CN106384161A - Optimization algorithm for regional division of spaceflight tour-inspection plan - Google Patents
Optimization algorithm for regional division of spaceflight tour-inspection plan Download PDFInfo
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Abstract
The invention discloses an optimization algorithm for regional division of a spaceflight tour-inspection plan. The algorithm comprises the steps that (1) the tour-inspection plane serves as input data, a correspondence set between to-be-inspected plans and a tour inspection route Li is established; (2) according to the distance from each temporary rising and landing point to the corresponding tour inspection route as well as the online rate, tour inspection projects are distributed to the temporary rising and landing points; (3) according to the capacity of a tour inspection region and the maximal regional clustering distance, the temporary rising and landing points are clustered into a region; (4) according to constraint of an altitude plan, plans which are not concluded to the temporary rising and landing points are distributed in a forced manner; and (5) and tour-inspection projects which are not concluded still are recorded, and serves as data which is returned finally. Compared with the prior art, a tour inspection region can be formed according to the tour inspection planes in each year, an optimal tour inspection work plan can be provided, and tour inspection can be most efficient.
Description
Technical field
The present invention relates to space flight route optimization algorithm, more particularly to one kind make an inspection tour circuit and interim landing point for space flight
Cluster optimized algorithm.
Background technology
Related art of the present invention includes optimized algorithm and space flight visit program region division optimized algorithm.
First, always researcher is devoted to one of research, the hot issue explored and solve to optimized algorithm for many years.When
The solution of front main flow mainly has ant group algorithm and dynamic optimization.Ant group algorithm is the mould of ant communities food collection process
Intend, be to be proposed in his thesis for the doctorate in 1992 by Marco Dorigo, its Inspiration Sources is in Formica fusca in search of food mistake
The behavior in path is found in journey.But, it optimizes performance and is largely dependent upon parameter setting, is affected relatively by initial value
Greatly.Dynamic optimization be also be operational research a branch, be to solve for the optimized mathematical method of decision making process.The 1950's
Just U.S. mathematician R.E.Bellman et al. when studying the optimization problem of multistage decision process it is proposed that famous optimum
Change principle.Ultimate principle be by PROBLEM DECOMPOSITION to be solved be several subproblems (stage), in order solve sub-stage, previous
The solution of subproblem, is that the solution of a rear subproblem provides useful information.
2nd, space flight visit program region division optimized algorithm achieves and makes an inspection tour circuit distribution spy according to transmission line of electricity helicopter
Point it is considered to each side factor such as transaction capabilities maked an inspection tour of helicopter, in conjunction with the main feature making an inspection tour region, carry out Rational Classification and
Optimize, provide optimum patrols and examines production plan so that making an inspection tour efficiency optimization.
Content of the invention
The defect being existed based on prior art, the present invention proposes a kind of optimization for space flight visit program region division
Algorithm, space flight visit program region division optimized algorithm achieves makes an inspection tour circuit characteristic distributions according to transmission line of electricity helicopter, examines
Consider each side factors such as the transaction capabilities that helicopter is maked an inspection tour, in conjunction with the main feature making an inspection tour region, carry out Rational Classification and optimization.
The invention discloses a kind of optimized algorithm for space flight visit program region division, the method includes following step
Suddenly：
Step 1, using visit program as input data, set up and treat visit program and patrol route LiSet of correspondences
Close；
Step 2, the distance making an inspection tour circuit according to corresponding to interim landing point is with plan and this two constraint bars of online rate
Part, will make an inspection tour allocation of items to interim landing point；；
Step 3, according to making an inspection tour field capacity and this two constraintss of region clustering ultimate range, by interim landing point
Cluster as region；
Step 4, the constraints according to height above sea level plan, force distribution not conclude the list of schedules of interim landing point；
The tour project that step 5, record still can not be concluded, as a part of data finally returning to.
Described step 2 also specifically includes following process：
Calculate the distance of interim landing point and plan corresponding tour circuit, and select to record interim landing point to plan institute
The corresponding minimum distance dis_pa making an inspection tour circuit；Calculate from interim landing point corresponding to plan make an inspection tour that circuit maked an inspection tour
Line rate, online rate formula is as follows：
Per_on=t_on/t_on+t_off
T_on=l_len/v_on
T_off=dis_pa+dis_st+dis_pen
Wherein, per_on is online rate, and t_on is the time of the online flight of aircraft when making an inspection tour this circuit, and t_off is winged
The time of the offline flight of machine；
For each interim landing point, minima min_dis_pa in selection minimum distance and the maximum of online rate
max_per_on；
If meeting the distance restraint that min_dis_pa is less than or equal to be intended to conclude interim landing point
LandingPointDistance, then be intended to conclude on corresponding interim landing point；If be unsatisfactory for, then judge to limit bar
Part, if maximum online rate max_per_on is more than or equal to the maximum online rate (80%) of system regulation, is intended to conclusion and arrives
On corresponding interim landing point；
For experience above step still without the plan concluding interim landing point, put into and do not conclude interim landing point
List of schedules.
Described step 4 also specifically includes following process：
Interim landing point is divided into two classes, that is, the first kind is interim landing point set S of the plan containing High aititudehigh,
Equations of The Second Kind is interim landing point set S containing only low altitude area planlow；
The all of interim landing point set including High aititude plan is clustered, that is, to set ShighClustered；
Including High aititude interim landing point cluster complete after, High aititude region starts to receive the interim landing of low altitude area
With the distance of interim landing point recently whether whether point, according to, and exceed field capacity and go to judge that can this plan add
The closely interim corresponding region of landing point；
To remaining low altitude area, interim landing point clusters；
After the completion of cluster, return to all regions generating.
Compared with prior art, the present invention is directed to space flight and makes an inspection tour the characteristic distributions of task and the factors of reality, shape
Become model the region division completing to the task of tour, can be formed for each annual visit program and make an inspection tour region., be given
Optimum patrols and examines production plan so that making an inspection tour efficiency optimization.
Brief description
Fig. 1 is a kind of optimized algorithm flow chart for space flight visit program region division of the present invention；
Fig. 2 is that the online rate of aircraft calculates schematic diagram；
Fig. 3 is that a kind of result of optimized algorithm running example for space flight visit program region division of the present invention is illustrated
Figure.
Specific embodiment
Present invention whole year is treated that visit program is sorted out, and whole year treats the classification of visit program mainly with interim landing point as core
The heart, whole year treats that visit program incorporates interim landing point into according to set constraint, and this process record is unsatisfactory for the tour of set constraint
Plan, completing whole year incorporates into after interim landing point after visit program, and interim landing point saves but also excellent former according to constraint and not only
Then clustered, ultimately generated the region that cluster is formed.After the completion of region division, will before unappropriated visit program according to
Excellent principle arrangement, in region, is less than the total capacity in each region, the plan that cannot arrange under this process record, this meter simultaneously
Draw and cannot arrange.After the completion of, it is equipped with aircraft according to whether there being High aititude plan in each region.
As shown in figure 1, a kind of optimized algorithm flow chart for space flight visit program region division of the present invention, each step
It is described in detail as follows：
Step 1, traversal plan (constituting each needing to arrange for of task of a tour project), being intended to numbering is i, if
Determine and plan TiRelated parameter includes making an inspection tour circuit Li, province Pi, for each plan in list of schedules, all carry out pre- place
Reason, pretreatment includes following process：
(1-1) plan and L are set upiCorrespondence set Ii, it is expressed as：
Ii={ Ts,Tj...|s,j...∈X}
Wherein, X represents all patrol route LiSet, s here, j represent respectively any two inspection circuit, Ts、TjPoint
Not Wei certain two tour the corresponding plans of circuit, this set establish plan and affiliated tour circuit LiBetween index, record
This all identical in the works tour circuit corresponding task creation relation simultaneously preserves；
(1-2) plan and P are set upiCorrespondence set Ni, it is expressed as：
Ni={ Ts,Tj...|s,j...∈Y}
Wherein, Y represents all provinces numbering PiSet, s here, j represent any two province, T respectivelys、TjAppoint respectively
The corresponding plan in two provinces of meaning, this set establishes plan and affiliated province PiBetween index, record this all plan
In the corresponding task creation relation in identical province preserving；
(1-3) traversal history data, based on historical data, sets up and LiSet of relationship O of related historical datai：
Oi={ Ts,Tj...|s,j...∈Z}
Wherein, Z is the set in 1 to December, and s here, j represent the month that any two once occurred in history respectively,
Ts、TjThis set of corresponding historic task of any two province establishes the institute making an inspection tour circuit and this circuit in historical data respectively
There is the index between the arrangement time, every circuit may correspond to multiple times；
Step 2, according to the constraint such as distance and online rate, will allocation of items be maked an inspection tour on interim landing point；This step
Desired data includes list of schedules, the interim landing point information of initial input, does not conclude the list of schedules of interim landing point (temporarily
When for empty list), be intended to conclude the distance restraint landingPointDistance of interim landing point, finally return to by returning
The interim landing point set received the interim landing point of list of schedules and constitute.This step specifically includes following process：
(2-1) as shown in Fig. 2 calculating the distance of interim landing point and plan corresponding tour circuit, and record is selected to face
When landing point to the corresponding minimum distance dis_pa making an inspection tour circuit of plan；Calculate from the corresponding tour to plan of interim landing point
The online rate that circuit is maked an inspection tour, online rate formula is as follows：
Per_on=t_on/t_on+t_off
T_on=l_len/v_on
T_off=dis_pa+dis_st+dis_pen
Wherein, per_on is online rate, and t_on is the time of the online flight of aircraft when making an inspection tour this circuit, and t_off is winged
The time of the offline flight of machine, l_len is the length of this tour circuit, and dis_st is apart from the nearest shaft tower of interim landing point and to be somebody's turn to do
Make an inspection tour the distance that circuit initiates between shaft tower, dis_pen is the distance between interim landing point and this tour line termination shaft tower, v_on
For the speed of the online flight of aircraft, generally take 20km/h, v_off is the speed of the offline flight of aircraft；
(2-2), for each interim landing point, select minimum distance in minima min_dis_pa and online rate
Big value max_per_on；
(2-3), first constraints restriction is carried out to minimum minimum distance min_dis_pa, if meeting min_dis_pa
Less than or equal to being intended to conclude the distance restraint landingPointDistance of interim landing point, then it is intended to conclude to right
On the interim landing point answered；If be unsatisfactory for, then judge restrictive condition, if maximum online rate max_per_on is more than or equal to being
The maximum online rate (80%) of system regulation, then be intended to conclude on corresponding interim landing point；
(2-4), for experience above three steps still without the plan concluding interim landing point, put into do not conclude interim
The list of schedules of landing point；
Step 3, it is intended to after division is fitted on interim landing point, the interim landing point set that step 2 is generated is according to flat
All field capacity perCapacity, high low altitude area demarcation line highLimit, region clustering ultimate range, and during this not
Meet the constraint and unallocated successful plan, interim landing point are clustered, forming region, finally produce one group of zone list, area
In domain the ultimate range constraint of cluster refer to not cluster interim landing point from first interim landing point adding this region away from
From less than this ultimate range；
The tour project (not concluding the list of schedules of interim landing point) that step 4, pressure distribution are not concluded, region is basic
After division completes, need to by cause be unsatisfactory for the unappropriated project of interim landing point distance restraint and force distribution to facing recently
When the corresponding region of landing point, must be fulfilled for simultaneously less than each region average year make an inspection tour capacity.
According to physical constraint, the high aircraft of peak of flight can make an inspection tour High aititude plan and low altitude area plan, and flies
The low aircraft in row ceiling can only make an inspection tour low altitude area plan, for all plans for High aititude, selects there is high priority, because
This this step needs first High aititude project to be processed.Step is as follows：
(4-1), whether include High aititude plan according in interim landing point, interim landing point is divided into two classes, the first kind
It is interim landing point set S of the plan containing High aititudehigh, Equations of The Second Kind is the interim landing point set containing only low altitude area plan
Close Slow.
Shigh=x | x.ceilingUp >=highLimit, x ∈ P }
Slow=x | x.ceilingUp ＜ highLimit, x ∈ P }
Wherein, P represents the summation being needed the project of being maked an inspection tour being arranged into interim landing point, and highLimit represents height sea
Pull out demarcation line；
(4-2), all of interim landing point set including High aititude plan is clustered, that is, to set ShighCarry out
Cluster.Clustering taproot algorithm is：
1) a, newly-built region A, from ShighOne interim landing point of middle taking-up is designated as LINi, add in the A of region；
2), remember LINiFor ShighIn i-th interim landing point, calculate other interim landing points and this interim landing point away from
From d, generate a set：
D=d | d=distance (Li, L1), i ∈ Z, i≤size (Shigh), i ≠ 1 }
3), from set D, select minimum range, judge that can this be added to region A apart from corresponding interim landing point
Interior, if region total capacity is not less than adding to the A of region；Total capacity exceedes, and does not operate；
4), from set D, remove minimum range, if D collection is combined into sky, carry out next step；If not being empty, repeat
Carry out step 2) to step 4)；
(4-3), after, the interim landing point cluster of inclusion High aititude completes, High aititude region starts to receive low altitude area interim
Landing point, according to distance recently whether core constraint is still distance, and whether exceed field capacity and go to judge this plan energy
The no addition interim corresponding region of landing point recently；Concrete steps are essentially identical with (4-2)；
(4-4), after the completion of, low altitude area interim landing point is received in High aititude plan, may also have part low altitude area and rise temporarily
Fall point is remaining, and in the same manner, according to step (4-1), to remaining low altitude area, interim landing point clusters, then execution and step (4-
2) identical is processed；
(4-5) all regions of generation are returned to after the completion of, clustering.
The project that still can not insert is recorded, as the part finally returning to after the completion of step 5, this step.
General plan length in Fig. 1, refers to the summation of the tour line length in all visit programs.
As shown in figure 3, the data that space flight is provided as the present invention a kind of for space flight visit program region division
The |input paramete of optimized algorithm, is successfully divided into 4 regions：As schemed, wherein first region includes 1 temporarily to concrete outcome
Landing point, this interim landing point includes 87 plans.
Claims (3)
1. a kind of optimized algorithm for space flight visit program region division is it is characterised in that the method comprises the following steps：
Step (1), using visit program as input data, set up and treat visit program and patrol route LiCorrespondence set；
Step (2), according to interim landing point with plan the distance of corresponding tour circuit and this two constraintss of online rate,
Visit program is assigned to interim landing point；
Step (3), according to making an inspection tour field capacity and this two constraintss of region clustering ultimate range, interim landing point is gathered
Class is region；
Step (4), the constraints according to height above sea level plan, force distribution not conclude the list of schedules of interim landing point；
The visit program that step (5), record still can not be concluded, as a part of data finally returning to.
2. as claimed in claim 1 a kind of optimized algorithm for space flight visit program region division it is characterised in that described
Step (2) also specifically includes following process：
Calculate interim landing point and the corresponding distance making an inspection tour circuit of plan, and select to record interim landing point to corresponding to plan
Make an inspection tour the minimum distance dis_pa of circuit；Calculate from interim landing point corresponding to plan make an inspection tour that circuit maked an inspection tour online
Rate, online rate formula is as follows：
Per_on=t_on/t_on+t_off
T_on=l_len/v_on
T_off=dis_pa+dis_st+dis_pen
Wherein, per_on is online rate, and t_on is the time of the online flight of aircraft when making an inspection tour this circuit, t_off be aircraft from
The time of line flight；
For each interim landing point, minima min_dis_pa in selection minimum distance and the maximum max_ of online rate
per_on；
If meeting the distance restraint that min_dis_pa is less than or equal to be intended to conclude interim landing point
LandingPointDistance, then be intended to conclude on corresponding interim landing point；If be unsatisfactory for, then judge to limit bar
Part, if maximum online rate max_per_on is more than or equal to the maximum online rate (80%) of system regulation, is intended to conclusion and arrives
On corresponding interim landing point；
For experience above step still without the plan concluding interim landing point, put into the meter not concluding interim landing point
Draw list.
3. as claimed in claim 1 a kind of optimized algorithm for space flight visit program region division it is characterised in that described
Step (4) also specifically includes following process：
Interim landing point is divided into two classes, that is, the first kind is interim landing point set S of the plan containing High aititudehigh, Equations of The Second Kind
For containing only interim landing point set S of low altitude area planlow；
The all of interim landing point set including High aititude plan is clustered, that is, to set ShighClustered；
Including High aititude interim landing point cluster complete after, High aititude region starts to receive low altitude area interim landing point, root
According to the distance of interim landing point whether recently, and whether exceed field capacity go to judge that can this plan add interim recently
The corresponding region of landing point；
To remaining low altitude area, interim landing point clusters；
After the completion of cluster, return to all regions generating.
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| CN109508868A (en) * | 2018-10-22 | 2019-03-22 | 南京航空航天大学 | High efficiency smart air traffic region dividing system |
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