein, E_cBe comprising In location candidate set P side a little set, the financial value of certain position σ is Local optimum positions I is all point sets with maximum return value on the e of side；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as maximum contention power position p。

Preferably, for every a line e ∈ E_cInitialization calculates its local optimum positions I's and corresponding financial value m Step includes：

By the algorithm of Erwig and Hagen to calculate G in each vertex v nearest facility point f and apart from d (v, f)；

Two end points v of e are calculated respectively_lAnd v_rAttraction set A (v_l) and A (v_r), wherein, give a vertex v, A V () is the set of all client point c and respective distances d (c, v) that can be attracted to comprising v；

According to the A (v for having calculated_l) and A (v_r) calculate e local optimum positions I and corresponding financial value m.

Preferably, a known vertex v, A (v) is obtained as follows：

Initialization A (v) is empty set；

All summits in G are traveled through with dijkstra's algorithm apart from ascending order according to v；

For the vertex v ' that each is traversed, a (v ') is made to be distances of the v ' to its nearest facility point f, if d (v, V ')≤a (v '), and v ' is client's point, then will be<v′,d(v′,v)>Vertex v is added to attract after set A (v)；If d (v,v′)>A (v '), then ignore all sides with v ' as end points.

Preferably, according to the A (v for having calculated_l) and A (v_r) calculate e local optimum positions I and corresponding income The step of value m, includes：

Calculate the financial value of two end points of e；

If the financial value of two end points is different, that larger end points of financial value is returned as the local optimum position of e I is put, the larger corresponding financial value m as e in two financial values；Otherwise, using the two equal financial values as e correspondence Financial value m, and investigate the financial value at the midpoint of e, if less than end points financial value, using two end points as e local optimum Position I, if the financial value at the midpoint of e is equal with the financial value of two end points, using whole piece side e all as local optimum positions I。

Step S3, according to the renewal p of dynamic monitoring at any time that facility point set F in road network or client's point set C occur.

Preferably, step S3 includes：

Included the step of at any time dynamic monitors p according to the renewal that facility point set F in road network or client's point set C occur：

The renewal of facility point and client's point in road network can be attributed to one client's point of increase（AddC(c)）, reduce one Client's point DelC (c), increases facility point AddF (f), reduces by facility point DelF (f) totally four kinds of basic operation；

When one updates operation arrives, the set for attracting distance to be updated affected client's point is calculated first V_cIf operation is AddC (c) or DelC (c), V_c={c}；If operation is AddF (f) or DelF (f), V_c={c|<c,d (c,v)>∈A(f)}；

For each client point c ∈ V_c, the attraction before client's point is found out apart from a⁰C () and new attraction are apart from a' (c), and set up two setWith

For each client point c ∈ V_c, according to a⁰(c), a'(c),Come update every a line e local most Best placement I and corresponding financial value m, the local optimum positions and corresponding financial value before order renewal are respectively I₀And m₀；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as minimum range and position p。

Preferably, the local optimum positions and corresponding financial value before known renewal are respectively I₀And m₀, according to a⁰(c), A'(c),The step of come the local optimum positions I and corresponding financial value m that update every a line e, includes：

Set up a vertex set

For each vertex v in S：IfAndThen set m (v)=m (v)- w(c)(a⁰(c)-d(v,c))；IfAndThen set m (v)=m (v)+w (c) (a ' (c)-d(v,c))；IfWithAll set up, then set m (v)=m (v)+w (c) (a ' (c)-a⁰(c))；Wherein m (v) represents the financial value of vertex v；

For every a line e, if at least one changed in the financial value of two end points of e：

Read e two end points update after financial value, if the financial value of two end points is different, return financial value compared with Local optimum positions I, in two financial values larger corresponding financial value m as e of that the big end points as e；Otherwise, will The two equal financial values and investigate the financial value at the midpoint of e as the corresponding financial value m of e, if than end points financial value It is little, then using two end points as e local optimum positions I, if the financial value phase of the financial value at the midpoint of e and two end points Deng then using whole piece side e all as local optimum positions I.

Embodiment two

The present invention also provides the dynamic monitoring system of another kind of inquiry minimum range and position, including：

Definition module, for giving the set C of the client's point and set F of a facility point, and a candidate bit Set P is put, minimum range and position areWhereinWeighting for client point c is inhaled Draw distance, w (c) is the weight of client point c, if client point c and facility point f in road network apart from d (c, f) be c and F In point minimum, then define the attraction person that f is c, c attracted by f, a (c)=d (c, f) for c attraction distance；

Acquisition module, for obtaining p according to facility point set F initial in road network and client's point set C;

Update module, for the renewal dynamic monitoring at any time occurred according to facility point set F in road network or client's point set C p。

Further, in said system, the acquisition module is used for：

By the Connected undigraph G to expression road network^o=(V^o,E^o) all of facility point f and client point c are inserted by E^oIn When being divided into new, for each point ρ ∈ C ∪ F, first consider the side e ∈ E that ρ is located^o, two end points for making e are v_lWith v_r, it is then two parts i.e. from v by e point_lTo ρ and from ρ to v_r, so that ρ becomes a new summit of Connected undigraph, add institute Some new summits are generating a new Connected undigraph G=(V, E), and V=V^o∪C∪F；

For every a line e ∈ E_cInitialization calculates its local optimum positions I and corresponding financial value m, wherein, E_cBe comprising In location candidate set P side a little set, the financial value of certain position σ is Local optimum positions I is all point sets with maximum return value on the e of side；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as maximum contention power position p。

Further, in said system, the acquisition module is used for：

By the algorithm of Erwig and Hagen to calculate G in each vertex v nearest facility point f and apart from d (v, f)；

Two end points v of e are calculated respectively_lAnd v_rAttraction set A (v_l) and A (v_r), wherein, give a vertex v, A V () is the set of all client point c and respective distances d (c, v) that can be attracted to comprising v；

According to the A (v for having calculated_l) and A (v_r) calculate e local optimum positions I and corresponding financial value m.

Further, in said system, the acquisition module is used for：

Initialization A (v) is empty set；

All summits in G are traveled through with dijkstra's algorithm apart from ascending order according to v；

For the vertex v ' that each is traversed, a (v ') is made to be distances of the v ' to its nearest facility point f, if d (v, V ')≤a (v '), and v ' is client's point, then will be<v′,d(v′,v)>Vertex v is added to attract after set A (v)；If d (v,v′)>A (v '), then ignore all sides with v ' as end points.

Further, in said system, the acquisition module is used for：

Calculate the financial value of two end points of e；

If the financial value of two end points is different, that larger end points of financial value is returned as the local optimum position of e I is put, the larger corresponding financial value m as e in two financial values；Otherwise, using the two equal financial values as e correspondence Financial value m, and investigate the financial value at the midpoint of e, if less than end points financial value, using two end points as e local optimum Position I, if the financial value at the midpoint of e is equal with the financial value of two end points, using whole piece side e all as local optimum positions I。

Further, in said system, the update module is used for：

The renewal of facility point and client's point in road network can be attributed to one client's point of increase（AddC(c)）, reduce one Client's point DelC (c), increases facility point AddF (f), reduces by facility point DelF (f) totally four kinds of basic operation；

When one updates operation arrives, the set for attracting distance to be updated affected client's point is calculated first V_cIf operation is AddC (c) or DelC (c), V_c={c}；If operation is AddF (f) or DelF (f), V_c={c|<c,d (c,v)>∈A(f)}；

For each client point c ∈ V_c, the attraction before client's point is found out apart from a⁰C () and new attraction are apart from a' (c), and set up two setWith

For each client point c ∈ V_c, according to a⁰(c), a'(c),Come update every a line e local most Best placement I and corresponding financial value m, the local optimum positions and corresponding financial value before order renewal are respectively I₀And m₀；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as minimum range and position p。

Further, in said system, it is known that the local optimum positions and corresponding financial value before renewal are respectively I₀And m₀, the update module is used for：

Set up a vertex set

For each vertex v in S：IfAndThen set m (v)=m (v)- w(c)(a⁰(c)-d(v,c))；IfAndThen set m (v)=m (v)+w (c) (a ' (c)-d(v,c))；IfWithAll set up, then set m (v)=m (v)+w (c) (a ' (c)-a⁰(c))；Wherein m (v) represents the financial value of vertex v；

For every a line e, if at least one changed in the financial value of two end points of e：

Read e two end points update after financial value, if the financial value of two end points is different, return financial value compared with Local optimum positions I, in two financial values larger corresponding financial value m as e of that the big end points as e；Otherwise, will The two equal financial values and investigate the financial value at the midpoint of e as the corresponding financial value m of e, if than end points financial value It is little, then using two end points as e local optimum positions I, if the financial value phase of the financial value at the midpoint of e and two end points Deng then using whole piece side e all as local optimum positions I.

Other detailed contents of embodiment two specifically can be found in embodiment one, will not be described here.

The present invention is by giving the set C of the client's point and set F of a facility point, and a position candidate collection P is closed, minimum range and position areWhereinFor client point c weighting attract away from From, w (c) is the weight of client point c, if client point c and facility point f in road network apart from d (c, f) be in c and F The minimum of point, then define the attraction person that f is c, and c is attracted by f, and a (c)=d (c, f) is the attraction distance of c；According to first in road network Facility point set F of beginning and client's point set C obtain p;Occurred more according to facility point set F in road network or client's point set C The new monitoring p of dynamic at any time, can quickly and dynamically inquire about minimum range and position.

Each embodiment is described by the way of progressive in this specification, and what each embodiment was stressed is and other The difference of embodiment, between each embodiment identical similar portion mutually referring to.For system disclosed in embodiment For, due to corresponding to the method disclosed in Example, so description is fairly simple, related part is referring to method part illustration .

Professional further appreciates that, with reference to the unit of each example of the embodiments described herein description And algorithm steps, can with electronic hardware, computer software or the two be implemented in combination in, in order to clearly demonstrate hardware and The interchangeability of software, according to function has generally described the composition and step of each example in the above description.These Function is performed with hardware or software mode actually, depending on the application-specific and design constraint of technical scheme.Specialty Technical staff can use different methods to realize described function to each specific application, but this realization should not Think beyond the scope of this invention.

Obviously, those skilled in the art can carry out the spirit of various changes and modification without deviating from the present invention to invention And scope.So, if these modifications of the present invention and modification belong to the claims in the present invention and its equivalent technologies scope it Interior, then the present invention is also intended to including including these changes and modification.

Claims (12)

1. it is a kind of inquiry minimum range and position dynamic monitoring and controlling method, it is characterised in that include：

Give the set C of the client's point and set F of a facility point, an and location candidate set P, minimum range with Position isWhereinWeighting for client point c attracts distance, and w (c) is client The weight of point c, if client point c and facility point f in road network be apart from d (c, f) point in c and F minimum, then The attraction person that f is c is defined, c is attracted by f, a (c)=d (c, f) is the attraction distance of c；

P is obtained according to facility point set F initial in road network and client's point set C；

According to the renewal p of dynamic monitoring at any time that facility point set F in road network or client's point set C occur；

Wherein, the renewal for being occurred according to facility point set F in road network or client's point set C includes the step of at any time dynamic monitors p：

The renewal of facility point and client's point in road network can be attributed to one client's point AddC (c) of increase, reduce by client's point DelC (c), increases facility point AddF (f), reduces by facility point DelF (f) totally four kinds of basic operation；

When one updates operation arrives, the set V for attracting distance to be updated affected client's point is calculated first_c, such as Fruit operation is AddC (c) or DelC (c), then V_c={ c }；If operation is AddF (f) or DelF (f), V_c=c |<c,d(c, v)>∈A(f)}；

For each client point c ∈ V_c, the attraction before client's point is found out apart from a⁰C () and new attraction are apart from a'(c), And set up two setWith

For each client point c ∈ V_c, according to a⁰(c), a'(c),To update the local optimum position of every a line e I and corresponding financial value m is put, the local optimum positions and corresponding financial value before order renewal are respectively I₀And m₀；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as minimum range and position p.

2. the dynamic monitoring and controlling method of minimum range and position is inquired about as claimed in claim 1, it is characterised in that according in road network Initial facility point set F and client's point set C includes the step of obtaining p：

By the Connected undigraph G to expression road network^o=(V^o,E^o) all of facility point f and client point c are inserted by E^oIn side New side is divided into, for each point ρ ∈ C ∪ F, the side e ∈ E that ρ is located first is considered^o, two end points for making e are v_lAnd v_r, so It is afterwards two parts i.e. from v by e point_lTo ρ and from ρ to v_r, so that ρ becomes a new summit of Connected undigraph, add all of new Summit is generating a new Connected undigraph G=(V, E), and V=V^o∪C∪F；

For every a line e ∈ E_cInitialization calculates its local optimum positions I and corresponding financial value m, wherein, E_cIt is comprising time Select in location sets P side a little set, the financial value of certain position σ is Local optimum positions I is all point sets with maximum return value on the e of side；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as maximum contention power position p.

3. the dynamic monitoring and controlling method of minimum range and position is inquired about as claimed in claim 2, it is characterised in that for each Side e ∈ E_cThe step of initialization calculates its local optimum positions I and corresponding financial value m includes：

By the algorithm of Erwig and Hagen to calculate G in each vertex v nearest facility point f and apart from d (v, f)；

Two end points v of e are calculated respectively_lAnd v_rAttraction set A (v_l) and A (v_r), wherein, a vertex v is given, A (v) is bag The set of all client point c and respective distances d (c, v) that can be attracted to containing v；

According to the A (v for having calculated_l) and A (v_r) calculate e local optimum positions I and corresponding financial value m.

4. the dynamic monitoring and controlling method of minimum range and position is inquired about as claimed in claim 3, it is characterised in that a known top Point v, A (v) are obtained as follows：

Initialization A (v) is empty set；

All summits in G are traveled through with dijkstra's algorithm apart from ascending order according to v；

For the vertex v ' that each is traversed, a (v ') is made to be distances of the v ' to its nearest facility point f, if d (v, v ')≤ A (v '), and v ' is client's point, then will be<v′,d(v′,v)>Vertex v is added to attract after set A (v)；If d (v, v′)>A (v '), then ignore all sides with v ' as end points.

5. the dynamic monitoring and controlling method of inquiry minimum range as claimed in claim 4 and position, it is characterised in that according to having counted A (the v for calculating_l) and A (v_r) calculate e local optimum positions I and corresponding financial value m the step of include：

Calculate the financial value of two end points of e；

If the financial value of two end points is different, that larger end points of financial value is returned as the local optimum positions I of e, The larger corresponding financial value m as e in two financial values；Otherwise, using the two equal financial values as e corresponding income Value m, and investigate the financial value at the midpoint of e, if less than end points financial value, using two end points as e local optimum positions I, if the financial value at the midpoint of e is equal with the financial value of two end points, using whole piece side e all as local optimum positions I.

6. the dynamic monitoring and controlling method of minimum range and position is inquired about as claimed in claim 5, it is characterised in that before known renewal Local optimum positions and corresponding financial value be respectively I₀And m₀, according to a⁰(c), a'(c),It is each to update The step of local optimum positions I and corresponding financial value m of bar side e, includes：

Set up a vertex set

For each vertex v in S：IfAndThen set m (v)=m (v)-w (c)(a⁰(c)-d(v,c))；IfAndThen set m (v)=m (v)+w (c) (a ' (c)-d(v,c))；IfWithAll set up, then set m (v)=m (v)+w (c) (a ' (c)-a⁰(c))；Wherein m (v) represents the financial value of vertex v；

For every a line e, if at least one changed in the financial value of two end points of e：

The financial value after two end points renewal of e is read, if the financial value of two end points is different, financial value is returned larger Local optimum positions I, in two financial values larger corresponding financial value m as e of that end points as e；Otherwise, by this two Individual equal financial value and investigates the financial value at the midpoint of e as the corresponding financial value m of e, if less than end points financial value, Using two end points as e local optimum positions I, if the financial value at the midpoint of e is equal with the financial value of two end points, Whole piece side e is as local optimum positions I.

7. it is a kind of inquiry minimum range and position dynamic monitoring system, it is characterised in that include：

Definition module, for giving the set C of the client's point and set F of a facility point, and a position candidate collection P is closed, minimum range and position areWhereinFor client point c weighting attract away from From, w (c) is the weight of client point c, if client point c and facility point f in road network apart from d (c, f) be in c and F The minimum of point, then define the attraction person that f is c, and c is attracted by f, and a (c)=d (c, f) is the attraction distance of c；

Acquisition module, for obtaining p according to facility point set F initial in road network and client's point set C；

Update module, for the renewal p of dynamic monitoring at any time occurred according to facility point set F in road network or client's point set C；

Wherein, the update module specifically for：

The renewal of facility point and client's point in road network can be attributed to one client's point AddC (c) of increase, reduce by client's point DelC (c), increases facility point AddF (f), reduces by facility point DelF (f) totally four kinds of basic operation；

When one updates operation arrives, the set V for attracting distance to be updated affected client's point is calculated first_c, such as Fruit operation is AddC (c) or DelC (c), then V_c={ c }；If operation is AddF (f) or DelF (f), V_c=c |<c,d(c, v)>∈A(f)}；

For each client point c ∈ V_c, the attraction before client's point is found out apart from a⁰C () and new attraction are apart from a'(c), And set up two setWith

For each client point c ∈ V_c, according to a⁰(c), a'(c),To update the local optimum position of every a line e I and corresponding financial value m is put, the local optimum positions and corresponding financial value before order renewal are respectively I₀And m₀；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as minimum range and position p.

8. the dynamic monitoring system of minimum range and position is inquired about as claimed in claim 7, it is characterised in that the acquisition mould Block is used for：

By the Connected undigraph G to expression road network^o=(V^o,E^o) all of facility point f and client point c are inserted by E^oIn side New side is divided into, for each point ρ ∈ C ∪ F, the side e ∈ E that ρ is located first is considered^o, two end points for making e are v_lAnd v_r, so It is afterwards two parts i.e. from v by e point_lTo ρ and from ρ to v_r, so that ρ becomes a new summit of Connected undigraph, add all of new Summit is generating a new Connected undigraph G=(V, E), and V=V^o∪C∪F；

For every a line e ∈ E_cInitialization calculates its local optimum positions I and corresponding financial value m, wherein, E_cIt is comprising time Select in location sets P side a little set, the financial value of certain position σ is Local optimum positions I is all point sets with maximum return value on the e of side；

According to the local optimum positions I on all sides select corresponding financial value m it is maximum as maximum contention power position p.

9. the dynamic monitoring system of minimum range and position is inquired about as claimed in claim 8, it is characterised in that the acquisition mould Block is used for：

By the algorithm of Erwig and Hagen to calculate G in each vertex v nearest facility point f and apart from d (v, f)；

Two end points v of e are calculated respectively_lAnd v_rAttraction set A (v_l) and A (v_r), wherein, a vertex v is given, A (v) is bag The set of all client point c and respective distances d (c, v) that can be attracted to containing v；

According to the A (v for having calculated_l) and A (v_r) calculate e local optimum positions I and corresponding financial value m.

10. the dynamic monitoring system of minimum range and position is inquired about as claimed in claim 9, it is characterised in that the acquisition Module is used for：

Initialization A (v) is empty set；

All summits in G are traveled through with dijkstra's algorithm apart from ascending order according to v；

For the vertex v ' that each is traversed, a (v ') is made to be distances of the v ' to its nearest facility point f, if d (v, v ')≤ A (v '), and v ' is client's point, then will be<v′,d(v′,v)>Vertex v is added to attract after set A (v)；If d (v, v′)>A (v '), then ignore all sides with v ' as end points.

11. inquiry minimum ranges as claimed in claim 10 and the dynamic monitoring system of position, it is characterised in that the acquisition Module is used for：

Calculate the financial value of two end points of e；

If the financial value of two end points is different, that larger end points of financial value is returned as the local optimum positions I of e, The larger corresponding financial value m as e in two financial values；Otherwise, using the two equal financial values as e corresponding income Value m, and investigate the financial value at the midpoint of e, if less than end points financial value, using two end points as e local optimum positions I, if the financial value at the midpoint of e is equal with the financial value of two end points, using whole piece side e all as local optimum positions I.

12. inquiry minimum ranges as claimed in claim 11 and the dynamic monitoring system of position, it is characterised in that known renewal Front local optimum positions and corresponding financial value are respectively I₀And m₀, the update module is used for：

Set up a vertex set

For each vertex v in S：IfAndThen set m (v)=m (v)-w (c)(a⁰(c)-d(v,c))；IfAndThen set m (v)=m (v)+w (c) (a ' (c)-d(v,c))；IfWithAll set up, then set m (v)=m (v)+w (c) (a ' (c)-a⁰(c))；Wherein m (v) represents the financial value of vertex v；

For every a line e, if at least one changed in the financial value of two end points of e：

The financial value after two end points renewal of e is read, if the financial value of two end points is different, financial value is returned larger Local optimum positions I, in two financial values larger corresponding financial value m as e of that end points as e；Otherwise, by this two Individual equal financial value and investigates the financial value at the midpoint of e as the corresponding financial value m of e, if less than end points financial value, Using two end points as e local optimum positions I, if the financial value at the midpoint of e is equal with the financial value of two end points, Whole piece side e is as local optimum positions I.