CN111737886B - Wind tunnel test scheduling method and system - Google Patents

Wind tunnel test scheduling method and system Download PDF

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CN111737886B
CN111737886B CN202010786307.4A CN202010786307A CN111737886B CN 111737886 B CN111737886 B CN 111737886B CN 202010786307 A CN202010786307 A CN 202010786307A CN 111737886 B CN111737886 B CN 111737886B
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CN111737886A (en
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明丽洪
罗昌俊
王小飞
熊建军
何福
郑娟
马永一
宋朝琪
袁宗泽
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Low Speed Aerodynamics Institute of China Aerodynamics Research and Development Center
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Abstract

The invention is applicable to the technical field of wind tunnel tests and provides a wind tunnel test scheduling method and a wind tunnel test scheduling system. In the wind tunnel test scheduling method and system, the utilization rate of the branch pipelines is considered, the accumulated return is constructed by taking the average utilization rate of the maximized pipelines as a target, so that the distribution of the wind tunnel test scheduling pipelines can be considered globally, and in the distribution, the selection of the next step execution action is obtained by maximizing the accumulated return.

Description

Wind tunnel test scheduling method and system
Technical Field
The invention belongs to the technical field of wind tunnel tests, and particularly relates to a wind tunnel test scheduling method and system.
Background
The wind tunnel test is an aerodynamic experiment method which fixes an aircraft model or a real object in a pipeline-shaped ground artificial environment (namely a wind tunnel), simulates various complex flight states of the aircraft or other objects in the air by artificially making airflow flow according to the motion relativity principle, thereby acquiring test data and knowing the aerodynamic characteristics of the actual aircraft or other objects.
The scheduling problem is generally defined as: the problem that a set of resources are correspondingly allocated to complete a set of work within a period of time is widely existed in the fields of energy, traffic, production, calculation, emergency medical treatment, safety and the like, and is a complex combined optimization problem. It may be dynamic or static. Dynamic scheduling is to determine the order of jobs or tasks in terms of the current operating environment state; static scheduling is typically a prearrangement, which is the allocation of jobs or tasks from a given workflow.
The wind tunnel test scheduling is a resource guarantee plan which is developed around a specific scene of the wind tunnel test, belongs to the category of dynamic scheduling, is a premise for smoothly developing the wind tunnel test, and is a complex multi-objective optimization problem. Under the condition of meeting the constraint, how to maximize the utilization rate of power resources and minimize the starting and stopping times of equipment, reduce the loss of power equipment and give an optimal test task queue according to time sequence is always the first problem faced by the wind tunnel test scheduling.
In the prior art, a manual scheduling method is usually adopted to realize wind tunnel test scheduling, and due to the defects caused by lack of global property, predictability and only personal experience, the problem is increasingly prominent particularly under the complex environments of sudden increase of test task quantity, centralized supply and guarantee of power resources, resource contention by multiple users and the like, and the traditional manual scheduling method is not free.
Some non-manual scheduling methods also appear in the prior art, but the methods in the prior art all utilize transition probabilities between events, and the transition probabilities are all set by human, so the setting of the magnitude of the transition probabilities greatly affects the scheduling effect, and compared with manual scheduling, the method has no obvious progress.
Disclosure of Invention
The invention aims to provide a wind tunnel test scheduling method and a wind tunnel test scheduling system, and aims to solve the technical problem that the transition probability needs to be manually set in the prior art.
The invention provides a wind tunnel test scheduling method, which comprises the following steps:
s10, constructing a pipeline communication network model;
s20, constructing a communication matrix C of the main pipeline and the branch pipelines according to the pipeline communication network model;
step S30, constructing a state space S according to the distribution condition of the wind tunnel test scheduling pipelines in the current time step, wherein the state space S is used for expressing the communication relation and the opening and closing states of the main pipeline and the branch pipelines;
step S40: constructing an action space A for indicating whether to open a valve of the branch pipeline;
step S50, calculating the accumulated reward within the time period T with the goal of maximizing the average utilization of the pipelineG T ；
Step S60, introduce the policy functionπWill accumulate the rewardG T Conversion to policy-based functionsπState value function and policy-based function ofπA function of action values of;
and step S70, solving the optimal action value function to obtain the optimal strategy.
Furthermore, the pipeline communication network comprises a wind tunnel test power resource, a sink node and a wind tunnel test main body, wherein the wind tunnel test power resource and the sink node are connected through a main pipeline, and the sink node and the wind tunnel test main body are connected through a branch pipeline.
Further, the elements of the connectivity matrix C
Figure 861492DEST_PATH_IMAGE001
Wherein, in the step (A),c ij is shown asiWhether or not there is a second under the main linejThe branch lines are branched into a plurality of branch lines,c ij when =1, it means that the second one is presentiFirst under the main pipelinejA branch line;c ij when =0, it means that the second one is not presentiFirst under the main pipelinejA branch line.
Further, the elements of the state space S
Figure 778633DEST_PATH_IMAGE002
Wherein, whens ij When =1, it means the secondiThe main pipeline is provided with a secondjA branch line, andifirst under the main pipelinejThe branch pipeline is in an open state; at that times ij When =1, the secondiThe main pipeline is provided with a secondjA branch line, andifirst under the main pipelinejThe branch pipeline is in a closed state;s ij when =0, it means the secondiThere is no second under the main linejA branch line.
Further, the elements of the action space A
Figure 558370DEST_PATH_IMAGE003
Wherein, whena ij When =1, will beiExisting under the main pipelinejOpening a valve of the branch pipeline; when in usea ij When =1, the second stepiExisting under the main pipelinejThe valves of the branch lines are closed.
Further, in the step S50,
Figure 891262DEST_PATH_IMAGE004
；
wherein the time of dayt+kBelonging to a point in time within the time period T,R t+k to representt+kAverage utilization of the pipeline at the time point willR t+k Ast+kThe return of the time of day is made,kindicates the number of the set time points,γis the discount rate for the future return.
Further, theR t+k Calculated by the following formula:
Figure 705635DEST_PATH_IMAGE005
；
Figure 465780DEST_PATH_IMAGE006
；
wherein u is ij To representt+kAt a time point ofiExisting under the main pipelinejThe utilization rate of the branch lines of the strip lines,s ij i.e. an element of the state space S, d ij To representt+kAt a time point ofiExisting under the main pipelinejThe test mission power resource demand of the branch pipeline,up ij to representt+kAt a time point ofiExisting under the main pipelinejThe upper limit of the capacity of the strip branch line,nrepresenting the total number of main lines,mis shown asiThe number of branch lines present below the main line,numthe total number of branch lines is indicated.
Further, in step S60, based on the policy functionπHas a state value function of Vπ(s ij )：
Figure 732813DEST_PATH_IMAGE007
；
Based on policy functionsπHas a function of action value of qπ：
Figure 869397DEST_PATH_IMAGE008
。
Further, in step S70, the optimal action value function is q*The optimal strategy isπ *：
Figure 538275DEST_PATH_IMAGE009
。
The invention further provides a wind tunnel test scheduling system, which comprises:
the model construction module is used for constructing a pipeline communication network model;
the communication matrix construction module is used for constructing a communication matrix C of the main pipeline and the branch pipelines according to the pipeline communication network model;
the state space construction module is used for constructing a state space S according to the distribution condition of the wind tunnel test scheduling pipelines in the current time step, and the state space S is used for expressing the communication relation and the state of the main pipeline and the branch pipelines;
an action space construction module: a valve for constructing an action space A to indicate whether the branch line is opened at the next time;
a cumulative reward constructing module for calculating the cumulative reward in the time period T by taking the average utilization rate of the maximized pipeline as the targetG T ；
Strategy function introduction module for introducing strategy functionπWill accumulate the rewardG T Conversion to policy-based functionsπState value function and policy-based function ofπA function of action values of;
and the solving module is used for solving the optimal action value function to obtain the optimal strategy.
Compared with the prior art, the invention has the technical effects that:
1. in the scheduling method, the accumulated return of the current moment is related to the return obtained after the action is executed at the next moment and the return obtained in the future, so that the selection of the next action, namely the valves of which branch pipelines are set to be opened or closed, can be obtained by maximizing the accumulated return instead of solving the state transition probability. Therefore, the influence caused by artificially setting the probability is avoided.
2. In the scheduling method, the utilization rate of branch pipelines is considered, and accumulated return is constructed by taking the average utilization rate of the maximized pipelines as a target, so that the distribution of the wind tunnel test scheduling pipelines can be considered globally, and in the distribution, the selection of the next execution action is obtained by maximizing the accumulated return, therefore, the scheduling method has predictability. Meanwhile, the utilization rate of power resources can be maximized, the opening/closing times of branch pipelines can be minimized, and the loss of power equipment is reduced.
3. According to the invention, the use condition of each pipeline of the wind tunnel test is analyzed, so that the distribution condition of the wind tunnel test scheduling pipeline at the next moment is only related to the distribution condition of the wind tunnel test scheduling pipeline at the current moment, the wind tunnel test scheduling can be realized, and the optimal test task queue can be given according to the time sequence. In addition, the wind tunnel test scheduling of the invention does not adopt a manual scheduling mode and does not adopt the conversion probability set by people, thereby avoiding the defects caused by the manual setting.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention or in the description of the prior art will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a wind tunnel test scheduling method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a pipeline connectivity network model provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram of a connectivity matrix provided by an embodiment of the present invention;
FIG. 4 is a state space diagram provided by an embodiment of the present invention;
fig. 5 is a schematic diagram of a wind tunnel test scheduling system according to an embodiment of the present invention.
Detailed Description
Aspects of the present invention will be described more fully hereinafter with reference to the accompanying drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to any specific structure or function presented throughout this disclosure. Rather, these aspects are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Based on the teachings herein one skilled in the art should appreciate that the scope of the present invention is intended to encompass any aspect disclosed herein, whether alone or in combination with any other aspect of the invention to accomplish any aspect disclosed herein. For example, it may be implemented using any number of the apparatus or performing methods set forth herein. In addition, the scope of the present invention is intended to cover apparatuses or methods implemented with other structure, functionality, or structure and functionality in addition to the various aspects of the invention set forth herein. It is to be understood that any aspect disclosed herein may be embodied by one or more elements of a claim.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments.
As shown in fig. 1, an embodiment of the present invention provides a wind tunnel test scheduling method, which includes the following steps:
s10, constructing a pipeline communication network model;
s20, constructing a communication matrix C of the main pipeline and the branch pipelines according to the pipeline communication network model;
step S30, constructing a state space S according to the distribution condition of the wind tunnel test dispatching pipeline in the current time step, wherein the state space S is used for expressing the communication relation and the opening and closing state of the main pipeline and the branch pipelines;
step S40: constructing an action space A for indicating whether to open a valve of the branch pipeline;
step S50, calculating the accumulated reward within the time period T with the goal of maximizing the average utilization of the pipelineG T ；
Step S60, introduce the policy functionπWill accumulate the rewardG T Conversion to policy-based functionsπFunction of state value ofBased on policy functionsπA function of action values of;
and step S70, solving the optimal action value function to obtain the optimal strategy.
The constructed pipeline communication network model is shown in figure 2, and the pipeline communication network comprises wind tunnel test power resources D, convergent nodes D1-D12 and wind tunnel test main bodies wt-01-wt-26, wherein the wind tunnel test power resources D and the convergent nodes D1-D12 are connected through main pipelines No. 1-12, and the convergent nodes D1-D12 and the wind tunnel test main bodies wt-01-wt-26 are connected through branch pipelines No. 1-26.
The wind tunnel test power resource is used for producing and storing power resources and is used for providing airflow for the wind tunnel test.
Specifically, some main pipelines are connected with branch pipelines, and some main pipelines are not connected with branch pipelines, as shown in fig. 2, branch pipelines are connected with main pipelines No. 1, No. 4, No. 5, No. 7, No. 8, No. 9, No. 10 and No. 12, and branch pipelines are not connected with main pipelines No. 2, No. 3, No. 6 and No. 11; in addition, the number of branch lines connected to the main line may be different, and as shown in fig. 2, 3 branch lines are connected to the main line 1 # and 8 branch lines are connected to the main line 5 #.
For convenience of describing the main pipeline and branch pipeline in the pipeline communication network model, subscripts in the embodiments of the present inventionijIs shown asiExisting under the main pipelinejA branch line, as shown in FIG. 2i=5，j=2When is shown as5Existing under the main pipeline2Branch lines 7 < CHEM > are branch lines below the main line 5 #.
To mathematically model a pipeline connectivity network, a connectivity matrix C is constructed, the elements of which
Figure 531639DEST_PATH_IMAGE001
Wherein, in the step (A),c ij is shown asiWhether or not there is a second under the main linejThe branch lines are branched into a plurality of branch lines,c ij =1when is present, indicates the presence ofiFirst under the main pipelinejA branch line;c ij =0is not present, it meansiFirst under the main pipelinejA branch line.
Therefore, the connection matrix C of the pipeline connection network model shown in FIG. 2 is as shown in FIG. 3.
For example,c 81~ c 88 all are equal to 1, namely 1-8 branch pipelines exist under the 8 th main pipeline; in a similar manner to that described above,c 31~ c 38 and if the number is 0, the number is 1 to 8, which means that no branch pipeline exists under the 3 rd main pipeline.
And performing mathematical characterization on the communication relation of the pipeline communication network model through the communication matrix C.
In step S30, a state space S is constructed according to the wind tunnel test scheduling pipeline allocation condition in the current time step, and the state space S is used for representing the communication relationship and the opening and closing states of the main pipeline and the branch pipelines;
wherein elements of the state space S
Figure 223652DEST_PATH_IMAGE002
。
Wherein whens ij When =1, it means the secondiThe main pipeline is provided with a secondjA branch line, andifirst under the main pipelinejThe branch pipeline is in an open state; at that times ij When =1, the secondiThe main pipeline is provided with a secondjA branch line, andifirst under the main pipelinejThe branch pipeline is in a closed state;s ij when =0, it means the secondiThere is no second under the main linejA branch line.
In order to avoid the problem that the supply quality of a sink node is reduced and the conflict between supply guarantee and supply is caused by simultaneously opening a plurality of branch pipelines under one main pipeline, the following constraint conditions are set: at a certain moment, only one branch pipeline is opened under one main pipeline; fig. 4 reflects the state space S at a certain moment.
For example,s 11 if =1, it means that the 1 st branch pipe exists below the 1 st main pipelineThe 1 st branch pipeline below the 1 st main pipeline is in an open state;s 12 = -1 ands 13 if =1, it indicates that 1 st and 2 th branch lines exist below the 1 st main line, and the 1 st and 2 nd branch lines below the 1 st main line are in a closed state; whiles 14 ~s 18 All equal to 0, it means that there are no 4 th to 8 th branch lines under the 1 st main line. Meanwhile, based on the above constraint conditions, only 1 branch line is opened under the 1 st main line, in this example, only the 1 st branch line is in an opened state, and the 2 nd and 3 rd branch lines are in a closed state under the 1 st main line.
Further, in order to mathematically turn on and off the branch line, an action space a is set, and elements of the action space a
Figure 960664DEST_PATH_IMAGE003
。
Wherein whena ij When =1, will beiExisting under the main pipelinejOpening a valve of the branch pipeline; when in usea ij When =1, the second stepiExisting under the main pipelinejThe valves of the branch lines are closed.
In the step S50, a cumulative reward is constructed with the goal of maximizing the average utilization of the pipelineG T ，
Figure 421732DEST_PATH_IMAGE004
；
Wherein the time of dayt+kBelonging to a point in time within the time period T,R t+k to representt+kAverage utilization of the pipeline at the time point willR t+k Ast+kThe return of the time of day is made,kindicates the number of the set time points,γis the discount rate of the long term return whenγ=0Time, meaning only concerned with immediate returns; when in useγ=1Time, it means that there is no discount on the future payoff, and the average utilization of all the pipelines is calculated with the same proportion.
It can be seen from the above formula that the accumulated reward at the current moment is related to the reward obtained after the action is executed at the next moment and the reward obtained in the future, so that the selection of the action to be executed next, i.e. which branch lines have their valves set to open or close, can maximize the accumulated rewardG T Instead of solving the state transition probability, thereby avoiding the influence caused by artificially setting the probability.
The above-mentionedR t+k Calculated by the following formula:
Figure 851576DEST_PATH_IMAGE005
；
Figure 30885DEST_PATH_IMAGE006
；
wherein u is ij To representt+kAt a time point ofiExisting under the main pipelinejThe utilization rate of the branch lines of the strip lines,s ij i.e. an element of the state space S, d ij To representt+kAt a time point ofiExisting under the main pipelinejThe test mission power resource demand of the branch pipeline,up ij to representt+kAt a time point ofiExisting under the main pipelinejThe upper limit of the capacity of the strip branch line,nrepresenting the total number of main lines,mis shown asiThe number of branch lines present below the main line, so that as shown in fig. 2, the number of branch lines present below the 5 th main line is 8,numthe total number of branch lines is indicated.
One of the core innovation points of the invention is that the utilization rate of branch pipelines is utilized to construct a return functionR t+k A corresponding return model is established, and then a target function is established by the return model, a similar return model does not exist in the prior art at present, but the return model can solve the technical problem that the wind tunnel test scheduling lacks predictability, and therefore the state transition probability is not needed.
In the scheduling method, the utilization rate of branch pipelines is considered, and accumulated return is constructed by taking the average utilization rate of the maximized pipelines as a target, so that the distribution of the wind tunnel test scheduling pipelines can be considered globally, and in the distribution, the selection of the next execution action is carried out to report the accumulated return by maximizingG T To achieve this, the scheduling method of the present invention is thus predictive.
Further, in step S60,
based on policy functionsπHas a state value function of Vπ(s ij )：
Figure 306008DEST_PATH_IMAGE007
Based on policy functionsπHas a function of action value of qπ：
Figure 949479DEST_PATH_IMAGE008
。
Further, in step S70, the optimal action value function is q*The optimal strategy isπ *：
Figure 222329DEST_PATH_IMAGE009
。
Through step S70, the action value in each state can be calculated and filled into the action space at the next moment, so as to obtain the distribution condition and the valve opening/closing condition of the wind tunnel test dispatching pipeline at the next moment.
In the invention, the use condition of each pipeline of the wind tunnel test is analyzed, so that the distribution condition of the wind tunnel test scheduling pipeline at the next moment is only related to the distribution condition of the wind tunnel test scheduling pipeline at the current moment, the wind tunnel test scheduling can be realized, the optimal test task queue can be given according to the time sequence, and the wind tunnel test scheduling does not adopt a manual scheduling mode and does not adopt the artificially set conversion probability, thereby avoiding the defects caused by artificial setting.
In addition, in the scheduling method, the accumulated reward is constructed by taking the average utilization rate of the maximized pipeline as a target, so that the utilization rate of power resources can be maximized, the opening/closing times of branch pipelines can be minimized, and the loss of power equipment is reduced.
As shown in fig. 5, the present invention further provides a wind tunnel test scheduling system, including:
the model construction module is used for constructing a pipeline communication network model;
the communication matrix construction module is used for constructing a communication matrix C of the main pipeline and the branch pipelines according to the pipeline communication network model;
the state space construction module is used for constructing a state space S according to the distribution condition of the wind tunnel test scheduling pipelines in the current time step, and the state space S is used for expressing the communication relation and the state of the main pipeline and the branch pipelines;
an action space construction module: a valve for constructing an action space A to indicate whether the branch line is opened at the next time;
a cumulative reward constructing module for calculating the cumulative reward in the time period T by taking the average utilization rate of the maximized pipeline as the targetG T ；
Strategy function introduction module for introducing strategy functionπWill accumulate the rewardG T Conversion to policy-based functionsπState value function and policy-based function ofπA function of action values of;
and the solving module is used for solving the optimal action value function to obtain the optimal strategy.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (10)

1. A wind tunnel test scheduling method is characterized by comprising the following steps:
s10, constructing a pipeline communication network model;
s20, constructing a communication matrix C of the main pipeline and the branch pipelines according to the pipeline communication network model;
step S30, constructing a state space S according to the distribution condition of the wind tunnel test scheduling pipelines in the current time step, wherein the state space S is used for expressing the communication relation and the opening and closing states of the main pipeline and the branch pipelines;
step S40: constructing an action space A for indicating whether to open a valve of the branch pipeline;
step S50, calculating the cumulative reward G over the time period T with the goal of maximizing the average utilization of the pipelineT；
Step S60, introduce the strategy function pi, the cumulative return GTConverting into a state value function based on a strategy function pi and an action value function based on the strategy function pi;
and step S70, solving the optimal action value function to obtain the optimal strategy.
2. The wind tunnel test scheduling method according to claim 1, wherein the pipeline communication network comprises a wind tunnel test power resource, a sink node and a wind tunnel test main body, wherein the wind tunnel test power resource and the sink node are connected through a main pipeline, and the sink node and the wind tunnel test main body are connected through a branch pipeline.
3. The wind tunnel test scheduling method of claim 2, wherein the element C of the connectivity matrix Cij∈[1，0]Wherein c isijIndicating the presence or absence of a jth branch line below the ith main line, cijWhen 1, the j branch pipeline below the i main pipeline exists; c. CijWhen 0, the j branch line below the i main line is not present.
4. A wind tunnel test scheduling method according to claim 3 wherein said state space SElement sij∈[1，0，-1]Wherein when sijWhen the number of the branch lines is 1, the j-th branch line exists below the ith main line, and the j-th branch line below the ith main line is in an open state; then sijWhen the pressure value is equal to-1, a jth branch pipeline exists below the ith main pipeline, and a jth branch pipeline below the ith main pipeline is in a closed state; sijWhen 0, it means that the j branch line does not exist under the i main line.
5. The wind tunnel test scheduling method of claim 4, wherein the element a of the motion space Aij∈[1，-1]Wherein, when aijWhen the pressure value is 1, opening a valve of a jth branch pipeline existing below an ith main pipeline; when a isijWhen the value is-1, the valve of the jth branch line existing below the ith main line is closed.
6. The wind tunnel test scheduling method of claim 5, wherein in step S50,
Figure FDA0002734222410000021
wherein the time T + k belongs to a time point within the time period T, Rt+kAverage utilization of the pipeline, R, representing the time point of t + kt+kAs the return at time t + k, k represents the number of set time points, and γ is the discount rate of the long-term return.
7. The wind tunnel test scheduling method of claim 6, wherein R ist+kCalculated by the following formula:
Figure FDA0002734222410000022
wherein u isijRepresents the utilization rate, s, of the jth branch pipeline existing under the ith main pipeline at the time point of t + kijI.e. an element of the state space S, dijRepresents the power resource demand of the test task of the jth branch pipeline existing under the ith main pipeline at the time point of t + k, upijThe capacity upper limit of the j branch line existing below the ith main line at the time point of t + k is shown, n represents the total number of the main lines, m represents the number of the branch lines existing below the ith main line, and num represents the total number of the branch lines.
8. The wind tunnel test scheduling method of claim 7, wherein in step S60, the state value function based on the policy function pi is Vπ(sij)：
Vπ(sij)＝Eπ[Rt+1+γVπ(St+1)|St＝sij]
The action value function based on the strategy function pi is qπ：
Figure FDA0002734222410000031
9. The wind tunnel test scheduling method of claim 8, wherein in step S70, the optimal action value function is q*The optimal strategy is pi*：
Figure FDA0002734222410000032
10. A wind tunnel test dispatch system, comprising:
the model construction module is used for constructing a pipeline communication network model;
the communication matrix construction module is used for constructing a communication matrix C of the main pipeline and the branch pipelines according to the pipeline communication network model;
the state space construction module is used for constructing a state space S according to the distribution condition of the wind tunnel test scheduling pipelines in the current time step, and the state space S is used for expressing the communication relation and the state of the main pipeline and the branch pipelines;
an action space construction module: a valve for constructing an action space A to indicate whether the branch line is opened at the next time;
a cumulative reward constructing module for calculating the cumulative reward G in the time period T by taking the average utilization rate of the maximized pipeline as the targetT；
A strategy function introduction module for introducing a strategy function pi and giving the accumulated return GTConverting into a state value function based on a strategy function pi and an action value function based on the strategy function pi;
and the solving module is used for solving the optimal action value function to obtain the optimal strategy.
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