CN104573856A - Spacecraft resource constraint processing method based on time topological sorting - Google Patents
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Abstract
The invention relates to a spacecraft resource constraint processing method based on time topological sorting and belongs to the technical field of autonomous control on spacecraft. The method comprises steps as follows: firstly, performing topological sorting on actions in planning results according to execution time of the actions; then layering the actions in a resource constraint network according to changes of resource numbers by the actions, and processing each resource mutation to improve the resource number computing efficiency. The method is particularly applicable to resource management in autonomous planning of spacecraft tasks in deep-space exploration. According to the method, the resource constraint network is adopted to describe resource information in planning, the changes of the resource numbers when a spacecraft executes the actions along with time are acquired through analysis of changes of apexes and edges in the network, advantages of an augmenting path method and a pre-flow push method for the maximum flow problem are combined, topological sorting is performed on resource mutations according to execution time, and the resource number computing process is optimized; resource constraint in the planning results can be effectively processed, and the computing efficiency is significantly improved.
Description
Technical field
The present invention relates to a kind of spacecraft resource constraint disposal route based on time topological sorting, belong to the autonomous control technology field of spacecraft.
Background technology
The planning of spacecraft Task Autonomous is the gordian technique realizing spacecraft proprietary technology.Spacecraft is when performing space tasks, spaceborne autonomous management system is according to the oneself state of the space environment state perceived, spacecraft and the task object needing execution, task action sequence after autonomous generation current time, can realize the long-term autonomous operation in unmanned intervention situation.The problem that the planning of spacecraft Task Autonomous can overcome in survey of deep space that communications lag is large, resource constraint is complicated, running environment dynamic change etc. brings, improves independence and the reliability of spacecraft long-time running.On the star of spacecraft, resource (propellant, electric energy, storer etc.) is very limited, not only will consider the use amount of resource, also will consider the restriction relation between different resource simultaneously during planning spacecraft action.Multiple subsystems of spacecraft can produce the multiple actions simultaneously carried out, and concurrent activity causes change in resources situation more complicated.The gordian technique that effective resource constraint disposal route is the planning of spacecraft Task Autonomous is designed in planning.
In the resource constraint disposal route of the spacecraft mission planning developed, first technology [1] (based on world TT&C Resources combined dispatching [J] of ant group optimization-simulated annealing. aerospace journal, 2012,33 (1): 85-90.), have studied the resource scheduling in space flight measurement and control, for constrained optimization problem Modling model, and the method adopting ant colony optimization algorithm and simulated annealing to combine seeks optimum solution.But the method launches research for the TT&C event determined, cannot meet the demand processing Dynamic Uncertain event in survey of deep space.
In first technology [2] (see Muscettola N.Computing the envelope forstepwise-constant resource allocations [J] .Berlin, Germany:Principles andPractice ofConstraintPrograming, 2002.), analyze behavior aggregate and change impact on resource quantity in time, network flow model is adopted to describe the resource constraint in planning, by the maximum flow valuve of computational grid, obtain time dependent resource quantity.But adopt general network flow algorithm when solving resource, not in conjunction with the design feature of resource constraint network.
Summary of the invention
The present invention is directed to the design feature that current resource constraint disposal route does not utilize resource constraint network, the problems such as the dynamic response requirement of spacecraft cannot be met, propose a kind of spacecraft resource constraint disposal route based on time topological sorting, in the autonomous mission planning at spacecraft, calculate resource service condition on star.
This method, first according to the execution time of action, carries out topological sorting to the action in program results; Then change the situation of resource quantity according to action, layering is carried out in the action in resource constraint network, process the sudden change of each resource respectively, improve the efficiency of computational resource quantity process; Be specially adapted to space flight in survey of deep space and have a high regard for the resource management of being engaged in contexture by self.
Spacecraft resource constraint disposal route based on time topological sorting specifically comprises the steps:
Step one, the autonomous mission planning of spacecraft generates time-constrain, each resource constraint needed for action executing between action sequence, multiple action in tasks carrying process and execution time thereof, each action.Wherein, action sequence is expressed as A={a
1, a
2..., a
i..., a
n.A
ifor the action comprised in program results.Time-constrain between action is the time interval that every two actions occur.The resource constraint of action be each action executing of spacecraft start with at the end of change to resource quantity.
As action a
iwhen needing to use a kind of resource r, if the quantity q of resource r
ronly at action a
istart time
or finish time
change, the change of each resource quantity is described as first resource sudden change δ.According to action sequence, for resource on the star used needed for each, generate a resource catastrophe set respectively.
Step 2, according to the resource catastrophe set described in step one, with the execution time t of resource sudden change δ for criterion, carries out topological sorting to the resource sudden change in each resource catastrophe set and in chronological sequence order label, generates and have the resource constraint network G of hierarchy
r.G
rrepresent all resource constraints in action sequence.Concrete grammar is:
Step 2.1, according to the execution time of resource sudden change, is designated as 1 by the sequence number of point corresponding for the resource performed the earliest sudden change, then increases the sequence number of following resource catastrophe point according to time sequencing successively.While marking serial numbers, all resource catastrophe points are labeled as production catastrophe point v according to the change of resource quantity
piwith consumption catastrophe point v
cj.
Described production catastrophe point represents the resource sudden change resources of production of this some correspondence, adds system resource quantity.
Described consumption catastrophe point represents the resource sudden change consumption of natural resource of this some correspondence, decreases system resource quantity.
Step 2.2, carries out layered shaping to all resource catastrophe points, obtains G
r.G
rbe divided into four layers: source point σ, production sudden change layer V
p, consume sudden change layer V
c, meeting point τ.Produce sudden change layer V
peach point and source point σ between limit be production limit E
p, produce sudden change layer V
pwith consumption sudden change layer V
ceach point between limit be internal edges E
i, consume sudden change layer V
cpoint and meeting point τ between limit be and consume limit E
c.
Step 2.3, increases a flow value for every bar limit after layered shaping.Flow initial value is set to 0, and must not exceed the capacity on this limit in use.
Described capacity is the maximal value of flow on every bar limit.The capacity E on production limit
pbe set to the production catastrophe point v be connected with production limit
picorresponding production sudden change increases the numerical value of resource, consumes the capacity E on limit
cbe set to and the consumption catastrophe point v consuming limit and be connected
cjcorresponding consumption sudden change reduces the numerical value of resource,
Step 3, from source point σ to production sudden change layer V
pcarry out flow propelling.According to label order from small to large, select each production catastrophe point v successively
pi, and at production limit E
pi=(σ, v
pi) on from source point σ to production catastrophe point v
picarry out saturated propelling.When carrying out saturated propelling, by E
piflow value be set to E
picapacity.For v
pi, when the resource sudden change that sequence number is greater than i is production sudden change, end step three, performs step 4.
Step 4, from production sudden change layer V
pto consumption sudden change layer V
ccarry out flow propelling, then from consumption sudden change layer V
cflow propelling is carried out to meeting point τ.Concrete grammar is:
Step 4.1, according to label order from small to large, selects production catastrophe point v successively
pi;
Step 4.2, for a production catastrophe point v
pi, according to label order from small to large, select all labels to be greater than v
piconsumption catastrophe point v
cj(j > i), at internal edges E
i=(v
pi, v
cj) on from production catastrophe point v
pito consumption catastrophe point v
cjcarry out saturated propelling;
From production catastrophe point v
pito consumption catastrophe point v
cjcarry out saturated propelling to be specially: with selected production catastrophe point v
piproduction limit E
pi=(σ, v
pi) flow deduct the internal edges E with current selected
iflow, obtain E
piutilizable flow; Then by internal edges E
i=(v
pi, v
cj) flow value be set to E
piutilizable flow, and by production limit E
piflow value deduct E
piutilizable flow.
Step 4.3, to the consumption catastrophe point v completing saturated propelling in step 4.2
cj, at consumption limit E
c=(v
cj, τ) on carry out saturated propelling;
Described is consuming limit E
c=(v
cj, τ) on carry out saturated propelling and be specially: with consuming limit E
cj=(v
cj, τ) capacity deduct E
cpresent flow rate, can E be obtained
cutilizable flow; If E
cutilizable flow to be greater than in step 4.2 selected internal edges E
i=(v
pi, v
cj) flow, then by E
cflow add E
iflow, and by E
iflow set be 0; If E
cutilizable flow to be less than or equal in step 4.2 selected internal edges E
ij=(v
pi, v
cj) flow, then by E
cflow set be E
ccapacity, and by E
iflow deduct E
cutilizable flow.
Step 4.4, selects sequence number to be greater than v
cjthe next one consume catastrophe point, consumption limit on carry out saturated propelling; If oneself is greater than v at treated complete all sequence numbers
cjconsumption catastrophe point, then select sequence number be greater than v
pinext production catastrophe point, return step 4.2, until all production catastrophe points all complete through consuming sudden change layer V
cto the saturated propelling of meeting point τ.
Step 5, above-mentioned steps completes source point σ through the middle two-layer saturated propelling to meeting point τ.According to G
rin to be connected with meeting point τ all E
c=(v
c, τ) flow sum, obtain the maximum flow valuve F (G of network
r).Changes values according to following formula computational resource quantity:
Wherein, q
rt () represents the changes values in t resource quantity.According to the execution time of resource sudden change and the relation of current time t, the resource caused by action sequence A sudden change is divided into three parts: oneself undergos mutation
wait to undergo mutation
do not undergo mutation
oneself undergos mutation
comprise all resource sudden changes that oneself performs at moment t, to total changes values of resource quantity be
wait to undergo mutation
comprise all resource sudden changes performed at moment t, to total changes values of resource quantity be
do not undergo mutation
comprise all in the still unenforced resource sudden change of moment t, to total changes values of resource quantity be
value by calculate moment t time all resource changing value summations that oneself undergos mutation
obtain,
value by calculating moment t time resource constraint network maximum flow valuve F (G
r) obtain.
Thus obtain the changes values of spacecraft resource quantity in program results.
Beneficial effect
The spacecraft resource constraint disposal route based on time topological sorting given by the present invention, have that algorithm is simple, counting yield advantages of higher, complicated program results can be processed, and efficiently utilize the time factor in planning, be convenient to carry out rapid computations in reality performs.
The method adopts the resource information in the planning of resource constraint network description, by analyzing the change on summit and limit in network, obtain the change of resource quantity when spacecraft performs an action in time, based on the layering feature of resource constraint network, combine the augmenting path method of maximum flow problem and the advantage flowing propulsion method in advance, by carrying out topological sorting according to the execution time to resource sudden change, optimize the process of computational resource quantity.The method effectively can process the resource constraint in program results, when the program results of calculation of complex, significantly improves counting yield.
Accompanying drawing explanation
Fig. 1 is the resource constraint network in background technology;
Fig. 2 is the resource constraint network stratified structure adopting the inventive method in embodiment; Wherein (a) illustrates for the flow direction of flow in resource constraint network at each interlayer of network, and (b) is for flow is according to the transmitting procedure of time topological sorting between network summit;
Fig. 3 is the spacecraft resource constraint result adopting the inventive method in embodiment.
Embodiment
For better objects and advantages of the present invention being described, below in conjunction with drawings and Examples, content of the present invention is described further.
First the feasibility of the inventive method is analyzed:
In existing resource constraint network as shown in Figure 1, solve F (G
r) time, can to G
rsummit and limit carry out classification process, resource constraint network is deformed into hierarchy, as shown in Figure 2.Summit in network is divided into four layers in the horizontal: source point σ, production sudden change layer V
p, consume sudden change layer V
c, meeting point τ.Arrange according to the execution time in the vertical.Limit is divided into three layers in the horizontal: production limit E
p, internal edges E
i, consume limit E
c.Fig. 2 (a) represents the flow direction of network traffics.
As can be seen from Fig. 2, flow is advanced to pass through following steps from σ to τ: 1) from source point σ along production limit E
pto production V
p, the flow of propelling may not exceed E
pcapacity; 2) from production V
palong internal edges E
ito exhaustion point V
c, due to E
icapacity be+∞, the flow of propelling is unrestricted; 3) from exhaustion point V
calong consuming limit E
cto meeting point τ, the flow of propelling may not exceed E
ccapacity.
At the G of Fig. 1
rin, production limit E
pdirection is σ → V
p, consume limit E
cdirection is V
c→ τ, only has a kind of situation when therefore the 1st step of above-mentioned flow process and the 3rd step perform.And when performing the second step of flow process, due to internal edges E
idirection can from V
pto V
c, also can from V
cto V
p, can also at V
por V
cwithin.If only edge is from V
pto V
ce
iadvance flow, as path
the augmenting path then produced is the shortest, is 3 through limit quantity.If in the layer of summit or V
cto V
pbetween E
iadvance flow, as path
then the length of augmenting path will be greater than 3.
When lower surface analysis advances flow in the layer of summit, from V
cto V
ppath on the impact of flow progradation.Consider time sequencing, for G
rin any two resources sudden change δ
iand δ
j, the execution time
time, namely there is E
i=(v
i, v
j).Therefore to production sudden change v
pwith the execution time at v
pafter all consumption sudden change v
c, all there is the limit (v directly connected
p, v
c).Due to E
ithe capacity on limit is+∞, when augmenting path comprises the limit in the layer of summit
or from V
cto V
plimit (v
c, v
p) time, what can be converted into equivalence only includes limit (v
p, v
c) path.So at selection E
itime, only according to the time relationship between resource sudden change, need consider from V
pto V
climit (v
p, v
c).
From V
pto V
cwhen advancing flow, advance the determination of flow and select E
iorder can have influence on the efficiency of computing.From v
pto v
cwhen advancing flow, v
pthe flow of upper storage equals and v
pthe E be connected
pcapacity, due to E
ithe capacity on limit is+∞, v
pthe flow of upper storage all will be advanced to v
con.But v
cthe flow that can advance equals and v
cthe E be connected
ccapacity, v
pto v
cwhat advance flows exceed v
cduring the flow that can advance, need v
con the flow that exceeds return, increase extra operation.When advancing flow, with E
pcapacity as a reference, unnecessary operation can be reduced.
Consider below to select E
iorder.If G
rthe middle resource sudden change execution time is all not identical, namely
time, G
rit is a directed acyclic graph.According to the execution time to G
rtopological sorting is carried out on interior all summits, generates the linear order of a resource sudden change.According to the select progressively v generating linear order
pwith v
cadvance flow, can ensure all to carry out saturated propelling in all production sudden changes, and reduce propelling number of times as far as possible.V
pwith v
cannexation only and δ
athe time relationship of middle resource sudden change is relevant, and the linear order that therefore topological sorting produces embodies the time sequencing that resource sudden change performs.
If G
rmiddle exist the execution time identical resource sudden change, namely
time, δ
iand δ
jbetween suddenling change with other resource, there is identical time relationship, according to | Δ q
r, δ| size they are sorted, can effectively reduce propelling number of times.
Provide a specific embodiment below so that the concrete implementation step of the inventive method to be described.In this example, consider the spacecraft with 8 subsystems, the behavior aggregate of program results is distributed on each subsystem time line, generate according to following parameter and need program results to be processed: the execution time T ∈ [0 of behavior aggregate in program results, 200], the action sum n=50 comprised, the resource of use is storer, resource quantity demand fulfillment q
r∈ [0,2000].When initial time t=0, memory resource quantity q
r(0)=2000.The connected probability cp=0.1 of the resource constraint network that program results generates, the parallel situation of action in this Parametric Representation Space Vehicle System.Concrete processing procedure is as follows:
Step one, time-constrain, each resource constraint needed for action executing between the multiple action in the action sequence of plane-generating, tasks carrying process and execution time thereof, each action.Action sequence is expressed as A={a
1, a
2..., a
i..., a
n.A
ifor the action comprised in program results, as attitude rotates, transmits data etc.Time-constrain between action is the time interval that every two actions occur.The resource constraint of action be each action executing of spacecraft start with at the end of change to resource quantity.
Action a in program results can be described as the set of action correlated variables
action a
itime-constrain represented by execution time t, its span is t ∈ [t
s, t
e], wherein t
s, t
ethe start time performed for action a and end time.The resource constraint of action a is by resource variable
represent,
the quantity of representative resource is expressed as q
r, the maximal value that it can be got is
, resource quantity must meet
an action can be subject to the impact of multiple resource constraint simultaneously.
When action a needs to use a kind of resource r, if the quantity q of resource
rthe only start time of conation work in office
or finish time
change, the change of each resource quantity can be described as first resource sudden change δ.According to the action sequence that the autonomous mission planning of spacecraft generates, for resource on the star used needed for each, a resource catastrophe set can be generated respectively.When the moment is t, the changes values of resource quantity is
In above formula, the changes values of not undergoing mutation
negligible.Oneself completes the changes values of sudden change
namely the range limit of execution time is that the δ of t is to resource changing amount sum.The changes values of pending sudden change
comparatively complicated, need calculate through the following steps.
Step 2, according to the resource catastrophe set that step one generates, can generate the resource constraint network G representing all resource constraints in action sequence
r.δ
ain resource each time sudden change δ be expressed as G
ra vertex v.In order to represent production and the consumption of resource, at G
ralso need to add the source point σ and meeting point τ that represent that resource is produced and consumed respectively.Time relationship between resource sudden change is expressed as internal edges E
i=(v
p, v
c), the resource sudden change performed comparatively is early pointed to from performing more late resource sudden change in the direction on limit, and the capacity on limit is infinitely great.According to δ, stock number is increased or minimizing, will represent that the summit increasing resource value is referred to as production catastrophe point v
p, the summit of reducing resource value is referred to as and consumes catastrophe point v
c.Production catastrophe point v
pand with production limit E between source point σ
p=(σ, v
p) connect, v is pointed to from σ in the direction on limit
p, the capacity on limit is the value Δ q of resource changing
r, δ; Consume between catastrophe point and meeting point τ with consuming limit E
c=(v
c, τ) connect, the direction on limit is from v
cpoint to τ, the capacity on limit is the value Δ q of resource changing
r, δ.
With the execution time t of resource sudden change δ for criterion, topological sorting is carried out to the resource sudden change in each resource catastrophe set and in chronological sequence order label, generate and there is the resource constraint network of hierarchy.According to the execution time of resource sudden change during sequence, the sequence number of point corresponding for the resource performed the earliest sudden change is designated as 1, then increases the sequence number on follow-up summit according to time sequencing successively.Production catastrophe point marked together with consumption catastrophe point during marking serial numbers, the form on final each summit is v
pior v
cj.
For the ease of subsequent treatment, also need G
rcarry out layered shaping.G
rsummit be divided into four layers: source point σ, produce sudden change V
p, consume sudden change V
c, meeting point τ.Produce sudden change V
pand the limit between source point σ is production limit E
p, produce sudden change V
pwith consumption sudden change V
cbetween limit be internal edges E
i, consume sudden change V
cand the limit between meeting point τ is and consumes limit E
c.
In order to follow-up use, after layered shaping, increase a flow value for every bar limit.Flow value is all set to 0, and must not exceed the capacity on this limit in use.
Step 3, from source point σ to production sudden change layer V
pcarry out flow propelling.According to label order from small to large, select each production catastrophe point v successively
pi, and at production limit e
pi=(σ, v
pi) on from source point σ to production catastrophe point v
picarry out saturated propelling.
When carrying out saturated propelling, by e
piflow value be set to e
picapacity.For v
pi, when the resource sudden change that sequence number is greater than i is production sudden change, end step three.
Step 4, from production sudden change layer V
pto consumption sudden change layer V
ccarry out flow propelling, then from consumption sudden change layer V
cflow propelling is carried out to meeting point τ.
Step 4.1, at production sudden change layer V
pin untreated production catastrophe point, sort according to the label of production catastrophe point, select the production catastrophe point v that label is minimum
pi;
Step 4.2, for selected production catastrophe point v
pi, be greater than v at all labels
piconsumption catastrophe point in, according to from small to large label select progressively consume catastrophe point v
cj(j > i), and from production catastrophe point v
pipoint to and consume catastrophe point v
cjinternal edges E
ij=(v
pi, v
cj) on, carry out saturated propelling;
With pointing to selected production catastrophe point v
piproduction limit E
pi=(σ, v
pi) flow deduct the internal edges E with current selected
ijflow, can E be obtained
piutilizable flow.Then by internal edges E
ij=(v
pi, v
cj) flow value be set to E
piutilizable flow, and by production limit E
piflow value deduct E
piutilizable flow.
Step 4.3, the consumption catastrophe point v selected from step 4.2
cjset out, at consumption limit E
cj=(v
cj, τ) on carry out saturated propelling.With consumption limit E
cj=(v
cj, τ) capacity deduct E
cjpresent flow rate, can E be obtained
cjutilizable flow.If E
cjutilizable flow to be greater than in step 4.2 selected internal edges E
ij=(v
pi, v
cj) flow, then by E
cjflow add E
ijflow, and by E
ijflow set be 0; If E
cjutilizable flow to be less than or equal in step 4.2 selected internal edges E
ij=(v
pi, v
cj) flow, then by E
cjflow set be E
cjcapacity, and by E
ijflow deduct E
cjutilizable flow.
Step 4.4, when at v
cjon complete saturated propelling after, then return step 4.2, select next label to be greater than v
piconsumption catastrophe point; If oneself through arriving the maximum consumption catastrophe point of last sequence number, then returns step 4.1, selects next label to be greater than v
piproduction catastrophe point.Until all production catastrophe points all complete through consuming sudden change layer V
cto the saturated propelling of meeting point τ.
Step 6, after completing above-mentioned steps, then source point σ has carried out saturated propelling through middle two-layer summit to meeting point τ.According to G
rin to be connected with meeting point τ all E
c=(v
c, τ) flow sum, the maximum flow valuve F (G of network can be obtained
r).According to following formula
The changes values of spacecraft resource quantity in program results can be obtained.
The spacecraft resource constraint result of this example as shown in Figure 3.As seen from the figure, work as n=50, during cp=0.1, when Execution plan result, the surplus of memory resource remains in Scope of Resources, and the resource constraint of program results is met.
Claims (3)
1., based on a spacecraft resource constraint disposal route for time topological sorting, it is characterized in that: comprise the steps:
Step one, the autonomous mission planning of spacecraft generates time-constrain, each resource constraint needed for action executing between action sequence, multiple action in tasks carrying process and execution time thereof, each action; Wherein, action sequence is expressed as A={a
1, a
2..., a
i..., a
n; a
ifor the action comprised in program results; Time-constrain between action is the time interval that every two actions occur; The resource constraint of action be each action executing of spacecraft start with at the end of change to resource quantity;
As action a
iwhen needing to use a kind of resource r, if the quantity q of resource r
ronly at action a
istart time
or finish time
change, the change of each resource quantity is described as first resource sudden change δ; According to action sequence, for resource on the star used needed for each, generate a resource catastrophe set respectively;
Step 2, according to the resource catastrophe set described in step one, with the execution time t of resource sudden change δ for criterion, carries out topological sorting to the resource sudden change in each resource catastrophe set and in chronological sequence order label, generates and have the resource constraint network G of hierarchy
r; G
rrepresent all resource constraints in action sequence; Concrete grammar is:
Step 2.1, according to the execution time of resource sudden change, is designated as 1 by the sequence number of point corresponding for the resource performed the earliest sudden change, then increases the sequence number of following resource catastrophe point according to time sequencing successively; While marking serial numbers, all resource catastrophe points are labeled as production catastrophe point v according to the change of resource quantity
piwith consumption catastrophe point v
cj;
Step 2.2, carries out layered shaping to all resource catastrophe points, obtains G
r; G
rbe divided into four layers: source point σ, production sudden change layer V
p, consume sudden change layer V
c, meeting point τ; Produce sudden change layer V
peach point and source point σ between limit be production limit E
p, produce sudden change layer V
pwith consumption sudden change layer V
ceach point between limit be internal edges E
i, consume sudden change layer V
cpoint and meeting point τ between limit be and consume limit E
c;
Step 2.3, increases a flow value for every bar limit after layered shaping; Flow initial value is set to 0, and must not exceed the capacity on this limit in use;
Described capacity is the maximal value of flow on every bar limit; The capacity E on production limit
pbe set to the production catastrophe point v be connected with production limit
picorresponding production sudden change increases the numerical value of resource, consumes the capacity E on limit
cbe set to and the consumption catastrophe point v consuming limit and be connected
cjcorresponding consumption sudden change reduces the numerical value of resource,
Step 3, from source point σ to production sudden change layer V
pcarry out flow propelling; According to label order from small to large, select each production catastrophe point v successively
pi, and at production limit E
pi=(σ, v
pi) on from source point σ to production catastrophe point v
picarry out saturated propelling; When carrying out saturated propelling, by E
piflow value be set to E
picapacity; For v
pi, when the resource sudden change that sequence number is greater than i is production sudden change, end step three, performs step 4;
Step 4, from production sudden change layer V
pto consumption sudden change layer V
ccarry out flow propelling, then from consumption sudden change layer V
cflow propelling is carried out to meeting point τ; Concrete grammar is:
Step 4.1, according to label order from small to large, selects production catastrophe point v successively
pi;
Step 4.2, for a production catastrophe point v
pi, according to label order from small to large, select all labels to be greater than v
piconsumption catastrophe point v
cj(j > i), at internal edges E
i=(v
pi, v
cj) on from production catastrophe point v
pito consumption catastrophe point v
cjcarry out saturated propelling;
Step 4.3, to the consumption catastrophe point v completing saturated propelling in step 4.2
cj, at consumption limit E
c=(v
cj, τ) on carry out saturated propelling;
Step 4.4, selects sequence number to be greater than v
cjthe next one consume catastrophe point, consumption limit on carry out saturated propelling; If oneself is greater than v at treated complete all sequence numbers
cjconsumption catastrophe point, then select sequence number be greater than v
pinext production catastrophe point, return step 4.2, until all production catastrophe points all complete through consuming sudden change layer V
cto the saturated propelling of meeting point τ;
Step 5, above-mentioned steps completes source point σ through the middle two-layer saturated propelling to meeting point τ; According to G
rin to be connected with meeting point τ all E
c=(v
c, τ) flow sum, obtain the maximum flow valuve F (G of network
r); Changes values according to following formula computational resource quantity:
Wherein, q
rt () represents the changes values in t resource quantity; According to the execution time of resource sudden change and the relation of current time t, the resource caused by action sequence A sudden change is divided into three parts: oneself undergos mutation
wait to undergo mutation
do not undergo mutation
oneself undergos mutation
comprise all resource sudden changes that oneself performs at moment t, to total changes values of resource quantity be
wait to undergo mutation
comprise all resource sudden changes performed at moment t, to total changes values of resource quantity be
do not undergo mutation
comprise all in the still unenforced resource sudden change of moment t, to total changes values of resource quantity be
value by calculate moment t time all resource changing value summations that oneself undergos mutation
obtain,
value by calculating moment t time resource constraint network maximum flow valuve F (G
r) obtain;
Thus obtain the changes values of spacecraft resource quantity in program results.
2. a kind of spacecraft resource constraint disposal route based on time topological sorting according to claim 1, is characterized in that: described in step 4.2 from production catastrophe point v
pito consumption catastrophe point v
cjcarry out saturated propelling to be specially: with selected production catastrophe point v
piproduction limit E
pi=(σ, v
pi) flow deduct the internal edges E with current selected
iflow, obtain E
piutilizable flow; Then by internal edges E
i=(v
pi, v
cj) flow value be set to E
piutilizable flow, and by production limit E
piflow value deduct E
piutilizable flow.
3. a kind of spacecraft resource constraint disposal route based on time topological sorting according to claim 1, is characterized in that: described in step 4.3 consumption limit E
c=(v
cj, τ) on carry out saturated propelling and be specially: with consuming limit E
cj=(v
cj, τ) capacity deduct E
cpresent flow rate, can E be obtained
cutilizable flow; If E
cutilizable flow to be greater than in step 4.2 selected internal edges E
i=(v
pi, v
cj) flow, then by E
cflow add E
iflow, and by E
iflow set be 0; If E
cutilizable flow to be less than or equal in step 4.2 selected internal edges E
ij=(v
pi, v
cj) flow, then by E
cflow set be E
ccapacity, and by E
iflow deduct E
cutilizable flow.
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