CN106485349A - A kind of distribution method of tour time - Google Patents

A kind of distribution method of tour time Download PDF

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Publication number
CN106485349A
CN106485349A CN201610851306.7A CN201610851306A CN106485349A CN 106485349 A CN106485349 A CN 106485349A CN 201610851306 A CN201610851306 A CN 201610851306A CN 106485349 A CN106485349 A CN 106485349A
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China
Prior art keywords
task
tour
list
distribution
time
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CN201610851306.7A
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Chinese (zh)
Inventor
张贵峰
周筑博
张娟
张巍
杨鹤猛
吴新桥
陈艳芳
赵克
王兵
王诗奎
谷连军
Original Assignee
南方电网科学研究院有限责任公司
中国南方电网有限责任公司电网技术研究中心
天津航天中为数据系统科技有限公司
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Priority to CN201610851306.7A priority Critical patent/CN106485349A/en
Publication of CN106485349A publication Critical patent/CN106485349A/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/004Artificial life, i.e. computers simulating life
    • G06N3/006Artificial life, i.e. computers simulating life based on simulated virtual individual or collective life forms, e.g. single "avatar", social simulations, virtual worlds or particle swarm optimisation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • G06Q10/0631Resource planning, allocation or scheduling for a business operation
    • G06Q10/06316Sequencing of tasks or work

Abstract

Embodiments of the invention provide a kind of distribution method of tour time, are related to task scheduling field of cruising, and are capable of the tour time of reasonable arrangement tour task.Concrete scheme includes:Target component list is obtained, the target component list includes task list and weather information list;Synoptic model is set up according to the weather information list;According to the management and control rank of each task in the task list, to each task, corresponding interim landing point is ranked up in the region;Order according to the synoptic model and interim landing point determines constraints, is that each task distributes tour time in the task list according to the constraints.The present invention is used for distributing tour time for making an inspection tour task.

Description

A kind of distribution method of tour time

Technical field

Embodiments of the invention are related to task scheduling field of cruising, more particularly to a kind of distribution method of tour time.

Background technology

Cruise task includes each region in multiple regions to be carried out once or repeatedly make an inspection tour, and cruise task assignment period Usually 1 year.

With the continuous progress of science and technology, cruise task becomes complicated all the more, and the distribution that repeatedly makes an inspection tour on a timeline is also got over Send out intensive, affect that the factor of tour time distribution is also more and more, these factors include the setting up of no-fly zone, weather condition, pipe Control rank etc..Under current complicated cruise applied environment, traditional tour time distribution method can not expire well Sufficient actual conditions, the excessively intensive situation of cruise task for cruise time conflict, some months often occur, therefore need badly to making an inspection tour Time makes scientific and reasonable arrangement, to reduce the conflict of cruise time, satisfactory completes cruise task.

Content of the invention

Embodiments of the invention provide a kind of distribution method of tour time, all tour can appoint in reasonable arrangement 1 year The tour time of business.

In order to reach above-mentioned purpose, the present invention provides a kind of distribution method of tour time, including:

Target component list is obtained, the target component list includes task list and weather information list;

Synoptic model is set up according to the weather information list;

According to the management and control rank of each task in the task list, the interim landing point corresponding in region to each task It is ranked up;

Order according to the synoptic model and interim landing point determines constraints, is institute according to the constraints State each task in task list and distribute tour time.

The distribution method of the tour time provided by embodiments of the invention, according to the management and control rank of task to interim landing Point is ranked up, for arranging tour time according to the sequence of landing point;Then further according to constraints by task Tour time was assigned on concrete month.In practical application scene, some tasks only need to single tour, and some then need at least Make an inspection tour twice, for both of which can by being limited the time that is maked an inspection tour with reasonable distribution each time to constraints, And then the tour time each to the multiple tasks in multiple regions, a plurality of circuit does rational arrangement, to reduce cruise time punching Prominent, balanced each month task amount, cruise task is completed so as to satisfactory.

Description of the drawings

In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, embodiment will be described below Needed for accompanying drawing to be used be briefly described, it should be apparent that, drawings in the following description be only the present invention some Embodiment, for those of ordinary skill in the art, on the premise of not paying creative work, can also be attached according to these Figure obtains other accompanying drawings.

The distribution method schematic flow sheet of the tour time that Fig. 1 is provided by embodiments of the invention;

Fig. 2 is the result schematic diagram for reading in task list in running example;

Fig. 3 is the result schematic diagram for reading in weather information list in running example;

Fig. 4 is the result schematic diagram of the historical data for reading in task deployment information in running example;

Fig. 5 is the result schematic diagram for reading in no-fly zone information in running example;

Fig. 6 is last output result schematic diagram in running example.

Specific embodiment

Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete Site preparation is described, it is clear that described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.It is based on Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made Embodiment, belongs to the scope of protection of the invention.

Embodiment

Embodiments of the invention provide a kind of distribution method of tour time, in conjunction with shown in Fig. 1, comprise the following steps:

101st, target component list is obtained.

Target component list includes task list, and it is as shown in table 1 that task list reads in parameter of regularity.

Table 1

Target component list also includes weather information list, and it is as shown in table 2 that parameter of regularity is read in weather information list.

Table 2

After obtaining target component list, it is that each task distributes tour time in task list according to target component list, The process completes the distribution of tour time with ant group algorithm and particle algorithm based on Dynamic Programming.To ant group algorithm and particle Group's algorithm and Dynamic Programming are described as follows:

1. ant group algorithm and population are calculated

Ant group algorithm is the simulation of ant communities food collection process, be by Marco Dorigo in 1992 in his rich Propose in scholar's paper, its Inspiration Sources finds the behavior in path during search of food in ant.Ant group algorithm is a kind of mould Intend evolution algorithm, preliminary research shows that the algorithm has many excellent properties.For proportional, integral-derivative, (English is complete Claim:Proportion integral derivative, English abbreviation:PID) optimization design of controller parameters problem, by ant colony The result of algorithm design is compared with the result of genetic Algorithm Design, and Numerical Simulation Results show, ant group algorithm has one Plant validity and the using value of new Simulating Evolution optimization method.

Particle cluster algorithm is that flock of birds is looked for food the simulation of process, and particle cluster algorithm takes a hint and for solving from this model Certainly optimization problem.In particle cluster algorithm, the solution of each optimization problem is a bird in search space.We term it " grain Son ".All of particle has an adaptive value determined by optimised function (English:Fitnessvalue), each particle Also one speed determines the direction and distance that they circle in the air.Then particles just follow current optimal particle in solution space Search.

As swarm intelligence algorithm uses probability search method, ant group algorithm and particle cluster algorithm have common excellent Point:

1) robustness:As algorithm is nothing centralized Control control constraints, will not affect entirely to ask because of the fault of individual one The solution of topic;

2) autgmentability:Information interchange mode is non-direct, and communication overhead is few;

3) parallel parsing:Multiprocessor can be made full use of, the working condition being suitable under network environment;

4) mathematical characteristic of particular problem need not be relied in optimization process, for example can be micro-, linear etc.;

5) algorithm is simply easily realized:In system, individual capability is simple, executes the time short;

In addition, particle cluster algorithm also has the advantage that:

1) collective search, and with memory function, retain individual and global optimal information;

2) collaboratively searching, while instructed using individual and global optimal information search further for.

Meanwhile, ant group algorithm and particle cluster algorithm there is also limitation:

1) optimize performance and parameter setting is largely dependent upon, affected by initial value larger.Distribute in the present embodiment During tour time, initial parameter setting more accurately, can exclude this weakness depending on history cruise data;

2) Premature Convergence is easily produced.

Ant group algorithm is substantially suitable for solving discrete combination optimization problem, on traveling salesman problem after successful application Other field is penetrated into successively.Reach in combinatorial optimization problems such as appointment, scheduling, subset, belt restraining satisfactions efficient excellent Change performance.And graph coloring, circuit design, quadratic assignment problem, data clusters analysis, weapon attacking Target Assignment and optimization, VLSI Design, network route optimization, data mining, vehicle path planning, regional radio frequency are divided automatically Join, gather covering etc. optimization field obtained successful Application.If there is the individuality of numerous nothings intelligence in certain colony, they pass through The intelligent behavior showed by simple cooperation each other is referred to as swarm intelligence (English:Swarm Intelligence).Exchange on internet, but more neurons connection (human brain) are interacted by internet As a result, optical cable and router are only the extensions of aixs cylinder and cynapse.From in the angle of self organization phenomenon, the intelligence of human brain and ant Group does not have difference substantially yet, and intelligence can not say that single ant does not have yet to single neuron, but formed by connection System, is an intelligent body.

2. Dynamic Programming

Dynamic Programming is a branch of operational research, is to solve for decision process (English:Decision process) optimum The mathematical method of change.Early 1950s U.S. mathematician R.E.Bellman et al. is in research multistage decision process (English Text:Multistep decision process) optimization problem when, it is proposed that famous principle of optimality (English: Principle of optimality), multistage process is converted into a series of single phase problems, is solved one by one, found and understand The new method Dynamic Programming of certainly this kind of process optimization problem.Nineteen fifty-seven has published his masterpiece Dynamic Programming, this are the first works in the field.

Dynamic programming be to solving a kind of approach of optimization problem, a kind of method, rather than a kind of special calculation Method.Unlike those search above or numerical computations, mathematic(al) representation with a standard and clear and definite clearly solve a problem Method.Dynamic programming is often directed to a kind of optimization problem, as the property of various problems is different, determines optimum The condition of solution is also different, thus the method for designing of Dynamic Programming has, to different problems, the solution approach for differing from one another, and There is no a kind of omnipotent dynamic programming algorithm, all kinds of optimization problems can be solved.Therefore in application process except will be to base Outside this concept and method correct understanding, it is necessary to which particular problem concrete analysis is processed, go to set up model with abundant imagination, with wound The skill of the property made goes to solve.

Basic thought is similar with divide and conquer, and PROBLEM DECOMPOSITION to be solved is several subproblems (stage), by suitable Sequence solves sub, and the solution of previous subproblem, the solution of a subproblem after being provide useful information.Ask arbitrary son is solved During topic, various possible local solutions are listed, those local solutions for being possible to reach optimum are retained by decision-making, abandons other local Solution.Each subproblem is solved successively, and last subproblem is exactly the solution of initial problem.

In the present embodiment, using ant group algorithm and particle algorithm, start to consider from each basic individuality, while considering The experience value of the system state in which after each individuality transfer, looks for optimal path and state branch mode, is applied to It is mainly reflected in consider the arrangement time of each tour during distribution tour time, under conditions of meet the constraint, distribution During tour time, whether the state transfer for considering whole system is optimum branch mode, and the process includes step 102-104.

102nd, synoptic model is set up according to weather information list.

Weather information is modeled according to history meteorological condition, by considering the information such as monthly total precipitation, by the gas of 1 year Image information be created as can calculation expression form, least unit is accurate to the moon, is monthly initialized as 30 days.Further, also Working day factor can be taken into account to do synoptic model and optimize.

103rd, according to the management and control rank of each task in task list, the interim landing point corresponding in the region to each task It is ranked up.

Each task has health degree attribute and importance attribute, generally high for annual management and control rank is put into the more early moon Part, that is to say, that the high task of control rank is completed as early as possible.

In the present embodiment, traversal is assigned to the task of an interim landing point first, calculates the management and control rank of each task; Then by the highest management and control rank of the task of interim landing point, as the management and control rank corresponding to interim landing point;According still further to facing When landing point corresponding management and control rank the interim landing point in region is ranked up.If the corresponding pipe of interim landing point Control rank is high, then preferential execution is assigned to the task of the interim landing point.

104th, task is assigned to concrete month.

Synoptic model consider precipitation, monthly can the factor such as flight number of days, can be calculated according to flight number of days monthly theoretical Can be used for make an inspection tour time span, it is ensured that less than the aircraft monthly can flight capacity.

The order of interim landing point considers the management and control rank of different task, that is, execute the order of priority of task.

During distribution tour time, the order according to synoptic model and interim landing point determines constraints, according still further to about Bundle condition is that each task distributes tour time in task list, and task is assigned to concrete month.

In a kind of specific embodiment, constraints includes:Sequence according to interim landing point is to interim in region Executing needed for landing point for task is maked an inspection tour;Task to an interim landing point, according to management and control rank from high to low suitable Sequence is maked an inspection tour, and in the case of management and control rank identical, is maked an inspection tour circuit of the number of times more than 1 and is preferentially maked an inspection tour;In region each The production plan amount arranged by the moon is no more than the workload upper limit.

For the task maked an inspection tour at least twice by needs, constraints can further include:Second of task Not less than K month, K was preset value to time interval between making an inspection tour and making an inspection tour for the first time, generally takes 4.For being unable to meet the constraint The task of condition need to carry out local directed complete set.

According to constraints above condition, the month in synoptic model is traveled through according to the sequencing in month successively, one is appointed The tour time of business is arranged into the month of meet the constraint condition.

On the premise of meet the constraint condition, task distribution should try not to focus on very much a month, and answer task equal Weighing apparatusization is distributed.

105th, determine the first time range that makes an inspection tour then.

Target component list can also include the historical data of task deployment information, for providing the Historical Jobs time.Go through It is as shown in table 3 that history data read in parameter of regularity.

Table 3

After being assigned to the tour time of all tasks in region, probabilistic model is built to existing according to historical data Task arrangement provides certain aid decision, including according to the line inspection time in historical data, determining first then tour The time range of same circuit.

106th, output no-fly zone information.

Target component list can also include no-fly zone information, for providing the description information to no-fly zone position, for example The information such as the position coordinates of no-fly zone.It is as shown in table 4 that no-fly zone information reads in parameter of regularity.

Table 4

After being assigned to the tour time of all tasks in region, check whether all circuits have shaft tower region to belong to taboo Winged area, when determination is routed through no-fly zone, exports no-fly zone information, no-fly zone information be used for indicating circuit with The lap position of no-fly zone.

As in the circuit that cruises, all of coordinate all at the earth's surface, needs to solve the distance between coordinate intersection problems, In the relatively bad solution of solid geometry category.Reasonable analogy is then passed through, elliposoidal spherical coordinate is mapped to flat square seat In mark system, main cause has:The earth is cut from equator, disc is similar to, easy solve problem;In the category of several kms, ground The concavo-convex degree of ball surface less, can approximately be analogous to plane;Chinese territory concentrates on the subregion of east longitude and north latitude, projection Solve problem is easier to rectangular coordinate system;The all points of cruise circuit fall at the earth's surface to going up, and project to plane right-angle coordinate Inside it is unlikely to cause overlap a little.Consider factors above, spheric coordinate system is projected to plane right-angle coordinate actually bright The act of intelligence.Formula specific as follows:

X'=cosXcosY, Y'=cosXsinY

Wherein X is dimension, and Y is longitude, and X ' is the abscissa after being transformed into plane right-angle coordinate, and Y ' is for being transformed into plane Ordinate after rectangular coordinate system.After conversion, it is possible to take the relevant knowledge of plane geometry to enter row operation.

107th, tour time is added in task list.

After being assigned to the tour time of all tasks in region, the tour time that distributes for task is added to task In list, output with the addition of the task list of tour time.

Based on the distribution method of the tour time described by above-mentioned steps, specific running example is described as follows:

Used as the |input paramete of algorithm, for reading in the result of task list, accompanying drawing 3 is accompanying drawing 2 data that space flight is provided The result of weather information list is read in, accompanying drawing 4 is the result of the historical data of reading task deployment information, accompanying drawing 5 is prohibited for reading in The result of winged area's information, last output result is as shown in Figure 6.

The task of distributing to the interim landing point is included in each interim landing point, while in each task IntendJobTime field represents the tour time for the task distribution generated by algorithm.As shown in fig. 6, circuit number Task for 60 is dispensed on January tour.

The distribution method of the tour time provided by embodiments of the invention, according to the management and control rank of task to interim landing Point is ranked up, for arranging tour time according to the sequence of landing point;Then further according to constraints by task Tour time was assigned on concrete month.In practical application scene, some tasks only need to single tour, and some then need at least Make an inspection tour twice, for both of which can by being limited the time that is maked an inspection tour with reasonable distribution each time to constraints, And then the tour time each to the multiple tasks in multiple regions, a plurality of circuit does rational arrangement, to reduce cruise time punching Prominent, balanced each month task amount, cruise task is completed so as to satisfactory.

More than, the specific embodiment of the only present invention, but protection scope of the present invention is not limited thereto, any it is familiar with Those skilled in the art the invention discloses technical scope in, change or replacement can be readily occurred in, should all be covered Within protection scope of the present invention.Therefore, protection scope of the present invention should be defined by scope of the claims.

Claims (9)

1. a kind of distribution method of tour time, it is characterised in that include:
Target component list is obtained, the target component list includes task list and weather information list;
Synoptic model is set up according to the weather information list;
According to the management and control rank of each task in the task list, to each task, corresponding interim landing point is carried out in the region Sequence;
Order according to the synoptic model and interim landing point determines constraints, is described according to the constraints In business list, each task distributes tour time.
2. distribution method according to claim 1, it is characterised in that described weather is set up according to the weather information list Model, including:
By the weather information of a year be created as can calculation expression form, least unit is accurate to month, is monthly initialized as 30 days.
3. distribution method according to claim 1, it is characterised in that the pipe according to each task in the task list Control rank, to each task, corresponding interim landing point in the region is ranked up, including:
Traversal is assigned to the task of an interim landing point, calculates the management and control rank of each task;
By the highest management and control rank of the task of interim landing point, as the management and control rank corresponding to interim landing point;
The interim landing point in region is ranked up according to interim landing point corresponding management and control rank.
4. distribution method according to claim 1, it is characterised in that the constraints includes:
Sequence according to interim landing point is maked an inspection tour to the interim landing point in region;
Task to an interim landing point, is maked an inspection tour according to management and control rank order from high to low, identical in management and control rank In the case of, make an inspection tour circuit of the number of times more than 1 and preferentially maked an inspection tour;
In the region production plan amount arranged by every month is no more than the workload upper limit.
5. distribution method according to claim 4, it is characterised in that for the task maked an inspection tour at least twice by needs, The constraints also includes:
Time interval between second of task is maked an inspection tour and maked an inspection tour for the first time is not less than K month, and K is preset value.
6. the distribution method according to claim 4 or 5, it is characterised in that described is described according to the constraints In business list, each task distributes tour time, including:
Sequencing according to month travels through the month in the synoptic model successively, and the tour time of a task is arranged into Meet the month of the constraints.
7. the distribution method according to any one of claim 1-6, it is characterised in that
The target component list also includes:The historical data of task deployment information;
After being assigned to the tour time of all tasks in region, the distribution method also includes:According to the historical data In the line inspection time, determine and make an inspection tour the time range of same circuit then for the first time.
8. the distribution method according to any one of claim 1-6, it is characterised in that
The target component list also includes:No-fly zone information;
After being assigned to the tour time of all tasks in region, the distribution method also includes:When determination is routed through During no-fly zone, no-fly zone information is exported, the no-fly zone information is used for indicating the lap position of circuit and no-fly zone.
9. the distribution method according to any one of claim 1-6, it is characterised in that in region during the tour of all tasks Between be assigned after, the distribution method also includes:
The tour time that distributes for task is added in the task list, output with the addition of the task row of tour time Table.
CN201610851306.7A 2016-09-26 2016-09-26 A kind of distribution method of tour time CN106485349A (en)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102737415A (en) * 2012-07-16 2012-10-17 航天科工深圳(集团)有限公司 Intelligent inspection system and method for formulating inspection tasks
CN103824340A (en) * 2014-03-07 2014-05-28 山东鲁能智能技术有限公司 Intelligent inspection system and inspection method for electric transmission line by unmanned aerial vehicle
CN103838144A (en) * 2013-12-30 2014-06-04 林兴志 Sugarcane precision planting drip irrigation modeling control method based on Internet-of-Things soil analysis
CN104615849A (en) * 2014-12-30 2015-05-13 中国民航大学 Flight plan evaluating system and implementation method applicable for general aviation

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102737415A (en) * 2012-07-16 2012-10-17 航天科工深圳(集团)有限公司 Intelligent inspection system and method for formulating inspection tasks
CN103838144A (en) * 2013-12-30 2014-06-04 林兴志 Sugarcane precision planting drip irrigation modeling control method based on Internet-of-Things soil analysis
CN103824340A (en) * 2014-03-07 2014-05-28 山东鲁能智能技术有限公司 Intelligent inspection system and inspection method for electric transmission line by unmanned aerial vehicle
CN104615849A (en) * 2014-12-30 2015-05-13 中国民航大学 Flight plan evaluating system and implementation method applicable for general aviation

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