CN106503895A - A kind of virtual contract network Team Member method for optimizing - Google Patents

Abstract

The present invention proposes a kind of virtual contract network Team Member method for optimizing, from the candidate personnel of virtual network platform, by member profile and cooperative cooperating ability, build candidate member's general performance information model, project demands personnel are preferably conformed to by sequence, the uncertainty and conflict, the purpose of raising project cooperation efficiency reduced in network cooperation is reached.Step is：Build candidate member profile and cooperative cooperating capacity index system, set up the virtual contract network Team Member optimization model based on member's general performance, information is participated according to candidate member's personal information and candidate member's project, give a mark according to index, model solution is carried out using multi-objective optimization algorithm, Pareto optimal solutions are obtained.Obtain the candidate based on member's general performance information to sort, select the virtual contract network team of Suitable members' composition.The invention embodies candidate member's integration capability, realizes between Team Member the complementation of knowledge and ability and cooperates, and avoids personnel's collision problem in later stage cooperating process, lift group- incentive, with better application value from source.

Description

Virtual collaborative network team member optimization method

Technical Field

The invention relates to the technical field of information, in particular to a method for optimizing members of a virtual collaborative network team.

Background

With the development of information technologies such as cloud computing and big data, a virtual network platform has been applied in various industries as an innovative service mode for realizing resource optimization integration, cooperative allocation and on-demand use. At present, a virtual network platform widely adopts a virtual cooperation network team working mode, a temporary cooperation team is formed by gathering members of cross-region, cross-professional and cross-industry to cooperate with each other, and innovative tasks are completed through knowledge sharing and advantage complementation. Proper selection of virtual collaborative network team members is a prerequisite and basis for smooth performance and completion of project tasks.

The selection of members of the team of virtual collaborative networks requires consideration of not only the personal abilities of the members, but also collaborative collaboration abilities between candidate members. Excellent professional skills of members of the team and good cooperative relations among the members can promote communication among the members and improve satisfaction, so that uncertainty and conflict in network cooperation are reduced, complementation of resources, capability and advantages is achieved, success of cooperative work is achieved finally, and the aim which is difficult to achieve only by single body strength is achieved.

The existing research respectively discusses the problem from the aspects of member optimization index system establishment, qualitative analysis, quantitative analysis and the like, but the complex cooperative network factors in the virtual network platform are not well reflected, meanwhile, most decision methods only consider the personal professional ability of candidate members, the comprehensive ability expression of the members is rarely reflected, and the selected members can not be guaranteed to play good cooperative ability in later project cooperation.

Disclosure of Invention

Aiming at the problems in the prior art, the invention researches the work flow of the virtual cooperative network team under the virtual network platform environment, constructs a comprehensive index system reflecting the individual ability of team members and the cooperative ability among the members, and constructs the cross-region, cross-professional and cross-industry virtual cooperative network team according to the needs, so as to realize the complementary and effective cooperation of knowledge and ability among the team members, avoid the personnel conflict problem in the later cooperative process from the source and finally improve the team performance.

In order to achieve the above purpose, the invention provides a virtual collaborative network team member optimization method, which has the technical scheme that:

the virtual collaborative network team member optimization method is characterized by comprising the following steps: the method comprises the following steps:

step 1: constructing an index system of personal ability and cooperative ability of candidate members of the project;

step 2: establishing a virtual cooperative network team member optimization model based on member comprehensive performance;

and step 3: calling personal data information of candidate members from a platform user database, calling project participation information of the candidate members from a project database, and scoring according to each index in an index system;

and 4, step 4: substituting the candidate member index fraction obtained in the step 3 into the model established in the step 2, and solving the model by adopting a multi-objective optimization algorithm to obtain a Pareto optimal solution; and selecting members according to the candidate sequence represented by the obtained Pareto optimal solution to form a virtual collaborative network team.

Further, in a preferred embodiment, the method for selecting members of a virtual collaboration network team comprises: in the step 1, personal ability indexes of the candidate members are divided into work experience, professional ability and professional knowledge; in the step 1, the cooperative cooperation capability indexes of the candidate members are divided into member evaluation grades, the number of projects completed by cooperating with other members and the number of problems for assisting other members to solve; the member evaluation level is divided into a cooperation attitude, an exchange communication capability and a team cooperation capability.

Further, in a preferred embodiment, the method for selecting members of a virtual collaboration network team comprises: the step 2 of establishing the member preference model of the virtual collaborative network team based on the member comprehensive performance comprises the following steps:

step 2.1: establishing a member selection model based on personal ability information;

step 2.2: establishing a member selection model based on the cooperative cooperation capability information;

step 2.3: and synthesizing the member selection model based on the personal ability information and the member selection model based on the cooperative ability information to obtain a member optimization model based on the member comprehensive performance information, wherein the member optimization model is a dual-target 0-1 quadratic programming model.

Further, in a preferred embodiment, the method for selecting members of a virtual collaboration network team comprises: the member selection model based on personal ability information in step 2.1 is built by the following steps:

step 2.1.1: on a virtual cooperative network platform, after a customer submits a design task, a management team issues a task notice to h related network subgroups through rapid demand analysis, wherein the number of candidate members in a network subgroup j is n_jTotal number of candidate members for entry application to participate in the design taskThe number of selected target members in the network subgroup j is q_jTotal number of selected target members is

Marking n candidate members participating in design task of registration application as P_iI is 1, …, n; the personal ability evaluation index is I_gG is 1, …, l, each item is weighted by v_gAnd is andx_ias a decision variable, then candidate member P_iWhen selected x_i1, otherwise x_i＝0；

Step 2.1.2: constructing a personal ability evaluation index matrix R ═ R of candidate members_ig]_n×lWherein r is_igIs a candidate member P_iIn the index I of personal ability evaluation_gA score of; normalizing the personal ability evaluation index according to the benefit index and the cost index to obtain a matrix R '═ R'_ig]_n×l：

The benefit type index is as follows:

cost type index:

wherein

Step 2.1.3: according to the formulaComputing candidate members P_i(ii) individual performance composite value of;

step 2.1.4: according to the obtained individual performance comprehensive value of each candidate memberObtaining a personal performance preference model for the member:

x_i∈{0,1},i＝1,…,n

wherein,

further, in a preferred embodiment, the method for selecting members of a virtual collaboration network team comprises: the member selection model based on the cooperative cooperation capability information in the step 2.2 is obtained through the following steps:

step 2.2.1: establishing a collaborative performance information decision matrix of candidate membersWhereinIs a candidate member P_iIn the presence of candidate member P_tWhen performing cooperation, corresponding cooperative ability evaluation index C_k(ii) a synergy performance score; evaluation index C of cooperative ability_kK is 1, …, m, each item weight is w_kAnd is and

step 2.2.2: will be provided withNormalizing the elements in the matrix to obtain the matrix

The benefit type index is as follows:

cost type index:

wherein

Step 2.2.3: according to the formulai ≠ t computing candidate members P_iIn the presence of candidate member P_tCollaborative representation of composite value psi when performing collaboration_it；

Step 2.2.4: according to the obtained comprehensive value psi of the cooperative expression_itI, t ═ 1, …, n; and i ≠ t, and a member selection model based on the cooperative cooperation capability information is obtained:

x_i∈{0,1},i＝1,…,n

wherein,

further, in a preferred embodiment, the method for selecting members of a virtual collaboration network team comprises: the member optimization model based on the member comprehensive performance information in the step 2.3 is established through the following steps:

integrating the member individual performance optimization model obtained in the step 2.1.4 and the member cooperation optimization model obtained in the step 2.2.4 to obtain a double-target 0-1 quadratic programming model as follows:

x_i∈{0,1},i＝1,…,n

wherein,

advantageous effects

Aiming at the characteristics of network cooperativity and task complexity of a virtual network platform, the invention provides a member optimization method of a virtual collaborative network team based on member comprehensive performance information on the basis of the characteristics, not only considers member personal capability information, but also considers member collaborative cooperation capability, constructs an optimization index system and a mathematical model based on member comprehensive performance information, solves the model by utilizing a multi-objective evolutionary algorithm, obtains a Pareto optimal solution of a virtual team member selection problem, and a decision maker can select according to the preference of member individual performance and collaborative performance. The project members selected by the invention have good cooperation attitude, excellent communication capability, members with rich cooperation experience and good cooperative cooperation capability, can effectively promote the communication among the members, improve the satisfaction among the members, reduce the conflict and uncertainty of cooperation, and have important significance for the smooth development of virtual cooperative innovation work and the improvement of efficiency. The method can be further expanded to the process of building virtual teams in other backgrounds, and has certain application significance.

Drawings

FIG. 1 is a flow chart of a member optimization method of a virtual collaborative network team based on member comprehensive performance information according to an embodiment of the present invention;

FIG. 2 is an embodiment of the present invention providing an index system of personal competency and collaborative ability of candidate members of an item.

Detailed Description

The following detailed description of embodiments of the invention is intended to be illustrative, and not to be construed as limiting the invention.

The applicant researches the work flow of the virtual cooperative network team in the virtual network platform environment, constructs a comprehensive index system reflecting the individual ability of team members and the cooperative ability among the members, and based on the comprehensive index system, the virtual cooperative network team member optimization method provided by the invention realizes the construction of cross-region, cross-professional and cross-industry virtual cooperative network teams according to needs, realizes the complementation and effective cooperation of knowledge and ability among the team members, avoids the problem of personnel conflict in the later cooperative process from the source, and finally improves the team performance.

The virtual collaborative network team member optimization method of the invention is specifically realized by the following steps as shown in figure 1:

step 1: constructing an index system of personal ability and cooperative ability of candidate members of the project, as shown in FIG. 2:

the personal ability indexes are divided into work experience, professional ability and professional knowledge, and the personal performance ability of the candidate members is inspected through the work experience, the professional ability and the professional knowledge; the cooperative cooperation capability index is divided into member evaluation level, the number of projects completed by cooperating with other people and the number of problems for assisting other members to solve; and inspecting the cooperative cooperation capability information of the candidate members by adopting member evaluation grades, the number of projects which are finished by cooperation with other members in the past and the number of problems solved by other members, wherein the member evaluation grades are divided into cooperation attitude, communication capability and team cooperation capability.

Step 2: establishing a virtual cooperative network team member optimization model based on member comprehensive performance; the method comprises the following steps:

step 2.1: establishing a member selection model based on personal capability information, and establishing the member selection model by the following steps:

step 2.1.1: on a virtual cooperative network platform, after a customer submits a design task, a management team issues a task notice to h related network subgroups through rapid demand analysis, wherein the number of candidate members in a network subgroup j is n_jTotal number of candidate members for entry application to participate in the design taskThe number of selected target members in the network subgroup j is q_jTotal number of selected target members is

Marking n candidate members participating in design task of registration application as P_iI is 1, …, n; the personal ability evaluation index is I_gG is 1, …, l, each item is weighted by v_gAnd is andx_ias a decision variable, then candidate member P_iWhen selected x_i1, otherwise x_i＝0；

Step 2.1.2: constructing a personal ability evaluation index matrix R ═ R of candidate members_ig]_n×lWherein r is_igIs a candidate member P_iIn the index I of personal ability evaluation_gA score of; will personalThe capability evaluation index is normalized according to the benefit index and the cost index to obtain a matrix R '═ R'_ig]_n×l，

The benefit type index is as follows:

cost type index:

wherein,

step 2.1.3: according to the formulaComputing candidate members P_i(ii) individual performance composite value of;

step 2.1.4: according to the obtained individual performance comprehensive value of each candidate memberObtaining a member optimization model based on member comprehensive performance information:

x_i∈{0,1},i＝1,…,n

step 2.2: establishing a member selection model based on cooperative cooperation capability information, and obtaining the member selection model through the following steps:

step 2.2.1: build candidateMember collaborative performance information decision matrixWhereinIs a candidate member P_iIn the presence of candidate member P_tWhen performing cooperation, corresponding cooperative ability evaluation index C_k(ii) a synergy performance score; evaluation index C of cooperative ability_kK is 1, …, m, each item weight is w_kAnd is and

step 2.2.2: will be provided withNormalizing the elements in the matrix to obtain the matrix

The benefit type index is as follows:

cost type index:

wherein

Step 2.2.3: according to the formulai ≠ t computing candidate members P_iIn the presence of candidate member P_tCollaborative representation of composite value psi when performing collaboration_it；

Step 2.2.4: according to the obtained comprehensive value psi of the cooperative expression_itI, t ═ 1, …, n; and i ≠ t, and a member selection model based on the cooperative cooperation capability information is obtained:

x_i∈{0,1},i＝1,…,n

wherein,

step 2.3: synthesizing a member selection model based on the personal ability information and a member selection model based on the cooperative ability information to obtain a member optimization model based on the member comprehensive performance information, wherein the member optimization model is a dual-target 0-1 quadratic programming model:

x_i∈{0,1},i＝1,…,n

wherein,

and step 3: and calling personal data information of the candidate members from the platform user database, calling project participation information of the candidate members from the project database, and scoring according to each index in the index system.

And 4, step 4: substituting the candidate member index score obtained in the step 3 into the model established in the step 2, and adopting a multi-objective optimization algorithm: solving the model by a second generation enhanced Pareto evolutionary algorithm (SPEA2) to obtain a Pareto optimal solution; and according to the requirements of the design task and the decision preference, selecting different member combinations according to the personal abilities and the cooperative ratio of the candidate members. And selecting members according to the obtained candidate sequence represented by the Pareto optimal solution to form a virtual collaborative network team.

Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made in the above embodiments by those of ordinary skill in the art without departing from the principle and spirit of the present invention.

Claims (6)

1. A virtual collaborative network team member optimization method is characterized by comprising the following steps: the method comprises the following steps:

step 1: constructing an index system of personal ability and cooperative ability of candidate members of the project;

step 2: establishing a virtual cooperative network team member optimization model based on member comprehensive performance;

and step 3: calling personal data information of candidate members from a platform user database, calling project participation information of the candidate members from a project database, and scoring according to each index in an index system;

and 4, step 4: substituting the candidate member index fraction obtained in the step 3 into the model established in the step 2, and solving the model by adopting a multi-objective optimization algorithm to obtain a Pareto optimal solution; and selecting members according to the candidate sequence represented by the obtained Pareto optimal solution to form a virtual collaborative network team.

2. The method for team member optimization in virtual collaborative network according to claim 1, wherein: in the step 1, personal ability indexes of the candidate members are divided into work experience, professional ability and professional knowledge; in the step 1, the cooperative cooperation capability indexes of the candidate members are divided into member evaluation grades, the number of projects completed by cooperating with other members and the number of problems for assisting other members to solve; the member evaluation level is divided into a cooperation attitude, an exchange communication capability and a team cooperation capability.

3. The method for team member optimization in virtual collaborative network according to claim 1, wherein: the step 2 of establishing the member preference model of the virtual collaborative network team based on the member comprehensive performance comprises the following steps:

step 2.1: establishing a member selection model based on personal ability information;

step 2.2: establishing a member selection model based on the cooperative cooperation capability information;

step 2.3: and synthesizing the member selection model based on the personal ability information and the member selection model based on the cooperative ability information to obtain a member optimization model based on the member comprehensive performance information, wherein the member optimization model is a dual-target 0-1 quadratic programming model.

4. The method for team member preference in virtual collaborative network as claimed in claim 2, wherein: the member selection model based on personal ability information in step 2.1 is built by the following steps:

step 2.1.1: on a virtual cooperative network platform, after a customer submits a design task, a management team analyzes the task through rapid demand analysisThe announcements are sent to h related network subgroups, wherein the number of candidate members in the network subgroup j is n_jTotal number of candidate members for entry application to participate in the design taskThe number of selected target members in the network subgroup j is q_jTotal number of selected target members is

Marking n candidate members participating in design task of registration application as P_iI is 1, …, n; the personal ability evaluation index is I_gG is 1, …, l, each item is weighted by v_gAnd is andx_ias a decision variable, then candidate member P_iWhen selected x_i1, otherwise x_i＝0；

Step 2.1.2: constructing a personal ability evaluation index matrix R ═ R of candidate members_ig]_n×lWherein r is_igIs a candidate member P_iIn the index I of personal ability evaluation_gA score of; normalizing the personal ability evaluation index according to the benefit index and the cost index to obtain a matrix R '═ R'_ig]_n×l：

The benefit type index is as follows:

cost type index:

wherein

Step 2.1.3: according to the formulaComputing candidate members P_i(ii) individual performance composite value of;

step 2.1.4: according to the obtained individual performance comprehensive value of each candidate memberObtaining a personal performance preference model for the member:

$\begin{array}{ccc}s.t.& \underset{i\∈n_j}{\Σ}{x}_i=q_j,& j=1,...,h,\end{array}$

x_i∈{0,1},i＝1,…,n

wherein,

5. the method for team member preference in virtual collaborative network as claimed in claim 2, wherein: the member selection model based on the cooperative cooperation capability information in the step 2.2 is obtained through the following steps:

step 2.2.1: establishing a collaborative performance information decision matrix of candidate membersWhereinIs a candidate member P_iIn the presence of candidate member P_tWhen performing cooperation, corresponding cooperative ability evaluation index C_k(ii) a synergy performance score; evaluation index C of cooperative ability_kK is 1, …, m, each item weight is w_kAnd is and

step 2.2.2: will be provided withNormalizing the elements in the matrix to obtain the matrix

The benefit type index is as follows:

cost type index:

wherein

Step 2.2.3: according to the formulaComputing candidate members P_iIn the presence of candidate member P_tCollaborative representation of composite value psi when performing collaboration_it；

Step 2.2.4: according to the obtained comprehensive value psi of the cooperative expression_itI, t ═ 1, …, n; and i ≠ t, and a member selection model based on the cooperative cooperation capability information is obtained:

$\max Z_2=\underset{i=1}{\overset{n}{\Σ}}\underset{t\≠i}{\overset{n}{\underset{t=1}{\Σ}}}{\mathrm{\ψ}}_{it}{x}_i{x}_t$

$\begin{array}{ccc}s.t.& \underset{i\∈n_j}{\Σ}{x}_i=q_j,& j=1,...,h\end{array}$

x_i∈{0,1},i＝1,…,n

wherein,

6. the method for team member preference in virtual collaborative network as claimed in claim 2, wherein: the member optimization model based on the member comprehensive performance information in the step 2.3 is established through the following steps:

integrating the member individual performance optimization model obtained in the step 2.1.4 and the member cooperation optimization model obtained in the step 2.2.4 to obtain a double-target 0-1 quadratic programming model as follows:

$\max Z_2=\underset{i=1}{\overset{n}{\Σ}}\underset{t\≠i}{\overset{n}{\underset{t=1}{\Σ}}}{\mathrm{\ψ}}_{it}{x}_i{x}_t$

$\begin{array}{ccc}s.t.& \underset{i\∈n_j}{\Σ}{x}_i=q_j,& j=1,...,h\end{array}$

x_i∈{0,1},i＝1,…,n

wherein,