CN110503396A - Complex space crowdsourcing method for allocating tasks based on more technical ability - Google Patents
Complex space crowdsourcing method for allocating tasks based on more technical ability Download PDFInfo
- Publication number
- CN110503396A CN110503396A CN201910779633.XA CN201910779633A CN110503396A CN 110503396 A CN110503396 A CN 110503396A CN 201910779633 A CN201910779633 A CN 201910779633A CN 110503396 A CN110503396 A CN 110503396A
- Authority
- CN
- China
- Prior art keywords
- technical ability
- worker
- task
- cost
- bucket
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/101—Collaborative creation, e.g. joint development of products or services
Abstract
The invention discloses a kind of complex space crowdsourcing method for allocating tasks based on more technical ability, includes the following steps: step 1: in worker wiIt is minimum that quotation is chosen in the skill collection havingItem technical ability, obtains minimum skill collection of offeringStep 2: according to minimum skill collection of offeringQuotation and distance apart from task t be di, calculate worker wiCost costi；Step 3: according to worker wiCost costiAscending to be ranked up to all workers, worker's set expression after sequence is Wsorted；Step 4: successively using worker's set W after sequencesortedIn worker the minimum skill collection of quotationIn technical ability remove the capacity of filling technical ability bucket, until each technical ability bucket is filled or number of workers is using finishing.The present invention comprehensively considers the factors such as the distance, technical ability and ability of worker and carries out cost calculation, can be realized the task distribution of the minimum worker team of cost.
Description
Technical field
The present invention relates to space crowdsourcing field, especially a kind of complex space crowdsourcing task distribution side based on more technical ability
Method.
Background technique
With the prevalence of mobile device and GPS in recent years, location-based space crowdsourcing platform comes into being, and at us
Daily life in play an increasingly important role.Personal and group can participate in the platform, completion such as acquisition,
The activities such as space time information are analyzed, society human resource is taken full advantage of.For example the companies such as our common Uber, Baidu push away
Oneself corresponding space crowdsourcing platform out.
One critical issue of space crowdsourcing platform is exactly task distribution.For certain angles, task allocation algorithms are
It is no reasonable, it has been largely fixed the efficiency of service and quality of space crowdsourcing platform.According to the allocation model of space tasks, when
Before can be divided into WST and SAT mode (i.e. worker select mission mode and server distribution mission mode).In WST mode, space
Task can be broadcast to all workers for participating in the platform, and worker selects the wanting to complete of the task according to personalized preference.But this
The shortcomings that kind mode is that worker is without global consciousness, and in general, people can select to have come apart from oneself closer task mostly
At this, which will lead to some tasks, to select for a long time without worker, this is unsatisfactory for the demand of crowdsourcing platform --- it maximizes
Overall task distribution.And unlike WST mode, in SAT mode, crowdsourcing server in space is according to task and worker position
It sets, directly assigns the task to worker.
Research work before only considered the binary entity scene of Traditional Space crowdsourcing mostly, i.e. only task and worker
Simple space tasks distribution.But not all space tasks are all such as real-time traffic situation report-back, collection of photos, sky
The simple task that gas quality testing etc. only needs single people to complete.In real life, some space tasks are complicated, need one
The worker that group has particular professional technical ability completes together, for example software development, does up a house, holds party etc., while task is asked
The possible limited budget of the person of asking, it would be desirable to save the cost as far as possible.Therefore, the method for traditional simple task distribution possibly can not fit
The scene that complex space crowdsourcing task for this kind of more technical ability is distributed.
It is had the following problems by correlation investigation and research, existing solution:
(1) technical ability required by complex space task does not have fine-grained demand for number of workers.Such as each technical ability
Worker is only needed to have to complete, problems can specification be set covering problem.But in fact, technical ability required by task
In, the quantity of worker may be determined according to the workload of this technical ability and the complexity to acquire skill.
(2) if worker receives execution task, no matter it provides how many kinds of technical ability, completes how many workload, gained remuneration
It is all certain.According to the distribution principle of distribution according to work " more pay for more work ", worker should have respective report for its individual event technical ability
The remuneration that valence, i.e. worker finally obtain is closely bound up with the technical ability number and kinds of skill of offer.
(3) server seldom considers the energy power limit of worker in the task of distribution, and a worker is unlikely to use it
Whole professional skills execute task, and one side worker's workload is too big, on the other hand, not can guarantee the execution quality of task.
Therefore in order to balance the workload of team, the maximum technical ability number that worker often can provide it is limited.
Although current research work is more technical ability space crowdsourcing tasks, distribution is made that significant contribution, these work
Do not consider above-described constraint condition completely.
Summary of the invention
The technical problems to be solved by the present invention are: in view of the above problems, providing a kind of answering based on more technical ability
Miscellaneous space crowdsourcing method for allocating tasks.
The technical solution adopted by the invention is as follows:
A kind of complex space crowdsourcing method for allocating tasks based on more technical ability is equipped with worker's set W={ w1,w2,w3,…
wn, n is the quantity of worker；For worker wi(1≤i≤n), the maximum technical ability number that can be provided areApart from task t away from
From for di；For skill collection S required by task tt={ s1,s2,…,sm, there are m technical ability bucket, the capacity of each technical ability bucket
For kj(1≤j≤m) indicates the number of workers that each technical ability needs；
The complex space crowdsourcing method for allocating tasks based on more technical ability, includes the following steps:
Step 1: in worker wiIt is minimum that quotation is chosen in the skill collection havingItem technical ability, obtains offering minimum
Skill collection
Step 2: according to minimum skill collection of offeringQuotation and distance apart from task t be di, calculate worker wi
Cost costi；
Step 3: according to worker wiCost costiIt is ascending that all workers are ranked up, worker's set after sequence
It is expressed as Wsorted；
Step 4: successively using worker's set W after sequencesortedIn worker the minimum skill collection of quotationIn
Technical ability remove the capacity of filling technical ability bucket, until each technical ability bucket is filled or number of workers is using finishing.
Further, in the step 2, worker wiCost costiCalculation formula it is as follows:
Wherein, pθIndicate minimum skill collection of offeringIn, the quotation of every technical ability；γ is system global parameter, table
Show the travel cost of unit distance.
Further, it in the step 4, is performed the following operations when entering technical ability to technical ability barreled:
When the technical ability bucket that will be packed into not yet is filled, then smoothly it is packed into；Otherwise:
The technical ability is deleted from the skill collection that still unappropriated worker has, then re-execute the steps 1~4, directly
It is filled to each technical ability bucket or number of workers is using finishing.
Further, the complex space crowdsourcing method for allocating tasks based on more technical ability meets following constraint condition:
(1) capacity consistency: in the same period, each worker can only distribute to a task, and skill used in worker
Energy number is no more than worker and completes the maximum technical ability number that can be provided when task
(2) technical ability constrains: the worker for distributing to task t can cover required technical ability, and the worker with i-th technical ability
Quantity is ki；
(3) distance restraint: each worker w of task t is distributed toi, to the distance d of taskiNo more than maximum travel distance
MTD。
In conclusion by adopting the above-described technical solution, the beneficial effects of the present invention are:
The present invention comprehensively considers the factors such as the distance, technical ability and ability of worker and carries out cost calculation, can be realized cost most
The task of low worker team is distributed.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to needed in the embodiment attached
Figure is briefly described, it should be understood that the following drawings illustrates only certain embodiments of the present invention, therefore is not construed as pair
The restriction of range for those of ordinary skill in the art without creative efforts, can also be according to this
A little attached drawings obtain other relevant attached drawings.
Fig. 1 is the flow diagram of the complex space crowdsourcing method for allocating tasks of the invention based on more technical ability.
Fig. 2 is another flow diagram of the complex space crowdsourcing method for allocating tasks of the invention based on more technical ability.
Fig. 3 is filling skill of the embodiment 1 based on the complex space crowdsourcing method for allocating tasks of the invention based on more technical ability
The process schematic of energy bucket.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention, i.e., described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is logical
The component for the embodiment of the present invention being often described and illustrated herein in the accompanying drawings can be arranged and be designed with a variety of different configurations.
Therefore, claimed invention is not intended to limit to the detailed description of the embodiment of the present invention provided in the accompanying drawings below
Range, but be merely representative of selected embodiment of the invention.Based on the embodiment of the present invention, those skilled in the art are not having
Every other embodiment obtained under the premise of creative work is made, shall fall within the protection scope of the present invention.
Need to illustrate: complex space crowdsourcing task allocation scenarios include following entity and content:
(1) complex space task: it is represented by binary group (< St:kt〉,Lt)；Wherein, < St:kt> is indicated required by task t
Skill collection StAnd number of workers k needed for completing each technical abilityt；LtFor the position of task t.
(2) worker: the worker with more technical ability is represented by triple (< Sw:pw>,Lw,Cw)；Wherein < Sw:pw> it is worker
The skill collection S that w haswAnd to quotation p specified by each technical abilityw；LwFor the position of worker w；CwWorker is represented to complete to appoint
Available maximum technical ability number when business t.
(3) reward of worker: for a worker after completion task, needing to pay his/her remuneration includes paying work
Remuneration needed for the technical ability that the travel cost of people is compensated and provided:
Wherein, dis (Lw,Lt) be worker w to task t distance；γ is system global parameter, indicates the travel cost of unit distance；
Sw,tSkill collection used in task t is completed for worker w, and | Sw,t|≤Cw；It is completed used in task t for worker
Quotation corresponding to each technical ability in skill collection, wherein s ∈ Sw,t。
(4) feasible worker team: for a task t, skill requirement are as follows: (< s1:k1>,<s2:k2>,…<sm:km>)。
One feasible worker team TeamtIt is one group of worker-technical ability pair set, it is desirable that skill collection provided by worker can be completely
Skill collection required by covering task, and the number of workers for possessing i-th technical ability is ki, then have:
Based on above-mentioned setting, the complex space crowdsourcing method for allocating tasks of the invention based on more technical ability is exactly all
In feasible team, the worker team with least cost is found for task t, to reduce the expenditure budget of task requester,
Its formal definitions are as follows:
The then complex space crowdsourcing method for allocating tasks based on more technical ability are as follows:
Equipped with worker set W={ w1,w2,w3,…wn, n is the quantity of worker；For worker wi(1≤i≤n), can mention
Supply maximum technical ability number beDistance apart from task t is di(i.e. dis (Lw,Lt))；For skill set required by task t
Close St={ s1,s2,…,sm, there is m technical ability bucket, the capacity of each technical ability bucket is kj(1≤j≤m) indicates each technical ability needs
Number of workers；The complex space crowdsourcing method for allocating tasks based on more technical ability, as shown in Figure 1, including the following steps:
Step 1: in worker wiIt is minimum that quotation is chosen in the skill collection havingItem technical ability, obtains offering minimum
Skill collection
Step 2: according to minimum skill collection of offeringQuotation and distance apart from task t be di, calculate worker wi
Cost costi；
Step 3: according to worker wiCost costiIt is ascending that all workers are ranked up, worker's set after sequence
It is expressed as Wsorted；
Step 4: successively using worker's set W after sequencesortedIn worker the minimum skill collection of quotationIn
Technical ability remove the capacity of filling technical ability bucket, until each technical ability bucket is filled or number of workers is using finishing.
Wherein, worker wiCost costiCalculation formula it is as follows:
Wherein, pθIndicate minimum skill collection of offeringIn, the quotation of every technical ability；γ is system global parameter, table
Show the travel cost of unit distance.
Further, it as shown in Fig. 2, in the step 4, is performed the following operations when entering technical ability to technical ability barreled:
When the technical ability bucket that will be packed into not yet is filled, then smoothly it is packed into；Otherwise:
The technical ability is deleted from the skill collection that still unappropriated worker has, then re-execute the steps 1~4, directly
It is filled to each technical ability bucket or number of workers is using finishing.
Further, the complex space crowdsourcing method for allocating tasks of the invention based on more technical ability needs to meet as follows about
Beam condition:
(1) capacity consistency: in the same period, each worker can only distribute to a task, and skill used in worker
Energy number is no more than worker and completes the maximum technical ability number that can be provided when taskIt can indicate are as follows:
(2) technical ability constrains: the worker for distributing to task t can cover required technical ability, and the worker with i-th technical ability
Quantity is ki；It can indicate are as follows:
(3) distance restraint: each worker w of task t is distributed toi, to the distance d of taskiNo more than maximum travel distance
MTD(Maximum Travel Distance)；Wherein, MTD indicates that worker is ready the maximum distance of trip, more than the distance
Task worker not receives.It can indicate are as follows:
Feature and performance of the invention are described in further detail with reference to embodiments.
Embodiment 1
The information of Given task t, for skill collection S required by task tt={ s1,s2,s3,s4,s5, i.e. task t is needed
The technical ability of 5 seed types is wanted to complete, according to skillset by skill collection S required by task ttIt is expressed as 5 technical ability bucket s1~
s5；The capacity k of technical ability buckett={ k1:2,k2:1,k3:2,k4:1,k5: 3 }, indicate technical ability bucket s1~s5Required number of workers.
Equipped with worker set W={ w1,w2,w3,w4,w5, the skill collection S that each worker hasw, each technical ability quotation pw, complete
The maximum technical ability number C that can be provided when taskw, the information such as distance apart from task t it is as shown in table 1；
Table 1:
| w1 | w2 | w3 | w4 | w5 | |
| Sw | {s1, s2, s5} | {s2, s3, s4, s5} | {s1, s3, s5} | {s2, s4} | {s1, s3, s5} |
| pw | { 5,3,4 } | { 3,3,4,3 } | { 3,2,4 } | { 2,3 } | { 3,4,5 } |
| Cw | 2 | 3 | 2 | 1 | 2 |
| di | 1 | 2 | 2 | 3 | 4 |
Complex space crowdsourcing method for allocating tasks of the embodiment of the present invention based on more technical ability, as shown in figure 3, including as follows
Step:
It recycles for the first time:
Step 1: in worker wiIt is minimum that quotation is chosen in the skill collection havingItem technical ability, obtains offering minimum
Skill collection
For worker w12 minimum technical ability of offering are chosen, then worker w1The minimum skill collection of quotation
For worker w23 minimum technical ability of offering are chosen, then worker w2The minimum skill collection of quotation
For worker w32 minimum technical ability of offering are chosen, then worker w3The minimum skill collection of quotation
For worker w41 minimum technical ability of offering is chosen, then worker w4The minimum skill collection of quotation
For worker w52 minimum technical ability of offering are chosen, then worker w5The minimum skill collection of quotation
Step 2: according to minimum skill collection of offeringQuotation and distance apart from task t be di, calculate worker wi
Cost costi；Worker wiCost costiCalculation formula it is as follows:
Wherein, pθIndicate minimum skill collection of offeringIn, the quotation of every technical ability；γ is system global parameter, table
Show the travel cost of unit distance, assumes γ=1, then the worker w being calculated in the present embodimentiCost costiRespectively
Are as follows: cost1=3+4+1=8, cost2=3+3+3+2=11, cost3=3+2+2=7, cost4=2+3=5, cost5=3+4+
4=11；
Step 3: according to worker wiCost costiIt is ascending that all workers are ranked up, worker's set after sequence
It is expressed as Wsorted；Worker's set W after sorting at this timesorted={ w4,w3,w1,w2,w5}；
Step 4: successively using worker's set W after sequencesortedIn worker the minimum skill collection of quotationIn
Technical ability remove the capacity of filling technical ability bucket, until each technical ability bucket is filled or number of workers is using finishing:
(1) worker w is used4The minimum skill collection of quotationTechnical ability bucket is filled, due toThen fill
Technical ability bucket s2；
(2) worker w is used3The minimum skill collection of quotationTechnical ability bucket is filled, due toThen
Fill technical ability bucket s1And s3；
(3) worker w is used1The minimum skill collection of quotationTechnical ability bucket is filled,Then fill
Technical ability bucket s2And s5；
At this point, technical ability bucket s2It is already filled with, then by technical ability bucket s2Corresponding skillset has from still unappropriated worker
It is deleted in skill collection, i.e., from worker w1、w2、w5The skill collection having in delete, the worker w after deletion1、w2、w5Tool
Some skill collection Sw, each technical ability quotation pw, complete the maximum technical ability number C that can be provided when taskw, apart from task t away from
From etc. information it is as shown in table 2；
Table 2:
| w1 | w2 | w5 | |
| Sw | {s1, s5} | {s3, s4, s5} | {s1, s3, s5} |
| pw | { 5,4 } | { 3,4,3 } | { 3,4,5 } |
| Cw | 2 | 3 | 2 |
| di | 1 | 2 | 4 |
Second of circulation, re-execute the steps 1~4:
Step 1, respectively from worker w1、w2、w5It is minimum that quotation is chosen in the skill collection havingItem technical ability, is reported
The minimum skill collection of valence
For worker w12 minimum technical ability of offering are chosen, then worker w1The minimum skill collection of quotation
For worker w23 minimum technical ability of offering are chosen, then worker w2The minimum skill collection of quotation
For worker w52 minimum technical ability of offering are chosen, then worker w5The minimum skill collection of quotation
Step 2, the worker w being calculated1、w2、w5Cost be respectively as follows: cost1=5+4+1=10, cost2=3+4+3+
2=12, cost5=3+4+4=11；
Step 3, according to worker w1、w2、w5Cost it is ascending be ranked up, at this time sort after worker's set Wsortrd
={ w1, w5, w2}；
Step 4, successively gather { w using the worker after sequence1, w5, w2In worker the minimum skill collection of quotationIn technical ability remove the capacity of filling technical ability bucket, until each technical ability bucket is filled or number of workers is using finishing:
(1) worker w is used1The minimum skill collection of quotationTechnical ability bucket is filled, due toThen fill out
Fill technical ability bucket s1And s5；
(2) worker w is used5The minimum skill collection of quotationTechnical ability bucket is filled, due toThen fill out
Fill technical ability bucket s1And s3；Technical ability bucket s at this time1It is already filled with, then by technical ability bucket s1Corresponding skillset is from still unappropriated worker
It is deleted in the skill collection having, i.e., from worker w2、w5The skill collection having in delete, the worker w after deletion2、w5Tool
Some skill collection Sw, each technical ability quotation pw, complete the maximum technical ability number C that can be provided when taskw, apart from task t away from
From etc. information it is as shown in table 3；
Table 3:
| w2 | w5 | |
| Sw | {s3, s4, s5} | {s3, s5} |
| pw | { 3,4,3 } | { 4,5 } |
| Cw | 3 | 2 |
| di | 2 | 4 |
Third time recycles, and re-execute the steps 1~4:
Step 1, respectively from worker w2、w5It is minimum that quotation is chosen in the skill collection havingItem technical ability, is offered
Minimum skill collection
For worker w23 minimum technical ability of offering are chosen, then worker w2The minimum skill collection of quotation
For worker w52 minimum technical ability of offering are chosen, then worker w5The minimum skill collection of quotation
Step 2, the worker w being calculated2、w5Cost be respectively as follows: cost2=3+4+3+2=12, cost5=4+5+4
=13；
Step 3, according to worker w2、w5Cost it is ascending be ranked up, at this time sort after worker's set Wsorted=
{w2, w5}；
Step 4, successively gather { w using the worker after sequence2, w5In worker the minimum skill collection of quotationIn
Technical ability remove the capacity of filling technical ability bucket, until each technical ability bucket is filled or number of workers is using finishing:
(1) worker w is used2The minimum skill collection of quotationTechnical ability bucket is filled, due to
Then fill technical ability bucket s3, s4And s5；
(2) worker w is used5The minimum skill collection of quotationTechnical ability bucket is filled, due toThen fill out
Fill technical ability bucket s3And s5；Technical ability bucket s at this time3It is already filled with, then by technical ability bucket s3Corresponding skillset is from still unappropriated worker
It is deleted in the skill collection having, i.e., from worker w5The skill collection having in delete, the worker w after deletion5The skill having
It can set Sw, each technical ability quotation pw, complete the maximum technical ability number C that can be provided when taskw, the letter such as distance apart from task t
Breath is as shown in table 3；
Table 3:
| w5 | |
| Sw | {s5} |
| pw | {5} |
| Cw | 2 |
| di | 4 |
4th circulation, re-execute the steps 1~4: at this point, worker w5In only residue s5, it is convenient to omit execution step 1~
3, directly by worker w5Technical ability fill to technical ability bucket s5。
It is followed by above-mentioned 4 times bad, obtains the task allocation result of optimal worker team are as follows: { < w1: { s1, s5}>,<w2:
{s3, s4, s5}>,<w3: { s1, s3}>,<w4: { s2}>,<w5: { s5} > }, the totle drilling cost Cost of the task allocation resultt=42.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (4)
1. a kind of complex space crowdsourcing method for allocating tasks based on more technical ability, which is characterized in that be equipped with worker's set W={ w1,
w2,w3,…wn, n is the quantity of worker；For worker wi(1≤i≤n), the maximum technical ability number that can be provided areDistance is appointed
The distance of business t is di；For skill collection S required by task tt={ s1,s2,…,sm, there are m technical ability bucket, each technical ability bucket
Capacity be kj(1≤j≤m) indicates the number of workers that each technical ability needs；The complex space crowdsourcing based on more technical ability is appointed
Business distribution method, includes the following steps:
Step 1: in worker wiIt is minimum that quotation is chosen in the skill collection havingItem technical ability, obtains minimum skill set of offering
It closes
Step 2: according to minimum skill collection of offeringQuotation and distance apart from task t be di, calculate worker wiAt
This costi；
Step 3: according to worker wiCost costiIt is ascending that all workers are ranked up, worker's set expression after sequence
For Wsorted；
Step 4: successively using worker's set W after sequencesortedIn worker the minimum skill collection of quotationIn skill
The capacity that can remove filling technical ability bucket, until each technical ability bucket is filled or number of workers is using finishing.
2. the complex space crowdsourcing method for allocating tasks according to claim 1 based on more technical ability, which is characterized in that described
In step 2, worker wiCost costiCalculation formula it is as follows:
Wherein, pθIndicate minimum skill collection of offeringIn, the quotation of every technical ability；γ is system global parameter, indicates single
The travel cost of position distance.
3. the complex space crowdsourcing method for allocating tasks according to claim 1 or 2 based on more technical ability, which is characterized in that
In the step 4, performed the following operations when entering technical ability to technical ability barreled:
When the technical ability bucket that will be packed into not yet is filled, then smoothly it is packed into；Otherwise:
The technical ability is deleted from the skill collection that still unappropriated worker has, 1~4 is then re-execute the steps, until every
A technical ability bucket is filled or number of workers is using finishing.
4. the complex space crowdsourcing method for allocating tasks according to claim 3 based on more technical ability, which is characterized in that described
Complex space crowdsourcing method for allocating tasks based on more technical ability meets following constraint condition:
(1) capacity consistency: in the same period, each worker can only distribute to a task, and technical ability number used in worker
The maximum technical ability number that can be provided when completing task no more than worker
(2) technical ability constrains: the worker for distributing to task t can cover required technical ability, and the number of workers with i-th technical ability
For ki；
(3) distance restraint: each worker w of task t is distributed toi, to the distance d of taskiNo more than maximum travel distance MTD.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910779633.XA CN110503396B (en) | 2019-08-22 | 2019-08-22 | Multi-skill-based complex space crowdsourcing task allocation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910779633.XA CN110503396B (en) | 2019-08-22 | 2019-08-22 | Multi-skill-based complex space crowdsourcing task allocation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110503396A true CN110503396A (en) | 2019-11-26 |
| CN110503396B CN110503396B (en) | 2022-12-27 |
Family
ID=68588881
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910779633.XA Active CN110503396B (en) | 2019-08-22 | 2019-08-22 | Multi-skill-based complex space crowdsourcing task allocation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110503396B (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111507757A (en) * | 2020-04-09 | 2020-08-07 | 中南大学 | Crowd sensing excitation method for improving task completion rate of remote area |
| US11386299B2 (en) | 2018-11-16 | 2022-07-12 | Yandex Europe Ag | Method of completing a task |
| US11416773B2 (en) | 2019-05-27 | 2022-08-16 | Yandex Europe Ag | Method and system for determining result for task executed in crowd-sourced environment |
| US11475387B2 (en) | 2019-09-09 | 2022-10-18 | Yandex Europe Ag | Method and system for determining productivity rate of user in computer-implemented crowd-sourced environment |
| US11481650B2 (en) | 2019-11-05 | 2022-10-25 | Yandex Europe Ag | Method and system for selecting label from plurality of labels for task in crowd-sourced environment |
| US11727336B2 (en) | 2019-04-15 | 2023-08-15 | Yandex Europe Ag | Method and system for determining result for task executed in crowd-sourced environment |
| US11727329B2 (en) | 2020-02-14 | 2023-08-15 | Yandex Europe Ag | Method and system for receiving label for digital task executed within crowd-sourced environment |
| CN116976652A (en) * | 2023-09-25 | 2023-10-31 | 烟台大学 | Multi-target task allocation method based on space-time crowdsourcing |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110313933A1 (en) * | 2010-03-16 | 2011-12-22 | The University Of Washington Through Its Center For Commercialization | Decision-Theoretic Control of Crowd-Sourced Workflows |
| US20130253969A1 (en) * | 2012-03-20 | 2013-09-26 | International Business Machines Corporation | Broadcast Messaging of Incentives Based on Value |
| CN107103408A (en) * | 2017-03-24 | 2017-08-29 | 扬州大学 | Complex task distribution method under a kind of mass-rent environment |
| CN107527147A (en) * | 2017-08-18 | 2017-12-29 | 扬州大学 | Complex task distribution method based on community network |
| CN108876012A (en) * | 2018-05-28 | 2018-11-23 | 哈尔滨工程大学 | A kind of space crowdsourcing method for allocating tasks |
| CN109767060A (en) * | 2018-12-04 | 2019-05-17 | 嘉兴国电通新能源科技有限公司 | A kind of crowdsourcing motivational techniques based on End-user relevance and accuracy |
| CN109919458A (en) * | 2019-02-20 | 2019-06-21 | 西北大学 | Cooperation cost method for allocating tasks and its system in social networks based on concept lattice |
| KR102008095B1 (en) * | 2018-02-08 | 2019-08-06 | 인하대학교 산학협력단 | Method and system for managing spatial crowdsourcing task based on privacy-aware grid |
-
2019
- 2019-08-22 CN CN201910779633.XA patent/CN110503396B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110313933A1 (en) * | 2010-03-16 | 2011-12-22 | The University Of Washington Through Its Center For Commercialization | Decision-Theoretic Control of Crowd-Sourced Workflows |
| US20130253969A1 (en) * | 2012-03-20 | 2013-09-26 | International Business Machines Corporation | Broadcast Messaging of Incentives Based on Value |
| CN107103408A (en) * | 2017-03-24 | 2017-08-29 | 扬州大学 | Complex task distribution method under a kind of mass-rent environment |
| CN107527147A (en) * | 2017-08-18 | 2017-12-29 | 扬州大学 | Complex task distribution method based on community network |
| KR102008095B1 (en) * | 2018-02-08 | 2019-08-06 | 인하대학교 산학협력단 | Method and system for managing spatial crowdsourcing task based on privacy-aware grid |
| CN108876012A (en) * | 2018-05-28 | 2018-11-23 | 哈尔滨工程大学 | A kind of space crowdsourcing method for allocating tasks |
| CN109767060A (en) * | 2018-12-04 | 2019-05-17 | 嘉兴国电通新能源科技有限公司 | A kind of crowdsourcing motivational techniques based on End-user relevance and accuracy |
| CN109919458A (en) * | 2019-02-20 | 2019-06-21 | 西北大学 | Cooperation cost method for allocating tasks and its system in social networks based on concept lattice |
Non-Patent Citations (2)
| Title |
|---|
| TIANSHU SONG等: "Specialty-Aware Task Assignment in Spatial Crowdsourcing", 《INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE》 * |
| 范泽军等: "基于约束的空间众包多阶段任务分配", 《计算机学报》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11386299B2 (en) | 2018-11-16 | 2022-07-12 | Yandex Europe Ag | Method of completing a task |
| US11727336B2 (en) | 2019-04-15 | 2023-08-15 | Yandex Europe Ag | Method and system for determining result for task executed in crowd-sourced environment |
| US11416773B2 (en) | 2019-05-27 | 2022-08-16 | Yandex Europe Ag | Method and system for determining result for task executed in crowd-sourced environment |
| US11475387B2 (en) | 2019-09-09 | 2022-10-18 | Yandex Europe Ag | Method and system for determining productivity rate of user in computer-implemented crowd-sourced environment |
| US11481650B2 (en) | 2019-11-05 | 2022-10-25 | Yandex Europe Ag | Method and system for selecting label from plurality of labels for task in crowd-sourced environment |
| US11727329B2 (en) | 2020-02-14 | 2023-08-15 | Yandex Europe Ag | Method and system for receiving label for digital task executed within crowd-sourced environment |
| CN111507757A (en) * | 2020-04-09 | 2020-08-07 | 中南大学 | Crowd sensing excitation method for improving task completion rate of remote area |
| CN111507757B (en) * | 2020-04-09 | 2024-03-15 | 中南大学 | Crowd sensing excitation method for improving task completion rate in remote areas |
| CN116976652A (en) * | 2023-09-25 | 2023-10-31 | 烟台大学 | Multi-target task allocation method based on space-time crowdsourcing |
| CN116976652B (en) * | 2023-09-25 | 2023-12-29 | 烟台大学 | Multi-target task allocation method based on space-time crowdsourcing |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110503396B (en) | 2022-12-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110503396A (en) | Complex space crowdsourcing method for allocating tasks based on more technical ability | |
| US8301479B2 (en) | System and method for web-based sports event scheduling | |
| US20080177611A1 (en) | Means and methods to coordinate meetings and generation of related documents | |
| Santos-Martín et al. | 4.2. Socio-cultural valuation approaches | |
| US20030177052A1 (en) | Human resources management system and method | |
| Jordan | GIS for community forestry user groups in Nepal: putting people before the technology | |
| CN109064357B (en) | Real-time tour guide recommendation system and method | |
| EP3905162A2 (en) | Schedule management service system and method | |
| Cudney et al. | Analyzing customer requirements for the American society of engineering management using quality function deployment | |
| US20160048806A1 (en) | Computer-based project management methods and systems | |
| US7734517B2 (en) | Systems and method for determining the cost of a securities research department to service a client of the department | |
| Mimbi et al. | Mobile phones and digital divide in East African countries | |
| Win et al. | Advantages and challenges of the gig economy: perspective from potential hospitality employees. | |
| Azizan et al. | Critical success factors for knowledge transfer via government websites | |
| Chandewar et al. | Automatic seating arrangement of university exam | |
| Juan | Resource cache sharing system of education information center network based on internet of things | |
| Lu et al. | The 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2020) virtual, online, USA November 3--6, 2020: conference report | |
| JP2002324176A (en) | Information mediation system, and recording medium | |
| Jaworski et al. | Evaluating ecosystem services as management outcomes in National Forest and Grassland Planning assessments | |
| Liu et al. | QFD application in software process management and improvement based on CMM | |
| CN100373340C (en) | Distribution computer system managing method | |
| CN102262747A (en) | Support system of establishing business based on labor dispatch | |
| Ikeda et al. | An evaluation model of internal and external contributions in hierarchical organizations | |
| Melgoza | The Impact of Telework Implementation in the Public Sector | |
| Warner et al. | Linking PRA to policy: the conflict analysis framework |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |