CN104008444A - Model and method applied to team construction under multi-constraint projects - Google Patents
Model and method applied to team construction under multi-constraint projects Download PDFInfo
- Publication number
- CN104008444A CN104008444A CN201410201069.0A CN201410201069A CN104008444A CN 104008444 A CN104008444 A CN 104008444A CN 201410201069 A CN201410201069 A CN 201410201069A CN 104008444 A CN104008444 A CN 104008444A
- Authority
- CN
- China
- Prior art keywords
- project
- personnel
- correlative factor
- team
- model
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 39
- 238000010276 construction Methods 0.000 title abstract 5
- 238000011156 evaluation Methods 0.000 claims description 28
- 238000010206 sensitivity analysis Methods 0.000 claims description 5
- 101150094193 AHP1 gene Proteins 0.000 claims description 4
- 101100269451 Arabidopsis thaliana AHL10 gene Proteins 0.000 claims description 4
- 238000004335 scaling law Methods 0.000 claims description 4
- 238000012360 testing method Methods 0.000 claims description 4
- 230000008569 process Effects 0.000 abstract description 5
- 238000005457 optimization Methods 0.000 abstract description 3
- 238000011160 research Methods 0.000 description 5
- 238000012216 screening Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000000926 separation method Methods 0.000 description 2
- 241001465754 Metazoa Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000009247 menarche Effects 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 208000001491 myopia Diseases 0.000 description 1
- 238000006748 scratching Methods 0.000 description 1
- 230000002393 scratching effect Effects 0.000 description 1
- 238000010187 selection method Methods 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 230000002195 synergetic effect Effects 0.000 description 1
Abstract
The invention relates to a model and method applied to team construction under multi-constraint projects and belongs to the field of industrial engineering. The model comprises the projects, related factors in the projects, related factor weights of the projects, personnel, and judgment values of the personnel and the related factors in the projects; a double-starting-point mode is used for constructing a construction plan of an optimal team, the construction plan of the optimal team is constructed by combining the related factor weights, generated by a starting point 1, of the projects, and the judgment values of the personnel and the related factors in the projects, wherein the judgment values are generated by a starting point 2. According to the model and the method, the team construction model has high adaptability in the actual application background, the algorithm has high flexibility in the actual application, accuracy of personnel location is high, and the optimization searching ability of the programmed optimal solution searching process in the more complex application background can be more remarkable; the model and the algorithm have high transfer ability, the model and algorithm basis can be provided for similar problems, and when the similar problems are solved, the model and the algorithm can be modified first and applied.
Description
Technical field
The present invention relates to a kind of models and methods that under multiple constraint project, team builds that is applied to, belong to Industrial Engineering field.
Background technology
In the process of social snap information, in the integration process of complicated resource, how to navigate to quickly and efficiently required information and be exactly emphasis and the focus studied now.People pass through complex network, the research of the aspects such as relative importance value theory and game theory, and then expectation solves the problem of most optimum distribution of resources.
Aspect the configuration of human resources, people have done a large amount of work, 20 century 70s, and Herman is breathed out and is agree found synergetics, and its core is cooperative mode and the mechanism of " integral body is greater than part sum " in exposing system.About the research of partner selection mainly with dynamic alliance, supply chain and virtual enterprise etc. are background, mainly adopt method for multiple attribute decision-makings or Optimization Modeling method, but have two aspect solutions certainly not ideal enough in existing research: the one, existing index system can not reflect the knowledge factor in working in coordination with; The 2nd, existing method can not be processed the concordance problem of partner's integral body.Based on this, the harmony of getting up according to newly-developed is theoretical, has provided the collaborative team of the knowledge Partnership Selection Method based on Concordance Matrix, by calculating the harmonious exponential sum index analysis whole harmonious that is discord, find the crucial core of candidate buddy, select accordingly desirable partner.
At present, at Chinese most enterprises, especially stateowned enterprise much relies on experience, rule or the configuration human resources such as adjusts afterwards, is easy to cause short-sighted, is difficult to carry out from the overall angle of corporate strategy development post and personnel's reasonable disposition.Researchist remains in qualitative aspect mostly to the research of human resources configuration, though aspect quantitatively, there are some researchs, not deep enough, often just to decision maker, provide foundation in theory, the actual utilization of distance also has a certain distance, and practicality and operability are not strong.Based on the given situation of project: 1. do not have the personnel team that a kind of mobilance and adaptability are very high to build model; 2. in the design of model, do not consider the relation mutually combining between qualitative and quantitative; 3. in the design of algorithm, do not use the correlation theory technology of operation on table; 4. about considering in Complex Constraints, do not use 1-9 point systems of AHP method to carry out project in the distinctive unified combination of personnel.
Based on the problems referred to above, especially in the key link in the regulation and control of personnel and project are controlled with this process management of distribution, the in the situation that of containing multiple constraint in project source, how the qualitative data in related constraint variable is converted into quantitative data, from HR pool, screening efficiently matches optimized personnel's scheme has become a urgent problem.Therefore, build Complex Constraints project team and built model, designed the team's optimization algorithm based on this model.
Summary of the invention
The invention provides a kind of models and methods that under multiple constraint project, team builds that is applied to, for solve the problem that matches optimized personnel's scheme of how screening efficiently from HR pool.
Technical scheme of the present invention is: a kind of model that is applied to team's structure under multiple constraint project, comprising: project P, correlative factor F in project
1, F
2, F
3, F
4f
n, project correlative factor weights W
1, W
2, W
3, W
4w
n; Personnel M
1, M
2, M
3, M
4m
m, the decision content I of correlative factor in each personnel and project
ij;
With two starting point forms, build optimum team constructing plan:
Starting point 1: produce project correlative factor F by project P
1, F
2, F
3, F
4f
n, then for F
1, F
2, F
3, F
4f
nstructure project correlative factor weights W
1, W
2, W
3, W
4w
n;
Starting point 2: by personnel M
1, M
2, M
3, M
4m
mwith F
1, F
2, F
3, F
4f
nproduce the decision content I of correlative factor in each personnel and project
ij;
The project correlative factor weights W producing in conjunction with starting point 1
1, W
2, W
3, W
4w
nthe decision content I of correlative factor in each personnel who produces with starting point 2 and project
ijbuild optimum team constructing plan;
Wherein, the quantity that m is personnel, n is the quantity of project correlative factor, i=1 ... m, j=1 ... n.
Be applied to the method that under multiple constraint project, team builds, the concrete steps of described method are as follows:
Step1, by personnel M
1, M
2, M
3, M
4m
mwith correlative factor F in project
1, F
2, F
3, F
4f
ncompare to determine between two, according to " AHP1～9 scaling law " the decision content I of correlative factor in personnel evaluation achievement data table is filled in out each personnel and project
ij;
Step2, by expert assessment method for the relevant plain F of project
1, F
2, F
3, F
4f
nobtain project correlative factor weights W
1, W
2, W
3, W
4w
n, entry item correlative factor weight table; Wherein project correlative factor weight is according to " W
1+ W
2+ W
3+ ... + W
n=1 " test;
Step3, according to the numerical value in personnel evaluation achievement data table and project correlative factor weight table, correspondence solves Iw
ij, fill in algorithm iteration relation table;
Step4, in algorithm iteration relation table, find out in every a line j maximum Iw
ijbe worth corresponding M
i:
If have and occurred identical M in multirow
i, by Iw maximum in corresponding row
ijvalue summation, obtains this M
ipersonnel selection weight evaluation index value;
If have and occurred M in a line
i, by Iw maximum in corresponding row
ijvalue is as this M
ipersonnel selection weight evaluation index value;
If there is no to occur in a line M
i, do not operate;
Step5, according to the corresponding M obtaining in Step4
ipersonnel selection weight evaluation index value carry out descending sequence, find maximum personnel selection weight evaluation index value, this personnel selection weight evaluation index is worth to corresponding M
ias the personnel that preferentially meet project;
Step6, will scratch in algorithm iteration relation table selected M in Step5
iiw in the i row at place
ijas the algorithm iteration relation table of getting after maximal value; According to the algorithm iteration table of getting after maximal value, continue to carry out iteration by the step of Step4, Step5, until find out all required team of this project, build personnel;
Wherein, the quantity that m is personnel, n is the quantity of project correlative factor, i=1 ... m, j=1 ... n.
Described Iw
ijcomputing formula be: Iw
ij=I
ij* W
j; I=1 wherein ... m, j=1 ... n, the quantity that m is personnel, n is the quantity of project correlative factor.
While continuing to carry out iteration with Step4 in described step Step6, find out Iw maximum in every a line j
ijbe worth corresponding M
ithe method of taking is: directly search or adopt the method for sensitivity analysis to search.
The invention has the beneficial effects as follows: show that Liao Gai team builds model and in actual application background, has stronger adaptability, this algorithm has higher flexibility in actual applications, in personnel positioning, have suitable accuracy, it is all the more obviously outstanding that the optimum solution of its sequencing is found process optimizing ability in more complicated application background; This model and algorithm have stronger animal migration, can supply a model and algorithm foundation for similar problem, after solving on Similar Problems also and can modifying to model and algorithm, use.
Accompanying drawing explanation
Fig. 1 is that under the multiple constraint project under the present invention, team builds model.
Embodiment
Embodiment 1: as shown in Figure 1, a kind of model that is applied to team's structure under multiple constraint project, comprising: project P, correlative factor F in project
1, F
2, F
3, F
4f
n, project correlative factor weights W
1, W
2, W
3, W
4w
n; Personnel M
1, M
2, M
3, M
4m
m, the decision content I of correlative factor in each personnel and project
ij;
With two starting point forms, build optimum team constructing plan:
Starting point 1: produce project correlative factor F by project P
1, F
2, F
3, F
4f
n, then for F
1, F
2, F
3, F
4f
nstructure project correlative factor weights W
1, W
2, W
3, W
4w
n;
Starting point 2: by personnel M
1, M
2, M
3, M
4m
mwith F
1, F
2, F
3, F
4f
nproduce the decision content I of correlative factor in each personnel and project
ij;
The project correlative factor weights W producing in conjunction with starting point 1
1, W
2, W
3, W
4w
nthe decision content I of correlative factor in each personnel who produces with starting point 2 and project
ijbuild optimum team constructing plan;
Wherein, the quantity that m is personnel, n is the quantity of project correlative factor, i=1 ... m, j=1 ... n.
Be applied to the method that under multiple constraint project, team builds, the concrete steps of described method are as follows:
Step1, by personnel M
1, M
2, M
3, M
4m
mwith correlative factor F in project
1, F
2, F
3, F
4f
ncompare to determine between two, according to " AHP1～9 scaling law " the decision content I of correlative factor in personnel evaluation achievement data table is filled in out each personnel and project
ij;
Step2, by expert assessment method for the relevant plain F of project
1, F
2, F
3, F
4f
nobtain project correlative factor weights W
1, W
2, W
3, W
4w
n, entry item correlative factor weight table; Wherein project correlative factor weight is according to " W
1+ W
2+ W
3+ ... + W
n=1 " test;
Step3, according to the numerical value in personnel evaluation achievement data table and project correlative factor weight table, correspondence solves Iw
ij, fill in algorithm iteration relation table;
Step4, in algorithm iteration relation table, find out in every a line j maximum Iw
ijbe worth corresponding M
i:
If have and occurred identical M in multirow
i, by Iw maximum in corresponding row
ijvalue summation, obtains this M
ipersonnel selection weight evaluation index value;
If have and occurred M in a line
i, by Iw maximum in corresponding row
ijvalue is as this M
ipersonnel selection weight evaluation index value;
If there is no to occur in a line M
i, do not operate;
Step5, according to the corresponding M obtaining in Step4
ipersonnel selection weight evaluation index value carry out descending sequence, find maximum personnel selection weight evaluation index value, this personnel selection weight evaluation index is worth to corresponding M
ias the personnel that preferentially meet project;
Step6, will scratch in algorithm iteration relation table selected M in Step5
iiw in the i row at place
ijas the algorithm iteration relation table of getting after maximal value; According to the algorithm iteration table of getting after maximal value, continue to carry out iteration by the step of Step4, Step5, until find out all required team of this project, build personnel;
Wherein, the quantity that m is personnel, n is the quantity of project correlative factor, i=1 ... m, j=1 ... n.
Described Iw
ijcomputing formula be: Iw
ij=I
ij* W
j; I=1 wherein ... m, j=1 ... n, the quantity that m is personnel, n is the quantity of project correlative factor.
While continuing to carry out iteration with Step4 in described step Step6, find out Iw maximum in every a line j
ijbe worth corresponding M
ithe method of taking is: directly search or adopt the method for sensitivity analysis to search.
Embodiment 2: as shown in Figure 1, a kind of model that is applied to team's structure under multiple constraint project, comprising: project P, correlative factor F in project
1, F
2, F
3, F
4f
n, project correlative factor weights W
1, W
2, W
3, W
4w
n; Personnel M
1, M
2, M
3, M
4m
m, the decision content I of correlative factor in each personnel and project
ij;
With two starting point forms, build optimum team constructing plan:
Starting point 1: produce project correlative factor F by project P
1, F
2, F
3, F
4f
n, then for F
1, F
2, F
3, F
4f
nstructure project correlative factor weights W
1, W
2, W
3, W
4w
n;
Starting point 2: by personnel M
1, M
2, M
3, M
4m
mwith F
1, F
2, F
3, F
4f
nproduce the decision content I of correlative factor in each personnel and project
ij;
The project correlative factor weights W producing in conjunction with starting point 1
1, W
2, W
3, W
4w
nthe decision content I of correlative factor in each personnel who produces with starting point 2 and project
ijbuild optimum team constructing plan;
Wherein, the quantity that m is personnel, n is the quantity of project correlative factor, i=1 ... m, j=1 ... n.
Be applied to the method that under multiple constraint project, team builds, the concrete steps of described method are as follows:
Problem is described: take certain graduate " W-Sn separation project " as project source, (be designated as " P "), the correlative factor in project represents with " F ", alternative personnel's use " M " value representation extracts four Ren Weiyige team from this HR pool.
Known: the correlative factor of the reference in W-Sn separation project is 1. item types; 2. project specialty background; 3. project technical know-how structure; 4. project beginning and ending time; 5. project cycle; 6. project funds, 7. project yield, 8. Project contract constraint, the 9. social benefit of project.The alternative personnel that have the screening of 12 menarche in HR pool.
Step1, by personnel M
1, M
2, M
3, M
4m
12with correlative factor F in project
1, F
2, F
3, F
4f
9compare to determine between two, according to " AHP1～9 scaling law " the decision content I of correlative factor in personnel evaluation achievement data table (as shown in table 1) is filled in out each personnel and project
ij;
Step2, by expert assessment method for the relevant plain F of project
1, F
2, F
3, F
4f
9obtain project correlative factor weights W
1, W
2, W
3, W
4w
9, entry item correlative factor weight table (as shown in table 2); Wherein project correlative factor weight is according to " W
1+ W
2+ W
3+ ... + W
9=1 " test;
Step3, according to the numerical value in personnel evaluation achievement data table and project correlative factor weight table, correspondence solves Iw
ij, fill in algorithm iteration relation table (as shown in table 3); Wherein, described Iw
ijcomputing formula be: Iw
ij=I
ij* W
j; I=1 wherein ... m, j=1 ... n, the quantity that m is personnel, n is the quantity of project correlative factor.
Step4, in algorithm iteration relation table, find out in every a line j maximum Iw
ijbe worth corresponding M
i(as shown in table 4): if had, in multirow, occurred identical M
i, by Iw maximum in corresponding row
ijvalue summation, obtains this M
ipersonnel selection weight evaluation index value; If have and occurred M in a line
i, by Iw maximum in corresponding row
ijvalue is as this M
ipersonnel selection weight evaluation index value; If there is no to occur in a line M
i, do not operate; (operation as shown in Table 5,6)
Step5, according to the corresponding M obtaining in Step4
ipersonnel selection weight evaluation index value carry out descending sequence, find maximum personnel selection weight evaluation index value, this personnel selection weight evaluation index is worth to corresponding M
ias the personnel that preferentially meet project;
Wherein, the sequence of M value: M
12, M
1(M
6), M
5, M
10, M
4(M
11), M
3.So at M
12for the preferential personnel that select.
Step6, will scratch in algorithm iteration relation table selected M in Step5
iiw in the i row at place
ijas the algorithm iteration relation table (as shown in table 7) of getting after maximal value; According to the algorithm iteration table of getting after maximal value, continue to carry out iteration by the step of Step4, Step5, until find out all required team of this project, build personnel;
While continuing to carry out iteration with Step4 in described step Step6, find out Iw maximum in every a line j
ijvalue (as table 7) corresponding M
i(that is,, in the table data that obtain in the time of only need to carrying out to Step4 to previous step, personnel's row of the preferential selection that Step5 is obtained is searched to take the method for sensitivity analysis to search; Herein for there is M in the data in his-and-hers watches 4 " corresponding M " row
12row search) or the method for directly searching (that is, from the first row one until last column search successively).From scratching M
12row algorithm iteration relation table in be not difficult to find out, only in the option of " Project contract constraint " row maximal value by M
120.9 become M
110.8, the maximal value of all the other each row does not exert an influence.That is to say that this scratches M
12m to the second selection in above-mentioned steps five after row
1, M
6do not exert an influence, so select M in current iteration is selected
1, M
6.
Owing to not meeting the requirements of number, so continue operation, obtain algorithm iteration table as shown in table 8:
In table 8, find out Iw maximum in every a line j
ijvalue (as table 8) corresponding M
itake the method (the same description) of directly searching or the method (the same description) that adopts sensitivity analysis.In table 8, the M of project specialty background
1(M
6) 1.35 change to M
5(M
11) 1.2; The M of project technical know-how structure
11.35 change to M
100.9; The M of project social benefit
60.45 change to M
2(M
7) 0.35.
According to M value table, new M
5value is original 2.7 to add that 1.2 is 3.9; New M
11value is original 1.8 to add that 1.2 is 3.0; New M
10value is original 2.15 to add that 1.2 is 3.35; New M
2value is original 0 to add that 0.35 is 0.35; New M
7value is original 0 to add that 0.35 is 0.35.
From the value of M shown in table 9 table, can find out, wherein Iw is 3.9. to the maximum and corresponds to M
5so this selection personnel are M
5.According to the personnel of team, build the target of selecting four personnel, this screening is M
12, M
1, M
6, M
5these four personnel build team and carry out this project.
By reference to the accompanying drawings the specific embodiment of the present invention is explained in detail above, but the present invention is not limited to above-mentioned embodiment, in the ken possessing those of ordinary skills, can also under the prerequisite that does not depart from aim of the present invention, make various variations.
Claims (4)
1. be applied to the model that under multiple constraint project, team builds, it is characterized in that: comprising: project P, correlative factor F in project
1, F
2, F
3, F
4f
n, project correlative factor weights W
1, W
2, W
3, W
4w
n; Personnel M
1, M
2, M
3, M
4m
m, the decision content I of correlative factor in each personnel and project
ij;
With two starting point forms, build optimum team constructing plan:
Starting point 1: produce project correlative factor F by project P
1, F
2, F
3, F
4f
n, then for F
1, F
2, F
3, F
4f
nstructure project correlative factor weights W
1, W
2, W
3, W
4w
n;
Starting point 2: by personnel M
1, M
2, M
3, M
4m
mwith F
1, F
2, F
3, F
4f
nproduce the decision content I of correlative factor in each personnel and project
ij;
The project correlative factor weights W producing in conjunction with starting point 1
1, W
2, W
3, W
4w
nthe decision content I of correlative factor in each personnel who produces with starting point 2 and project
ijbuild optimum team constructing plan;
Wherein, the quantity that m is personnel, n is the quantity of project correlative factor, i=1 ... m, j=1 ... n.
2. be applied to the method that under multiple constraint project, team builds, it is characterized in that: the concrete steps of described method are as follows:
Step1, by personnel M
1, M
2, M
3, M
4m
mwith correlative factor F in project
1, F
2, F
3, F
4f
ncompare to determine between two, according to " AHP1～9 scaling law " the decision content I of correlative factor in personnel evaluation achievement data table is filled in out each personnel and project
ij;
Step2, by expert assessment method for the relevant plain F of project
1, F
2, F
3, F
4f
nobtain project correlative factor weights W
1, W
2, W
3, W
4w
n, entry item correlative factor weight table; Wherein project correlative factor weight is according to " W
1+ W
2+ W
3+ ... + W
n=1 " test;
Step3, according to the numerical value in personnel evaluation achievement data table and project correlative factor weight table, correspondence solves Iw
ij, fill in algorithm iteration relation table;
Step4, in algorithm iteration relation table, find out in every a line j maximum Iw
ijbe worth corresponding M
i:
If have and occurred identical M in multirow
i, by Iw maximum in corresponding row
ijvalue summation, obtains this M
ipersonnel selection weight evaluation index value;
If have and occurred M in a line
i, by Iw maximum in corresponding row
ijvalue is as this M
ipersonnel selection weight evaluation index value;
If there is no to occur in a line M
i, do not operate;
Step5, according to the corresponding M obtaining in Step4
ipersonnel selection weight evaluation index value carry out descending sequence, find maximum personnel selection weight evaluation index value, this personnel selection weight evaluation index is worth to corresponding M
ias the personnel that preferentially meet project;
Step6, will scratch in algorithm iteration relation table selected M in Step5
iiw in the i row at place
ijas the algorithm iteration relation table of getting after maximal value; According to the algorithm iteration table of getting after maximal value, continue to carry out iteration by the step of Step4, Step5, until find out all required team of this project, build personnel;
Wherein, the quantity that m is personnel, n is the quantity of project correlative factor, i=1 ... m, j=1 ... n.
3. the method that is applied to team's structure under multiple constraint project according to claim 2, is characterized in that: described Iw
ijcomputing formula be: Iw
ij=I
ij* W
j; I=1 wherein ... m, j=1 ... n, the quantity that m is personnel, n is the quantity of project correlative factor.
4. the method that is applied to team's structure under multiple constraint project according to claim 2, is characterized in that: while continuing to carry out iteration with Step4 in described step Step6, find out Iw maximum in every a line j
ijbe worth corresponding M
ithe method of taking is: directly search or adopt the method for sensitivity analysis to search.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410201069.0A CN104008444A (en) | 2014-05-14 | 2014-05-14 | Model and method applied to team construction under multi-constraint projects |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410201069.0A CN104008444A (en) | 2014-05-14 | 2014-05-14 | Model and method applied to team construction under multi-constraint projects |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104008444A true CN104008444A (en) | 2014-08-27 |
Family
ID=51369092
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410201069.0A Pending CN104008444A (en) | 2014-05-14 | 2014-05-14 | Model and method applied to team construction under multi-constraint projects |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104008444A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108053186A (en) * | 2017-12-28 | 2018-05-18 | 中科钢研节能科技有限公司 | A kind of new technology project is built together information analysis system and method |
| CN113793133A (en) * | 2021-09-26 | 2021-12-14 | 北京明略昭辉科技有限公司 | Team calendar processing method and system, electronic device and storage medium |
| CN117114386A (en) * | 2023-10-19 | 2023-11-24 | 北京一起网科技股份有限公司 | Workflow management system for designer and industrial worker |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103346617A (en) * | 2013-07-11 | 2013-10-09 | 国家电网公司 | Error logical judgment prevention system and judgment method considering multiple constraint conditions |
| CN103493084A (en) * | 2011-04-25 | 2014-01-01 | 索尼公司 | Evaluation device and evaluation method, service provision system, and computer program |
| CN103697863A (en) * | 2013-12-18 | 2014-04-02 | 中国空气动力研究与发展中心高速空气动力研究所 | Method for correcting measurement vibration of deformation video of multi-constrained wind tunnel test model |
-
2014
- 2014-05-14 CN CN201410201069.0A patent/CN104008444A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103493084A (en) * | 2011-04-25 | 2014-01-01 | 索尼公司 | Evaluation device and evaluation method, service provision system, and computer program |
| CN103346617A (en) * | 2013-07-11 | 2013-10-09 | 国家电网公司 | Error logical judgment prevention system and judgment method considering multiple constraint conditions |
| CN103697863A (en) * | 2013-12-18 | 2014-04-02 | 中国空气动力研究与发展中心高速空气动力研究所 | Method for correcting measurement vibration of deformation video of multi-constrained wind tunnel test model |
Non-Patent Citations (1)
| Title |
|---|
| 李博 等: "《多约束下的产品形态涉及计算机辅助系统研究》", 《中国机械工程》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108053186A (en) * | 2017-12-28 | 2018-05-18 | 中科钢研节能科技有限公司 | A kind of new technology project is built together information analysis system and method |
| CN108053186B (en) * | 2017-12-28 | 2021-01-05 | 中科钢研节能科技有限公司 | New technical project co-construction information analysis system and method |
| CN113793133A (en) * | 2021-09-26 | 2021-12-14 | 北京明略昭辉科技有限公司 | Team calendar processing method and system, electronic device and storage medium |
| CN117114386A (en) * | 2023-10-19 | 2023-11-24 | 北京一起网科技股份有限公司 | Workflow management system for designer and industrial worker |
| CN117114386B (en) * | 2023-10-19 | 2024-02-02 | 北京一起网科技股份有限公司 | Workflow management system for designer and industrial worker |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2021088436A1 (en) | Project scheduling method and apparatus for multi-language collaborative development | |
| Frini et al. | MUPOM: A multi-criteria multi-period outranking method for decision-making in sustainable development context | |
| CN103870647A (en) | Operation workshop scheduling modeling method based on genetic algorithm | |
| CN104699890A (en) | Modeling method of short-term forewarning model for heavy overload of distribution transformer of urban power network | |
| JP6694447B2 (en) | Big data calculation method and system, program, and recording medium | |
| He et al. | Construction of a 5D duration and cost optimisation model based on genetic algorithm and BIM | |
| Wang et al. | Evolution model with time lag effects for the coal industrial symbiosis system: A case study of Ordos, China | |
| Selvam et al. | Genetic algorithm based optimization for resource leveling problem with precedence constrained scheduling | |
| CN104008444A (en) | Model and method applied to team construction under multi-constraint projects | |
| Shang et al. | Production scheduling optimization method based on hybrid particle swarm optimization algorithm | |
| Leonard | Spatial development and innovation in Russia | |
| CN101930566B (en) | Hydrological experimental simulation system and method based on parallel system | |
| Li et al. | Research and application of computer aided design system for product innovation | |
| Jiang et al. | Embodied energy account of Chinese economy 2002 | |
| CN103763302A (en) | Web service combination generating method | |
| CN110298538B (en) | Intelligent workshop combined scheduling control method | |
| Zhu et al. | A Resource Scheduling Method for Enterprise Management Based on Artificial Intelligence Deep Learning | |
| CN106295834A (en) | A kind of method that parts stock shares optimization | |
| BISHOP | Optimization in geodesign | |
| Marzouk et al. | Selecting building materials using system dynamics and ant colony optimization | |
| Hongliang et al. | Appraisal of lean production's implementation | |
| Nasresfahani et al. | Scenario Planning of Iran’s Energy Futures by Combining Incasting Approach and Morphological Analysis by Combining Incasting Approach and Morphological Analysis | |
| Gao et al. | Application of fuzzy comprehensive evaluation method in engineering project risk management | |
| Zhang | Energy-saving optimization design of multi-story office buildings based on genetic algorithm | |
| Murtishaw et al. | Methodological and practical considerations for developing multiproject baselines for electric power and cement industry projects in Central America |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20140827 |
|
| RJ01 | Rejection of invention patent application after publication |