CN107239661A - A kind of remote sensing satellite observation mission planing method - Google Patents
A kind of remote sensing satellite observation mission planing method Download PDFInfo
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Abstract
The present invention provides a kind of remote sensing satellite observation mission planing method, and method includes：When becoming neighborhood tabu search algorithm using dynamic, initial taboo list T is set*, initial taboo list lengthDynamic becomes taboo list lengthAnd initial solution x0, since iterations k=1, by T*、And initial solution x0, the iterative process of tabu search algorithm is performed using modified neighborhood building method, and after stopping criterion is met, optimal solution x when output meets stopping criterion*；Further according to T*、And x when meeting stopping criterion*, the iterative process of tabu search algorithm is performed using adjusting type neighborhood method；After stopping criterion is met, using the optimal solution x to finally exporting*The optimal case that a more excellent solution to be output is planned as remote sensing satellite observation mission is obtained using local search algorithm.The above method is to use dynamic to become the method that neighborhood tabu search algorithm handles remote sensing satellite observation mission planning problem, can improve the operational efficiency of algorithm, expands the hunting zone solved and algorithm is difficult to be absorbed in cyclic search state.
Description
Technical field
It is particularly a kind of that neighborhood tabu search algorithm processing remote sensing satellite is become using dynamic the present invention relates to computer technology
The method of observation mission planning problem.
Background technology
Remote sensing earth observation mission planning problem can be briefly described for:One group of remote sensing satellite, one group of observation mission, each
The completion of observation mission includes two activities of data acquisition and data back, as shown in Figure 1.One is specified for each observation mission
Priority；There are one group of available time windows between the corresponding ground target of observation mission and satellite；One reference time scope
It is used as the beginning and ending time of mission planning.
In order that remote sensing satellite preferably plays a role, mission planning technology seems particularly critical.The implication of mission planning
Refer to carry out pending observation mission scheduling, it is resource matched, and to satellite and its work time domain, spatial domain and the mould of load
Formula etc. is determined, and formulates the process of detailed operation plan, and the purpose is to drive satellite resource science, be effectively carried out appointing
Business.Remote sensing earth observation mission planning must be completed under complicated constraints and under a variety of optimization aims, there is a problem that
Dimension is wide, and optimization space is big, many in the prior art to draw its approximate optimal solution using intelligent algorithm.In the prior art using one kind
Taboo Neighborhood-region-search algorithm is a kind of algorithm of conventional solution remote sensing earth observation mission planning problem.
However, when taboo Neighborhood-region-search algorithm handles remote sensing satellite earth observation mission planning problem in the prior art, searching
Suo Sudu is slower, and is easily trapped into local circulation search condition, it is impossible to all Searching Resolution Spaces, can not find all solution spaces
More excellent solution.
The content of the invention
For defect of the prior art, the present invention provides one kind and becomes the processing remote sensing of neighborhood tabu search algorithm using dynamic
The method of satellite earth observation mission planning problem.
In a first aspect, the present invention provides a kind of remote sensing satellite observation mission planing method, methods described is using dynamic change
The method that neighborhood tabu search algorithm handles remote sensing satellite observation mission planning problem, method includes：
S1, when becoming neighborhood tabu search algorithm processing remote sensing satellite observation mission planning problem using dynamic, set and prohibit
The initial taboo list T avoided in searching algorithm*, initial taboo list lengthDynamic becomes neighborhood taboo list lengthWith
And initial solution x0, and make optimal solution be equal to initial solution x*=x0；
S2, since iterations k=1, according to initial taboo list T*, dynamic become taboo list lengthAnd just
The solution that begins x0, using modified neighborhood building method, perform the iterative process of tabu search algorithm；Taboo is met in iterative process to search
After the stopping criterion of rope algorithm, output meets optimal solution x during stopping criterion*；
S3, according to taboo list T*, dynamic become taboo list lengthIt is optimal when meeting stopping criterion in step S2
Solve x*, the iterative process of tabu search algorithm is performed using adjusting type neighborhood building method；
S4, meet after dynamic becomes the stopping criterion of neighborhood tabu search algorithm in step S3 iterative process, to last defeated
The optimal solution x gone out*Obtain what a more excellent solution to be output was planned as remote sensing satellite observation mission using local search algorithm
Optimal case.
Alternatively, step S2 includes：
Set taboo listInitial taboo list length From repeatedly
Generation number k=1 starts, and randomly selects an initial solution x in solution space0, and calculate the target function value f of initial solution
(x0)；
Initial solution x0 neighborhood solution set N is obtained using modified neighborhood method1(x), to n (x) ∈ N1(x), solution is suitable
Response function is f [n (x)], and n is filtered out according to f [n (x)]*(x), n*(x) it is set N1(x) fitness function value is caused most in
Big solution；
The selection rule of solution is as follows：
If 1.：n*(x)∈T*And n*(x) aspiration criterion is met, then makes x*=n*(x), n*(x)→T*；
If 2.：n*(x)∈T*And n*(x) aspiration criterion is unsatisfactory for, then makes x*=n'(x), and wherein f [n'(x)]=opt { f
[n(x)],n(x)∈(N1(x)-T*)}；
If 3.：Then make x*=n*(x), n*(x)→T*；
Judge whether to meet stopping criterion, stop output x if meeting*, otherwise to current x*Continue to use modified neighborhood
Building method produces disturbance, continues iteration；
Will be with n*(x) corresponding neighborhood moving method inserts taboo list T*In, set its Tabu Length to beAnd by taboo list T after follow-up iteration every time*In with n*(x) corresponding neighborhood movement side
The Tabu Length of method subtracts 1.
Alternatively, step S2 includes：
Initial taboo list T*With initial solution x0, dynamic change taboo list lengthIterations
K=0 starts；It is random to use insertion new task or replace multitask method to x0Produce random perturbation generation neighborhood solution space N1(x),
In N1(x) a new more excellent solution j is obtained in1, judge whether to receive new more excellent solution j1；Iteration process is stopped until meeting
Then, the more excellent solution obtained when meeting stopping criterion is x to no-go gage*；
Step S3 includes：
Using reallocation task to meeting more excellent solution x during stopping criterion in step S2*Random perturbation is produced, neighborhood is generated
Solution space N2(x), in N2(x) a new more excellent solution j is obtained in2, judge whether to receive new more excellent solution j2；Iteration mistake
Cheng Zhizhi meets stopping rule.
Alternatively, the stopping criterion of dynamic change neighborhood tabu search algorithm includes：
Determine step number stop criterion：The current optimal solution recorded when step number reaches threshold value becomes neighborhood taboo as dynamic and searched
The optimal solution of rope algorithm output；
Or,
FREQUENCY CONTROL principle：A certain solution sequence or target function value are used as the more excellent solution frequency of occurrences in iterative process
During beyond a given threshold value, terminate and calculate；
Or,
Target control principle：In given step number, current optimal value no longer changes, or the difference changed
Within a preset range, terminate and calculate.
Alternatively, each more excellent solution includes：
Perform the satellite mark of each task, observe start time point, observation end time point；
Start time point that each satellite is interacted with least one earth station, end time point；
And/or,
Modified neighborhood building method is that new task is inserted to current solution sequence or wherein one or more are replaced
Business, thus constructs new solution space；The new task of insertion or the task of replacement are：The user received in advance treats at least one satellite
Perform the task for observation/pass down；
Adjusting type neighborhood building method is, to current solution sequence reallocation task i.e. by among a certain satellite solution sequence
A certain observation mission is adjusted to the satellite to its another SEE time window from a SEE time window；
And/or,
Methods described also includes：
Assignment instructions corresponding with each satellite in the optimal case are sent into the satellite so that the satellite it is distant
Sensor is performed according to the observation mission of planning.
Second aspect, the present invention also provides a kind of device for handling the planning of remote sensing satellite observation mission, including：
Receiver, the processor for connecting receiver；
Receiver receives the observation mission that at least one is performed with satellite remote sensor；
The processor becomes the planning that neighborhood tabu search algorithm handles remote sensing satellite observation mission, specific bag using dynamic
Include：When becoming neighborhood tabu search algorithm processing remote sensing satellite observation mission planning problem using dynamic, TABU search is set to calculate
Initial taboo list T in method*, initial taboo list lengthDynamic becomes neighborhood taboo list lengthAnd initial solution
x0, and make optimal solution be equal to initial solution x*=x0；
Since iterations k=1, according to initial taboo list T*, dynamic become taboo list lengthAnd initial solution
x0, using modified neighborhood building method, perform the iterative process of tabu search algorithm；TABU search is met in iterative process to calculate
After the stopping criterion of method, output meets optimal solution x during stopping criterion*；
According to taboo list T*, dynamic become taboo list lengthOptimal solution when meeting stopping criterion in step S2
x*, the iterative process of tabu search algorithm is performed using adjusting type neighborhood building method；
After the stopping criterion that previous step iterative process meets dynamic change neighborhood tabu search algorithm, to what is finally exported
Optimal solution x*Using local search algorithm obtain a more excellent solution to be output as remote sensing satellite observation mission plan it is optimal
Scheme.
Alternatively, in addition to：The transmitter being connected with processor；
The transmitter sends the assignment instructions of each satellite into the satellite, so that the remote sensor of satellite is according to planning
Observation mission perform；
Wherein, each more excellent solution includes：
Perform the satellite mark of each task, observe start time point, observation end time point；
Start time point that each satellite is interacted with least one earth station, end time point.
And/or,
The modified neighborhood building method that processing implement body is performed is that new task is inserted to current solution sequence or it is replaced
In one or more tasks, thus construct new solution space；The new task of insertion or the task of replacement are：The user received in advance
Treat that at least one satellite performs the task for observation/pass down；
And/or, the adjusting type neighborhood building method that processing implement body is performed is to be to current solution sequence reallocation task
A certain observation mission among a certain satellite solution sequence is adjusted to the satellite to its another from a SEE time window
Time window.
Alternatively, the stopping criterion of dynamic change neighborhood tabu search algorithm includes：
Determine step number stop criterion：The current optimal solution recorded when step number reaches threshold value is exported as tabu search algorithm
Optimal solution；
Or,
FREQUENCY CONTROL principle：A certain solution sequence or target function value are used as the more excellent solution frequency of occurrences in iterative process
During beyond a given threshold value, terminate and calculate；
Or,
Target control principle：In given step number, current optimal value no longer changes, or the difference changed
Within a preset range, terminate and calculate.
Alternatively, the processor, specifically for：
Set taboo listInitial taboo list length From repeatedly
Generation number k=1 starts, and randomly selects an initial solution x in solution space0, and calculate the target function value f of initial solution
(x0)；
Initial solution x is obtained using modified neighborhood method0Neighborhood solution set N1(x), to n (x) ∈ N1(x), solution is suitable
Response function is f [n (x)], and n is filtered out according to f [n (x)]*(x), n*(x) it is set N1(x) fitness function value is caused most in
Big solution；
The selection rule of solution is as follows：
If 1.：n*(x)∈T*And n*(x) aspiration criterion is met, then makes x*=n*(x), n*(x)→T*；
If 2.：n*(x)∈T*And n*(x) aspiration criterion is unsatisfactory for, then makes x*=n'(x), and wherein f [n'(x)]=opt { f
[n(x)],n(x)∈(N1(x)-T*)}；
If 3.：Then make x*=n*(x), n*(x)→T*；
Judge whether to meet stopping criterion, stop output x if meeting*, otherwise to current x*Continue to use modified neighborhood
Building method produces disturbance, continues iteration；
Will be with n*(x) corresponding neighborhood moving method inserts taboo list T*In, set its Tabu Length to beAnd by taboo list T after follow-up iteration every time*In with n*(x) corresponding neighborhood movement side
The Tabu Length of method subtracts 1.
Alternatively, the processor, is additionally operable to：
Initial taboo list T*With initial solution x0, dynamic change taboo list lengthIterations
K=1 starts；It is random to use insertion new task or replace multitask method to x0Produce random perturbation generation neighborhood solution space N1(x),
In N1(x) a new more excellent solution j is obtained in1, judge whether to receive new more excellent solution j1；Iteration process is stopped until meeting
Then, the more excellent solution obtained when meeting stopping criterion is x to no-go gage*；
And,
Using reallocation task to meeting more excellent solution x during stopping criterion*Produce random perturbation, generation neighborhood solution space N2
(x), in N2(x) a new more excellent solution j is obtained in2, judge whether to receive new more excellent solution j2；Iteration process is until full
Sufficient stopping rule.
The present invention's becomes neighborhood tabu search algorithm processing remote sensing satellite earth observation mission planning problem using dynamic
Method, makes the solution performance of problem be significantly improved.Meanwhile, by the way that two class neighbour structures are used alternatingly, enhance algorithm
To the search capability and the ability for evading locally optimal solution of solution space, improve it and solve quality and efficiency.
Brief description of the drawings
Fig. 1 schematic diagrames that moonscope is interacted with earth station in the prior art；
Fig. 2 is the schematic diagram for the time window that present satellites are observed；
The method flow schematic diagram that Fig. 3 provides for one embodiment of the invention；
The schematic diagram for the optimal solution that Fig. 4 provides for one embodiment of the invention.
Embodiment
In order to preferably explain the present invention, in order to understand, below in conjunction with the accompanying drawings, by embodiment, to this hair
It is bright to be described in detail.
At present, remote sensing satellite earth observation needs to meet following constrain:
(1) imaging on a surface target must treat that satellite moves to the upper space-time progress of target in a certain track circle time,
Now the remote sensor of satellite can be within a period it can be seen that target, this period is referred to as time window (such as Fig. 2 institutes
Show).Within given planning horizon, general more than one time window between satellite and target, observation of the satellite to target need to be
Completed wherein within some time window, and the time window that target is observed will be generally less than visible time window, during observation
Between at the beginning of window between it is as shown in Figure 2 with the end time.
(2) satellites are in the observation mission of 2 successives of execution, and intermediate demand has certain transit time, with
Satellite remote sensor is allowed to perform adjustment.Earth station is when receiving satellite down-transmitting data as observation mission, and data down transmission is also required to
Completed within time window.
(3) in the time of switching on and shutting down each time, the side view adjustment number of times of satellite is limited.Side view adjustment number of times is to defend
The lateral swinging angle of star adjustment remote sensor is with observed object.
(4) there is memory on the star of a fixed capacity on satellite, satellite temporarily deposits the destination image data of observation
In memory.After data to be passed back to earth station, the memory capacity of memory is released.Therefore the real time capacity of memory
It is dynamic change in whole observation process.
(5) satellite during observed object and down-transmitting data all can consumed energy, and satellite is in each track
Workable energy is limited in circle time, therefore in scheduling process, the energy expenditure in each circle time is no more than maximum
Energy limitation.
Tabu search algorithm is one kind extension to local neighborhood search, by setting taboo list to be undergone to avoid some
Operation, and reward using aspiration criterion some excellent solutions, so as to realize the algorithm of global optimizing, tabu search algorithm when
Between complexity depend on the size of search neighborhood and determine mobile assessment cost.Due to tabu search algorithm be to single solution by
Step optimization, therefore algorithm performs efficiency is higher.Tabu search algorithm is accurate using more flexible storage organization and corresponding taboo
Then evade cyclic search, and discharge by aspiration criterion some solutions avoided, and then ensure the diversified algorithm of solution space
Locally optimal solution is jumped out, global optimization is finally realized.
Tabu search algorithm is a kind of Neighborhood-region-search algorithm, and it is from an initial solution, in the neighborhood of current initial solution
In screen candidate solution one by one, and find out optimal candidate solution.If the optimal candidate solution found out is better than current solution, displacement is current
Solution.If the optimal candidate solution found out is inferior to current solution, the candidate solution of optimal non-taboo is selected to replace current solution.
Tabu search algorithm is class algorithm with strong applicability, can be solved for many problems.It is being applied to remote sensing
In satellite task planning problem, it is usually required mainly for be concerned with the construction of coded system and neighborhood solution.
In addition, be briefly described below tabu search algorithm in terms of the satellite task planning problem on application, with preferable
Understand algorithm performs process.
In remote sensing satellite mission planning problem, using the coded system based on resource (satellite), i.e., task is united
One numbering, the task list establishment that satellite is imaged in track circle time is the coding of iteration.Such as a certain satellite Sat1 is one
Coding (i.e. one feasible solution) Sat1 in secondary iteration：10 → 2 → 4 → 42 → 5 → 27 expression Sat1 satellites successively execution the 10th,
2nd, 4,42,5,27 tasks.
In addition, for the particularity of remote sensing mission planning problem, designing a variety of neighbour structures, such as：1. neighborhood is inserted, will
Some Meta task is inserted into the task list of certain satellite as single observation activity；2. neighborhood is deleted, i.e., from some
Some observation activity is directly removed in moonscope effort scale；3. task neighborhood is replaced, i.e., is appointed the member that some is not arranged
Some Meta task arranged in current solution is replaced in business；4. reallocation task neighborhood, i.e., hand over two Meta tasks in current solution
Change place, order, realize that neighborhood is transformed.
Further, TABU search is Neighborhood-region-search algorithm, and the basis of its iteration is constantly to construct neighborhood solution.And every
Once construction neighborhood is solved simultaneously, can compare constraints, it is ensured that the neighborhood solution of composition is feasible solution.Therefore, for solving
The tabu search algorithm of remote sensing satellite mission planning problem is each time in iteration, and the neighborhood solution feasible by constructing is whole to realize
The iteration of body.
In conventional implementation, Tabu-Search Algorithm remote sensing satellite earth observation mission planning problem can be described such as
Under：
If whole search space is S, taboo list is T, and current solution is x, x ∈ S.If currently solving neighborhood disaggregation is combined into N
(x), wherein n (x) ∈ N (x), the fitness function of solution is f [x], if there is n*(x) so that：
f[n*(x)]=opt { f [n (x)], n (x) ∈ (N (x)-T) }
Then use n*(x) replace x as new solution, continue iteration.Said process is repeated, until meeting end condition.
In iterative process, if the movement of some neighborhood is selected, the move neighborhood is inserted into taboo list T, to avoid next iterative process
In be absorbed in local minimum.If f [n*(x) level] is sufficiently high, meets aspiration criterion, even if then n*(x) ∈ T, also select n*
(x) as current new explanation.
According to foregoing description, the basic procedure of tabu search algorithm can be summarized as：
Step1：Initialization algorithm parameter, produces initial solution x, makes x*=x,
That is, given algorithm parameter, randomly generates initial solution i, it is sky to put taboo list.
Step2：N (x) is constructed according to candidate solution building method；
Step3：N is filtered out according to f [n (x)]*(x),
If：n*(x) ∈ T and n*(x) aspiration criterion is met, then makes x*=n*(x), n*(x)→T；
If：n*(x) ∈ T and n*(x) aspiration criterion is unsatisfactory for, then makes x*=n'(x), and wherein f [n'(x)]=opt { f [n
(x)],n(x)∈(N(x)-T)}；
If：Then make x*=n*(x), n*(x)→T。
Step4：T is updated, the object of failure is removed；
Step5：Judge whether to meet end condition, be, terminate and export optimum results, otherwise turn Step2.
The following defect of presence of above-mentioned tabu search algorithm：
When 1. using Tabu-Search Algorithm remote sensing satellite earth observation mission planning problem, searched using fixed neighborhood
The effect that Cable Structure carries out TABU search is undesirable, and search speed is slower.
2. Tabu Length size is to influence the key parameter of tabu search algorithm performance.Prior art is in whole search procedure
The middle Tabu Length using fixation, the long increase amount of calculation of Tabu Length and influence algorithm operational efficiency, and Tabu Length mistake
It is short and be easily trapped into cyclic search state.
3. single radius of neighbourhood search is easily absorbed in Local Minimum, and all Searching Resolution Spaces can not can not find most
Excellent solution.
Therefore, the main object of the present invention is that Tabu-Search Algorithm process is improved to solve quality to improve it
And efficiency.
(1) the neighborhood search structure of the fixation used for former technical scheme, designs modified and the class of adjusting type two
Neighbour structure, by the way that two class neighbour structures are used alternatingly, enhance algorithm to the search capability of solution space and evades local optimum
The ability of solution.
(2) for original technology using fixed Tabu Length, the present invention combines modified neighborhood and adjusting type neighborhood, design
Dynamic becomes Tabu Length.I.e. when using modified neighborhood, shorter introduce taboo list length can be used to realize to search in the past
The concentration search in domain, and make current solution as early as possible close to some local minimizers number；When using adjusting type neighborhood, using longer taboo
List length is avoided, to promote search procedure quickly to reach other regions of search, so as to have an opportunity to look for preferably solution.
(3) searched for for the single radius of neighbourhood, selection change search radius is scanned for, that is, searching one continuously
After the constant optimal solution of several generations, judge whether whole solution space traversal, such as fail whole traversals, then expand search radius, until
Whole space traversals.So avoid to be absorbed in local optimum.Then optimal solution is found in whole solution space, search radius
Diminish, fine search is carried out in the scope of new optimal solution, until meeting end condition.
Seen over the ground using dynamic change neighborhood tabu search algorithm processing remote sensing satellite therefore, the embodiment of the present invention provides one kind
The method for surveying mission planning problem, as shown in figure 3, the method shown in Fig. 3 comprises the steps：
S1, when becoming neighborhood tabu search algorithm processing remote sensing satellite observation mission planning problem using dynamic, set and prohibit
The initial taboo list T avoided in searching algorithm*, initial taboo list lengthDynamic becomes neighborhood taboo list lengthWith
And initial solution x0, and make optimal solution be equal to initial solution x*=x0；
S2, since iterations k=1, according to initial taboo list T*, dynamic become taboo list lengthAnd just
The solution that begins x0, using modified neighborhood building method, perform the iterative process of tabu search algorithm；Taboo is met in iterative process to search
After the stopping criterion of rope algorithm, output meets optimal solution x during stopping criterion*；
S3, according to taboo list T*, dynamic become taboo list lengthIt is optimal when meeting stopping criterion in step S2
Solve x*, the iterative process of tabu search algorithm is performed using adjusting type neighborhood building method；
S4, meet after dynamic becomes the stopping criterion of neighborhood tabu search algorithm in step S3 iterative process, to last defeated
The optimal solution x gone out*Obtain what a more excellent solution to be output was planned as remote sensing satellite observation mission using local search algorithm
Optimal case.
The method of the present embodiment, makes the solution performance of problem be significantly improved.Meanwhile, it is adjacent by the way that two classes are used alternatingly
Domain structure, enhances search capability and the ability of evading locally optimal solution of the algorithm to solution space, improves it and solve quality and effect
Rate.
For example, foregoing step S2 may include：
Set taboo listInitial taboo list length From repeatedly
Generation number k=1 starts, and randomly selects an initial solution x in solution space0, and calculate the target function value f of initial solution
(x0)；
Initial solution x is obtained using modified neighborhood method0Neighborhood solution set N1(x), to n (x) ∈ N1(x), solution is suitable
Response function is f [n (x)], and n is filtered out according to f [n (x)]*(x), n*(x) it is set N1(x) fitness function value is caused most in
Big solution；
The selection rule of solution is as follows：
If 1.：n*(x)∈T*And n*(x) aspiration criterion is met, then makes x*=n*(x), n*(x)→T*；
If 2.：n*(x)∈T*And n*(x) aspiration criterion is unsatisfactory for, then makes x*=n'(x), and wherein f [n'(x)]=opt { f
[n(x)],n(x)∈(N1(x)-T*)}；
If 3.：Then make x*=n*(x), n*(x)→T*；
Judge whether to meet stopping criterion, stop output x if meeting*, otherwise to current x*Continue to use modified neighborhood
Building method produces disturbance, continues iteration；
Will be with n*(x) corresponding neighborhood moving method inserts taboo list T*In, set its Tabu Length to beAnd by taboo list T after follow-up iteration every time*In with n*(x) corresponding neighborhood movement side
The Tabu Length of method subtracts 1.
In another optional implementation, the step S2 of the method shown in foregoing Fig. 1 includes：
Initial taboo list T*With initial solution x0, initial taboo list lengthHere initial taboo list length
Setting can suitably be adjusted according to problem scale, dynamic become Tabu Length intoFrom iteration time
Number k=1 starts；It is random to use insertion new task or replace multitask method to x0Produce random perturbation generation neighborhood solution space N1
(x), in N1(x) a new more excellent solution j is obtained in1, judge whether to receive new more excellent solution j1；Iteration process is until full
Sufficient stopping rule, the more excellent solution obtained when meeting stopping criterion is x*；
Step S3 includes：
Using reallocation task to meeting more excellent solution x during stopping criterion in step S2*Random perturbation is produced, neighborhood is generated
Solution space N2(x), in N2(x) a new more excellent solution j is obtained in2, judge whether to receive new more excellent solution j2；Iteration mistake
Cheng Zhizhi meets stopping rule.
In the present embodiment, each more excellent solution may include：Perform satellite mark, the observation initial time of each task
Point, observation end time point；Start time point that each satellite is interacted with least one earth station, end time point.
Certainly, the above method may also include following step S5：
S5, assignment instructions corresponding with each satellite in the optimal case are sent into the satellite so that the satellite
Remote sensor according to planning observation mission perform.
The stopping criterion that dynamic becomes neighborhood tabu search algorithm has：
(1) step number stop criterion is determined：The current optimal solution recorded when step number reaches threshold value becomes neighborhood as dynamic and prohibited
Avoid the optimal solution of searching algorithm output；
(2) FREQUENCY CONTROL principle：More excellent solve being used as in iterative process of a certain solution sequence or target function value occurs
When frequency exceeds a given threshold value, terminate and calculate；
(3) target control principle：In given step number, current optimal value no longer changes, or change
Difference within a preset range, is terminated and calculated.
The content of embodiment for a better understanding of the present invention, first, for remote sensing satellite earth observation mission planning problem
It has been pre-designed modified neighborhood and adjusting type neighborhood is as follows：
(1) neighbour structure is designed
Neighbour structure is one of fundamental of tabu search algorithm, and the iteration development of TABU search is exactly by not
Break and search for more preferable solution in the neighborhood currently solved to realize.For the spy of remote sensing satellite earth observation mission planning problem
Point, devises following three kinds of different neighbour structures：
1. new task neighborhood (being a kind of modified neighborhood) is inserted
The effect of insertion new task neighborhood is the original new observation mission not arranged of insertion one into current solution i, is
Facilitate control, can further limit wait to catch into task scope and be inserted into task satellite resource scope.The neighborhood
Primarily directed to satellite resource within certain time may still it is available free complete more multitask the characteristics of design.
2. task neighborhood (being a kind of modified neighborhood) is replaced
The sight that the observation mission that the effect foot of replacement task neighborhood is not arranged with some has arranged come some in solution i before replacing
Survey task is controlled for convenience, can also further be limited the scope for the observation mission that can mutually replace and is replaced task institute
Satellite resource scope.The neighborhood be mainly designed to meter to following problematic features：Satellite resource in some time window,
It is possible to observe different observed objects by using different postures, but disposably can not observes simultaneously, one can only be selected.
If the replacing low priority of the task can be gone to be possible to make the quality of solution to be improved with the task of a high priority.
3. reallocation task neighborhood (being a kind of adjusting type neighborhood)
The effect of reallocation task neighborhood is the observation mission that two different satellites are exchanged in currently solution i, so as to realize
The satellite resource for performing observation mission is redistributed；Or the observation mission for performing certain satellite can from their one
See that time window is adjusted to another SEE time window, realize redistributing for single star internal observation task time window.
In above-mentioned three kinds of neighbour structures, first two is modified neighborhood search, can be by arranging more tasks, or use
High-priority task replaces low priority task, realizes the improvement to optimization aim.The third is adjusting type neighborhood search, essence
Upper is, to the adjustment for the position for having arranged task, optimization object function value not to be influenceed.
Although adjusting type neighborhood is not directly affected to optimization aim, by the adjustment to observation program, but it is possible to
Possibility is provided further to improve the quality solved using modified neighborhood, this is also exactly using the basis for becoming neighborhood search strategy.
(2) dynamic becomes Tabu Length
Tabu Length size is to influence the key parameter of tabu search algorithm performance.Tabu Length is that taboo object is not being examined
Do not allow to be selected to obtain maximum times in the case of worry aspiration criterion.The long increase amount of calculation of Tabu Length and influence algorithm operation
Efficiency, and Tabu Length is too short is easily trapped into cyclic search state.
For this problem, with reference to modified neighborhood and adjusting type neighborhood, the dynamic Tabu Length of designI.e. when iteration is initialIt is smaller, during using modified neighborhood, using shorter
Introduce taboo list length makes current solution as early as possible close to some local minimizers number to realize the concentration search to former region of search；
During using adjusting type neighborhood, as k values increase,Increase.Using longer introduce taboo list length, to promote search procedure
Other regions of search are quickly reached, so as to have an opportunity to look for preferably solution.
In addition, in the present embodiment, the new task of insertion or the task of replacement can be regarded as：The user received in advance treats at least
One satellite performs the task for observation/pass down；
Reallocation task can be regarded as：The observation mission that a certain satellite is performed is adjusted to another from a SEE time window
The task of one SEE time window.
Determine that dynamic becomes neighborhood Tabu-Search Algorithm remote sensing earth observation mission planning problem by above improvement project
Flow it is as follows：
Step 1：Initialization algorithm parameter, sets taboo listInitial taboo list lengthDynamic
Become Tabu LengthAnd initial solution x is randomly selected from solution space0, make optimal solution x*=
x0；
Step 2：Whether evaluation algorithm end condition meets.If meeting, terminate algorithm and export optimum results；Otherwise,
Perform step 3；
Step 3：According to the current more excellent solution x of modified neighborhood method generation*Neighborhood solution set N1(x) it is rightN is filtered out according to f [n (x)]*(x), screening technique is as follows：
If 1.：n*(x)∈T*And n*(x) aspiration criterion is met, then makes x*=n*(x), n*(x)→T*；
If 2.：n*(x)∈T*And n*(x) aspiration criterion is unsatisfactory for, then makes x*=n'(x), and wherein f [n'(x)]=opt { f
[n(x)],n(x)∈(N1(x)-T*)}；
If 3.：Then make x*=n*(x), n*(x)→T*；
Step 4：The Tabu Length is taken to beUpdate T*, and remove the object of failure；
Step 5：Judge whether to meet end condition, be, go to step 6, otherwise go to step 2.
Step 6：According to adjusting type neighborhood into currently more excellent solution x*Neighborhood solution set N2(x) it is rightAccording to f
[n (x)] filters out n*(x), screening technique is as follows：
If 1.：n*(x)∈T*And n*(x) aspiration criterion is met, then makes x*=n*(x), n*(x)→T*；
If 2.：n*(x)∈T*And n*(x) aspiration criterion is unsatisfactory for, then makes x*=n'(x), and wherein f [n'(x)]=opt { f
[n(x)],n(x)∈(N1(x)-T*)}；
If 3.：Then make x*=n*(x), n*(x)→T*；
Step 7：The Tabu Length is taken to beUpdate T*, remove the object of failure；
Step 8：Judge whether to meet end condition, be, go to step 9, otherwise go to step 6.
Step 9：Optimal solution to above-mentioned steps final output uses local search algorithm, until algorithm terminates to produce most
Excellent solution is used as the optimal solution for solving remote sensing satellite earth observation mission planning.
Currently, in actual applications, after the above method finds optimal case, it can perform following by the optimal case
In assignment instructions corresponding with each satellite send into the satellite so that the remote sensor of the satellite according to planning observation mission
Perform.
1st, neighbour structure is designed.The present invention is directly prohibited for tabu search algorithm using fixed neighborhood search structure
The effect for avoiding search is undesirable, and the slower result of search speed devises two kinds of modified neighbour structures and a kind of adjusting type neighborhood
Structure.
2nd, Tabu Length is become using dynamic.The present invention combines modified neighborhood and adjusting type neighborhood, during search
Employ dynamic and become Tabu Length.I.e. when using modified neighborhood, using shorter taboo list length；Adjacent using adjusting type
During domain, using longer introduce taboo list length.
3rd, selection change search radius is scanned for, i.e., after a constant optimal solution of constant generations is searched, and is judged
Whether whole solution space is traveled through, and is such as failed whole traversals, is then expanded search radius, until whole space traversals.Then whole
Optimal solution is found in solution space, search radius is diminished, fine search is carried out in the scope of new optimal solution, until meeting eventually
Only condition.
The above method enhances search capability of the algorithm to solution space；Algorithm has the energy for preferably evading locally optimal solution
Power, is difficult to be absorbed in local optimum；Elongated Tabu Length is more flexible than fixed Tabu Length, can improve algorithm operational efficiency again
Algorithm can be made to be difficult to be absorbed in cyclic search state；Algorithm for Solving better quality.
On the other hand, the present invention also provides a kind of device for handling remote sensing satellite earth observation mission planning, including：Receive
Device, the processor for connecting receiver；
Receiver receives the observation mission that at least one is performed with satellite remote sensor；
The processor becomes the planning that neighborhood tabu search algorithm handles remote sensing satellite earth observation task using dynamic, tool
Body includes：The initial taboo list T for setting dynamic to become in neighborhood tabu search algorithm*, initial taboo list lengthIt is dynamic
State becomes Tabu LengthAnd initial solution x0, and make optimal solution be equal to initial solution x*=x0；
According to initial taboo list T*, dynamic become taboo list lengthAnd initial solution x0,
Since iterations k=1, using modified neighborhood method, the iterative process that dynamic becomes neighborhood tabu search algorithm is performed；
Iterative process meets dynamic and become after the stopping criterion of neighborhood tabu search algorithm, and output meets optimal solution x during stopping criterion*；
According to taboo list T*, dynamic become taboo list lengthStopped based on above-mentioned satisfaction accurate
Optimal solution x when then*, the iterative process of tabu search algorithm is performed using adjusting type neighborhood method；
The iterative process performed based on adjusting type neighborhood method is met after the stopping criterion of tabu search algorithm, to last defeated
The optimal solution x gone out*A more excellent solution to be output is obtained using local search algorithm to advise as remote sensing satellite earth observation task
The optimal case drawn.
Specifically, said apparatus may also include：The transmitter being connected with processor；The transmitter is appointed each satellite
Business instruction is sent into the satellite, so that the remote sensor of satellite is performed according to the observation mission of planning.
For example, above-mentioned processor can be specifically for performing the content of foregoing any means embodiment, such as
Perform the content that abovementioned steps S2 may include：
Set taboo listInitial taboo list length From repeatedly
Generation number k=1 starts, and randomly selects an initial solution x in solution space0, and calculate the target function value f of initial solution
(x0)；
Initial solution x is obtained using modified neighborhood method0Neighborhood solution set N1(x), to n (x) ∈ N1(x), solution is suitable
Response function is f [n (x)], and n is filtered out according to f [n (x)]*(x), n*(x) it is set N1(x) fitness function value is caused most in
Big solution；
The selection rule of solution is as follows：
If 1.：n*(x)∈T*And n*(x) aspiration criterion is met, then makes x*=n*(x), n*(x)→T*；
If 2.：n*(x)∈T*And n*(x) aspiration criterion is unsatisfactory for, then makes x*=n'(x), and wherein f [n'(x)]=opt { f
[n(x)],n(x)∈(N1(x)-T*)}；
If 3.：Then make x*=n*(x), n*(x)→T*；
Judge whether to meet stopping criterion, stop output x if meeting*, otherwise to current x*Continue to use modified neighborhood
Building method produces disturbance, continues iteration；
Will be with n*(x) corresponding neighborhood moving method inserts taboo list T*In, set its Tabu Length to beAnd by taboo list T after follow-up iteration every time*In with n*(x) corresponding neighborhood movement side
The Tabu Length of method subtracts 1.
Or, the description below that computing device abovementioned steps S2 includes：
Initial taboo list T*With initial solution x0, initial taboo list lengthHere initial taboo list length
Setting can suitably be adjusted according to problem scale, dynamic become Tabu Length intoFrom iteration time
Number k=1 starts；It is random to use insertion new task or replace multitask method to x0Produce random perturbation generation neighborhood solution space N1
(x), in N1(x) a new more excellent solution j is obtained in1, judge whether to receive new more excellent solution j1；Iteration process is until full
Sufficient stopping rule, the more excellent solution obtained when meeting stopping criterion is x*；
Step S3 includes：
Using reallocation task to meeting more excellent solution x during stopping criterion in step S2*Random perturbation is produced, neighborhood is generated
Solution space N2(x), in N2(x) a new more excellent solution j is obtained in2, judge whether to receive new more excellent solution j2；Iteration mistake
Cheng Zhizhi meets stopping rule.
Further, the stopping criterion of the dynamic change neighborhood tabu search algorithm in the present embodiment may include：
Determine step number stop criterion：The current optimal solution recorded when step number reaches threshold value becomes neighborhood taboo as dynamic and searched
The optimal solution of rope algorithm output；
Or,
FREQUENCY CONTROL principle：A certain solution sequence or target function value are used as the more excellent solution frequency of occurrences in iterative process
During beyond a given threshold value, terminate and calculate；
Or,
Target control principle：In given step number, current optimal value no longer changes, or the difference changed
Within a preset range, terminate and calculate.
Wherein, each more excellent solution includes：
Perform the satellite mark of each task, observe start time point, observation end time point；
Start time point that each satellite is interacted with least one earth station, end time point and/or, the new task of insertion
Or replacing for task is：The user received in advance treats that at least one satellite performs the task for observation/pass down；
Reallocation task is：The observation mission that a certain satellite is performed is adjusted to another from a SEE time window can
See the task of time window.
Those skilled in the art can be understood that, for convenience and simplicity of description, only with above-mentioned each functional module
Division progress for example, in practical application, can distribute complete by different functional modules by above-mentioned functions as needed
Into the internal structure of device being divided into different functional modules, to complete all or part of function described above.On
The specific work process of the device of description is stated, the corresponding process in preceding method embodiment is may be referred to, will not be repeated here.
Finally it should be noted that：Above-described embodiments are merely to illustrate the technical scheme, rather than to it
Limitation；Although the present invention is described in detail with reference to the foregoing embodiments, it will be understood by those within the art that：
It can still modify to the technical scheme described in previous embodiment, or which part or all technical characteristic are entered
Row equivalent substitution；And these modifications or substitutions, the essence of appropriate technical solution is departed from various embodiments of the present invention technical side
The scope of case.
Claims (10)
1. a kind of remote sensing satellite observation mission planing method, it is characterised in that methods described is to become neighborhood taboo using dynamic to search
The method of rope algorithm process remote sensing satellite observation mission planning problem, method includes：
S1, when becoming neighborhood tabu search algorithm processing remote sensing satellite observation mission planning problem using dynamic, set taboo to search
Initial taboo list T in rope algorithm*, initial taboo list lengthDynamic becomes neighborhood taboo list lengthAnd just
The solution that begins x0, and make optimal solution be equal to initial solution x*=x0；
S2, since iterations k=1, according to initial taboo list T*, dynamic become taboo list lengthAnd initial solution
x0, using modified neighborhood building method, perform the iterative process of tabu search algorithm；TABU search is met in iterative process to calculate
After the stopping criterion of method, output meets optimal solution x during stopping criterion*；
S3, according to taboo list T*, dynamic become taboo list lengthOptimal solution x when meeting stopping criterion in step S2*,
The iterative process of tabu search algorithm is performed using adjusting type neighborhood building method；
S4, step S3 iterative process meet dynamic become neighborhood tabu search algorithm stopping criterion after, to what is finally exported
Optimal solution x*Using local search algorithm obtain a more excellent solution to be output as remote sensing satellite observation mission plan it is optimal
Scheme.
2. according to the method described in claim 1, it is characterised in that step S2 includes：
Set taboo listInitial taboo list length From iteration time
Number k=1 starts, and randomly selects an initial solution x in solution space0, and calculate the target function value f (x of initial solution0)；
Initial solution x is obtained using modified neighborhood method0Neighborhood solution set N1(x), to n (x) ∈ N1(x), the fitness of solution
Function is f [n (x)], and n is filtered out according to f [n (x)]*(x), n*(x) it is set N1(x) fitness function value maximum is caused in
Solution；
The selection rule of solution is as follows：
If 1.：n*(x)∈T*And n*(x) aspiration criterion is met, then makes x*=n*(x), n*(x)→T*；
If 2.：n*(x)∈T*And n*(x) aspiration criterion is unsatisfactory for, then makes x*=n'(x), and wherein f [n'(x)]=opt { f [n
(x)],n(x)∈(N1(x)-T*)}；
If 3.：Then make x*=n*(x), n*(x)→T*；
Judge whether to meet stopping criterion, stop output x if meeting*, otherwise to current x*Continue using modified neighborhood construction
Method produces disturbance, continues iteration；
Will be with n*(x) corresponding neighborhood moving method inserts taboo list T*In, set its Tabu Length to beAnd by taboo list T after follow-up iteration every time*In with n*(x) corresponding neighborhood movement side
The Tabu Length of method subtracts 1.
3. according to the method described in claim 1, it is characterised in that step S2 includes：
Initial taboo list T*With initial solution x0, dynamic change taboo list lengthIterations k=0
Start；It is random to use insertion new task or replace multitask method to x0Produce random perturbation generation neighborhood solution space N1(x), in N1
(x) a new more excellent solution j is obtained in1, judge whether to receive new more excellent solution j1；Iteration process stops rule until meeting
Then, the more excellent solution obtained when meeting stopping criterion is x*；
Step S3 includes：
Using reallocation task to meeting more excellent solution x during stopping criterion in step S2*Random perturbation is produced, generation neighborhood solution is empty
Between N2(x), in N2(x) a new more excellent solution j is obtained in2, judge whether to receive new more excellent solution j2；Iteration process is straight
To meeting stopping rule.
4. the method according to claim 1 or 3, it is characterised in that dynamic becomes the stopping criterion of neighborhood tabu search algorithm
Including：
Determine step number stop criterion：The current optimal solution recorded when step number reaches threshold value becomes neighborhood TABU search as dynamic and calculated
The optimal solution of method output；
Or,
FREQUENCY CONTROL principle：A certain solution sequence or target function value as in iterative process it is more excellent solution the frequency of occurrences exceed
During one given threshold value, terminate and calculate；
Or,
Target control principle：In given step number, current optimal value no longer changes, or the difference changed is pre-
If in scope, terminating and calculating.
5. according to any described method of claims 1 to 3, it is characterised in that
Each more excellent solution includes：
Perform the satellite mark of each task, observe start time point, observation end time point；
Start time point that each satellite is interacted with least one earth station, end time point；
And/or,
Modified neighborhood building method is that new task is inserted to current solution sequence or wherein one or more tasks are replaced, by
This constructs new solution space；The new task of insertion or the task of replacement are：The user received in advance treats that at least one satellite is performed
Observe/passing down for task；
Adjusting type neighborhood building method is that being will be a certain among a certain satellite solution sequence to current solution sequence reallocation task
Observation mission is adjusted to the satellite to its another SEE time window from a SEE time window；
And/or,
Methods described also includes：
Assignment instructions corresponding with each satellite in the optimal case are sent into the satellite so that the remote sensor of the satellite
Performed according to the observation mission of planning.
6. a kind of device for handling the planning of remote sensing satellite observation mission, it is characterised in that including：
Receiver, the processor for connecting receiver；
Receiver receives the observation mission that at least one is performed with satellite remote sensor；
The processor becomes the planning that neighborhood tabu search algorithm handles remote sensing satellite observation mission using dynamic, specifically includes：
When becoming neighborhood tabu search algorithm processing remote sensing satellite observation mission planning problem using dynamic, set in tabu search algorithm
Initial taboo list T*, initial taboo list lengthDynamic becomes neighborhood taboo list lengthAnd initial solution x0, and
Optimal solution is made to be equal to initial solution x*=x0；
Since iterations k=1, according to initial taboo list T*, dynamic become taboo list lengthAnd initial solution x0,
Using modified neighborhood building method, the iterative process of tabu search algorithm is performed；Tabu search algorithm is met in iterative process
Stopping criterion after, optimal solution x when output meets stopping criterion*；
According to taboo list T*, dynamic become taboo list lengthOptimal solution x when meeting stopping criterion in step S2*, adopt
The iterative process of tabu search algorithm is performed with adjusting type neighborhood building method；
It is optimal to what is finally exported after the stopping criterion that previous step iterative process meets dynamic change neighborhood tabu search algorithm
Solve x*The optimal case that a more excellent solution to be output is planned as remote sensing satellite observation mission is obtained using local search algorithm.
7. device according to claim 6, it is characterised in that also include：The transmitter being connected with processor；
The transmitter sends the assignment instructions of each satellite into the satellite, so that sight of the remote sensor of satellite according to planning
Survey tasks carrying；
Wherein, each more excellent solution includes：
Perform the satellite mark of each task, observe start time point, observation end time point；
Start time point that each satellite is interacted with least one earth station, end time point.
And/or,
The modified neighborhood building method that processing implement body is performed is that new task or replacement wherein one are inserted to current solution sequence
Individual or multiple tasks, thus construct new solution space；The new task of insertion or the task of replacement are：The user received in advance treat to
A few satellite performs the task for observation/pass down；
And/or, the adjusting type neighborhood building method that processing implement body is performed is, to current solution sequence reallocation task i.e. by certain
A certain observation mission is adjusted to the satellite to its another SEE time from a SEE time window among one satellite solution sequence
Window.
8. the device according to claim 6 or 7, it is characterised in that dynamic becomes the stopping criterion of neighborhood tabu search algorithm
Including：
Determine step number stop criterion：The current optimal solution recorded when step number reaches threshold value is exported most as tabu search algorithm
Excellent solution；
Or,
FREQUENCY CONTROL principle：A certain solution sequence or target function value as in iterative process it is more excellent solution the frequency of occurrences exceed
During one given threshold value, terminate and calculate；
Or,
Target control principle：In given step number, current optimal value no longer changes, or the difference changed is pre-
If in scope, terminating and calculating.
9. device according to claim 7, it is characterised in that the processor, specifically for：
Set taboo listInitial taboo list length From iteration time
Number k=1 starts, and randomly selects an initial solution x in solution space0, and calculate the target function value f (x of initial solution0)；
Initial solution x is obtained using modified neighborhood method0Neighborhood solution set N1(x), to n (x) ∈ N1(x), the fitness of solution
Function is f [n (x)], and n is filtered out according to f [n (x)]*(x), n*(x) it is set N1(x) fitness function value maximum is caused in
Solution；
The selection rule of solution is as follows：
If 1.：n*(x)∈T*And n*(x) aspiration criterion is met, then makes x*=n*(x), n*(x)→T*；
If 2.：n*(x)∈T*And n*(x) aspiration criterion is unsatisfactory for, then makes x*=n'(x), and wherein f [n'(x)]=opt { f [n
(x)],n(x)∈(N1(x)-T*)}；
If 3.：Then make x*=n*(x), n*(x)→T*；
Judge whether to meet stopping criterion, stop output x if meeting*, otherwise to current x*Continue using modified neighborhood construction
Method produces disturbance, continues iteration；
Will be with n*(x) corresponding neighborhood moving method inserts taboo list T*In, set its Tabu Length to beAnd by taboo list T after follow-up iteration every time*In with n*(x) corresponding neighborhood movement side
The Tabu Length of method subtracts 1.
10. device according to claim 9, it is characterised in that the processor, is additionally operable to：
Initial taboo list T*With initial solution x0, dynamic change taboo list lengthIterations k=1
Start；It is random to use insertion new task or replace multitask method to x0Produce random perturbation generation neighborhood solution space N1(x), in N1
(x) a new more excellent solution j is obtained in1, judge whether to receive new more excellent solution j1；Iteration process stops rule until meeting
Then, the more excellent solution obtained when meeting stopping criterion is x*；
And,
Using reallocation task to meeting more excellent solution x during stopping criterion*Produce random perturbation, generation neighborhood solution space N2(x),
In N2(x) a new more excellent solution j is obtained in2, judge whether to receive new more excellent solution j2；Iteration process is stopped until meeting
No-go gage is then.
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108090630A (en) * | 2018-01-22 | 2018-05-29 | 合肥工业大学 | More star contingency tasks method and device for planning |
| CN108171374A (en) * | 2017-12-27 | 2018-06-15 | 中国电子科技集团公司第五十四研究所 | A kind of earth observation satellite mission planning method based on simulated annealing |
| CN109857937A (en) * | 2019-01-25 | 2019-06-07 | 同济大学 | One kind being based on Sine mapping and segmented continuous TABU search data processing method parallel |
| CN110378639A (en) * | 2018-09-06 | 2019-10-25 | 北京京东尚科信息技术有限公司 | Distribution route method and system for planning |
| CN110456387A (en) * | 2019-08-14 | 2019-11-15 | 上海卫星工程研究所 | Active remote sensing satellite establishes barrier tapes to the method for aircraft search |
| CN111062561A (en) * | 2019-11-05 | 2020-04-24 | 合肥工业大学 | AHP ideal target point solving method and system for multi-target satellite task planning |
| CN111178419A (en) * | 2019-12-24 | 2020-05-19 | 上海交通大学 | Agile remote sensing satellite multi-target task planning method based on task clustering |
| CN111581580A (en) * | 2020-04-23 | 2020-08-25 | 暨南大学 | Ferry service network optimization method based on variable neighborhood descent hybrid algorithm |
| CN111669794A (en) * | 2020-06-18 | 2020-09-15 | 南京邮电大学 | Variable neighborhood searching method for solving wireless network base station switching minimization problem |
| CN112070370A (en) * | 2020-08-21 | 2020-12-11 | 中南大学 | Relay satellite task planning method, system and storage medium |
| CN112235216A (en) * | 2020-10-16 | 2021-01-15 | 哈尔滨工程大学 | Compressed sensing pilot frequency design method based on tabu search |
| CN113313348A (en) * | 2021-04-20 | 2021-08-27 | 合肥工业大学 | Satellite task planning method and device, storage medium and electronic equipment |
| CN116629190A (en) * | 2023-07-21 | 2023-08-22 | 西安智多晶微电子有限公司 | FPGA layout method based on cellular automaton and tabu search |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101984412A (en) * | 2010-10-13 | 2011-03-09 | 北京航空航天大学 | Method for scheduling parallel test tasks based on grouping and tabu search |
| US20120203728A1 (en) * | 2000-09-06 | 2012-08-09 | Masterlink Corporation | System and method for managing mobile workers |
| WO2014205585A1 (en) * | 2013-06-28 | 2014-12-31 | Polyvalor, Société En Commandite | Method and system for optimizing the location of data centers or points of presence and software components in cloud computing networks using a tabu search algorithm |
| CN105512479A (en) * | 2015-12-03 | 2016-04-20 | 中国地质大学（武汉） | Evaluation method and device of multi-satellite earth observation task planning algorithms |
-
2017
- 2017-06-05 CN CN201710415442.6A patent/CN107239661B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120203728A1 (en) * | 2000-09-06 | 2012-08-09 | Masterlink Corporation | System and method for managing mobile workers |
| CN101984412A (en) * | 2010-10-13 | 2011-03-09 | 北京航空航天大学 | Method for scheduling parallel test tasks based on grouping and tabu search |
| WO2014205585A1 (en) * | 2013-06-28 | 2014-12-31 | Polyvalor, Société En Commandite | Method and system for optimizing the location of data centers or points of presence and software components in cloud computing networks using a tabu search algorithm |
| CN105512479A (en) * | 2015-12-03 | 2016-04-20 | 中国地质大学（武汉） | Evaluation method and device of multi-satellite earth observation task planning algorithms |
Non-Patent Citations (1)
| Title |
|---|
| 陈英武 等: ""卫星任务调度问题的约束规划模型"", 《国防科技大学学报》 * |
Cited By (20)
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| CN108090630B (en) * | 2018-01-22 | 2020-09-01 | 合肥工业大学 | Multi-satellite emergency task planning method and device |
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| CN113313348B (en) * | 2021-04-20 | 2022-09-30 | 合肥工业大学 | Satellite task planning method and device, storage medium and electronic equipment |
| CN116629190A (en) * | 2023-07-21 | 2023-08-22 | 西安智多晶微电子有限公司 | FPGA layout method based on cellular automaton and tabu search |
| CN116629190B (en) * | 2023-07-21 | 2023-11-03 | 西安智多晶微电子有限公司 | FPGA layout method based on cellular automaton and tabu search |
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