Human resource planning method and system capable of simultaneously meeting strategic and operation targets

Abstract

The invention relates to the technical field of human resource planning, in particular to a human resource planning method and system capable of simultaneously meeting strategic and operation objectives, and the method comprises the steps: firstly constructing a flow network model according to an organization to be subjected to human resource planning, and achieving the expression of a human resource management strategy through the definition of the capacity of a node and the limitation of an arc; constructing a mixed integer target planning problem according to the requirements of the organization on the strategic level and the operation level; solving the mixed integer target planning problem through a mathematical optimization solver, and determining the optimal flow of the network; and finally, analyzing and evaluating a solution output by the solver, and outputting a human resource planning scheme. Different from a general method of emphasizing strategic planning and then processing operation planning, the method provided by the invention solves the problem of separation of strategic and operation planning, allows simultaneous searching of optimal planning on strategic and operation levels, and realizes reasonable balance of organizational personnel structures.

Description

Technical Field

[0001] The present invention relates to the technical field of human resource planning, and in particular to a human resource planning method and system that simultaneously meets strategic and operational objectives. Background Art

[0002] Human resource planning is a series of planned human resource deployment and management activities that organizations carry out to ensure the achievement of strategic and operational goals, usually including estimation of human resource demand, assessment of human resource availability, and matching of human resource demand with available resources. Organizations formulate corresponding strategies for acquiring, utilizing, retaining and developing human resources by forecasting human resource demand and supply in the future to ensure that they have the right number, quality and structure of personnel at the required time and position, thereby achieving a long-term balance between organizational and individual development.

[0003] Human resource planning usually consists of strategic and operational plans. Strategic planning aims to guide the strategic allocation of human resources, focusing on the organization's long-term demand and supply strategies, such as recruitment, promotion and retirement strategies. Strategic planning usually involves the accessibility and maintainability of human resource distribution, hoping to achieve a specific and stable distribution. Operational planning aims to allocate appropriate personnel with required characteristics to actual jobs, focusing on the realization of the organization's daily business goals. Operational planning usually involves the sustainability of human resource distribution, expecting human resource allocation to be optimally competitive.

[0004] Human resource planning approaches generally focus on strategic planning and then address operational needs based on the strategic planning results. However, human resources deployed in this way do not ensure that needs at both the strategic and operational levels are met. In fact, strategies for one type of planning may have an impact on planning for another type. Decisions made to meet short-term operational goals have both short-term and long-term effects on the composition of future human resources, which may lead to failure to meet strategic goals.

[0005] Strategic planning and operational planning of human resources influence each other. Strategic planning provides direction and guidance for operational planning, while operational planning is the key to the implementation and implementation of strategic planning. Defining strategic and operational goals separately does not guarantee consistency between the two goals. In the case of inconsistent goal definitions, strategic and operational goals cannot usually be achieved at the same time. For example, the strategic strategy that an organization intends to implement is to force a reduction in personnel by lowering the retirement age, which means that the organization will lose senior personnel at the operational level and even lead to a talent deficit. Summary of the invention

[0006] The present invention aims to solve the problem that the separation of strategic planning and operational planning makes it impossible for human resource deployment to meet the needs of both the strategic and operational levels at the same time. A human resource planning method and system that simultaneously meet the strategic and operational goals are proposed. On the basis of simultaneously meeting the needs of both the strategic and operational levels, the optimal human resource planning solution is obtained to provide reliable support for the personnel deployment of the enterprise.

[0007] To achieve the above purpose, the technical solution adopted is:

[0008] An approach to workforce planning that meets both strategic and operational objectives includes the following steps:

[0009] Firstly, a flow network model is constructed according to the organization for which human resource planning is to be carried out, and the human resource management strategy is expressed by defining the capacity of nodes and the restrictions on arcs.

[0010] Then, a mixed integer goal programming problem is constructed based on the organization’s needs at both the strategic and operational levels;

[0011] Then the mixed integer objective programming problem is solved by a mathematical optimization solver to determine the optimal flow of the network;

[0012] Finally, the solution output by the solver is analyzed and evaluated, and the human resource planning plan is output.

[0013] According to the human resource planning method that simultaneously meets strategic and operational goals of the present invention, further, each node of the flow network model represents a homogeneous personnel group; all possible nodes in the same year form a layer, expressing the distribution of human resources in that year; the arcs between nodes of different layers of the flow network represent the flow of human resources, and each arc represents the eligibility of one personnel group to transfer to another personnel group.

[0014] According to the human resource planning method that simultaneously meets strategic and operational goals of the present invention, further, each layer of the flow network model includes two special nodes, a source node and a sink node. The source node expresses the annual recruitment capacity of the organization and is provided to the basic nodes through arcs with limited capacity; the sink node represents the node that retires and leaves the organization, and the flow flowing to the node represents the personnel who are about to retire; the first node of each layer in the flow network is the source node, and the last node is the sink node; in addition, other basic nodes are represented as flow nodes. In order to consider the loss of human resources caused by leaving the organization other than retirement situations, the flow passing through the flow nodes will be lost according to a attrition rate.

[0015] According to the human resource planning method that simultaneously meets strategic and operational goals of the present invention, further, the method of defining the capacity of a node is: representing the distribution of human resources according to the needs of the organization at the strategic level and the operational level, and converting the distribution of human resources into the number of personnel in the node set.

[0016] According to the human resource planning method that satisfies both strategic and operational goals of the present invention, further, the construction of the mixed integer goal programming problem includes defining decision variables:

[0017] Let N be the number of personnel nodes at a certain level, M be the number of levels considered, and define the following variables: N rec is the source node, Nret is the sink node, Ly={1,2,...,N,Nrec,Nret} is the node set of the yth layer, K y is the number of demand sets at each layer, SY is the service life, R y (i) is the node set of the i-th requirement subset on the y-th layer, rm y (i) is the number of the i-th demand subset on the y-th layer, A(i) is the initial personnel of node i∈L0, X y (i,j) is the slave node i∈L y To node j∈L y+1 The flow of arcs, is the set of nodes connected to the source node in the yth layer, is the set of nodes connected to the sink node in the yth layer, is the maximum recruitment capacity allowed for the yth level, is the retirement capacity of the y≤SY layer, α is the annual attrition rate, is the positive or negative deviation of the target value of the i-th demand subset on the y-th layer.

[0018] According to the human resource planning method that satisfies both strategic and operational objectives of the present invention, further, the construction of the mixed integer objective programming problem includes defining an objective function:

[0019] The objective function is defined as minimizing the sum of deviations from the target distribution:

[0020]

[0021] According to the human resource planning method that satisfies both strategic and operational goals of the present invention, further, the construction of the mixed integer goal programming problem includes defining constraints:

[0022] The first rigid constraint associated with the model is defined as the initial human resource condition, which requires that every person present in the first layer should move to the next layer:

[0023]

[0024] The second rigid constraint associated with the model is defined as the flow condition, which requires that for each node present in the middle layer, the total amount of flow from the previous layer must flow into the next layer:

[0025]

[0026] The rigid constraints related to personnel management are defined as follows: recruitment policy for the entire study period, retirement policy that depends on the initial human resources, and specified retirement policy that depends on the previous part of recruitment, respectively:

[0027]

[0028]

[0029] According to the human resource planning method that satisfies both strategic and operational objectives of the present invention, further, the objective constraint is expressed as the deviation between the number of personnel required each year and the target value:

[0030]

[0031] According to the human resource planning method that simultaneously meets strategic and operational goals of the present invention, further, CPLEX, Gurobi, SCIP or Xpress solver is selected for solving the mixed integer goal programming problem.

[0032] Furthermore, the present invention also provides a human resource planning system that simultaneously meets strategic and operational goals, which is used to implement the human resource planning method that simultaneously meets strategic and operational goals as described above, and the system includes a model building module, a goal planning module, a solution module and a solution output module, wherein:

[0033] The model building module is used to build a flow network model according to the organization that intends to carry out human resource planning, and to express the human resource management strategy by defining the capacity of the nodes and the restrictions on the arcs;

[0034] Goal Planning module, which is used to construct mixed integer goal programming problems based on the organization's strategic and operational needs;

[0035] The solution module is used to solve the mixed integer objective programming problem through a mathematical optimization solver to determine the optimal flow of the network;

[0036] The solution output module is used to analyze and evaluate the solution output by the solver and output the human resource planning solution.

[0037] The beneficial effects achieved by adopting the above technical solution are:

[0038] The present invention proposes a human resource planning method that meets both strategic and operational goals. The organization to be human resource planning is modeled, and then based on the flow network model, the capacity of the node and the restriction on the arc are used to express the human resource management strategy. Then, a mixed integer goal planning problem is constructed according to the organization's needs at the strategic and operational levels. The optimal flow of the network is determined by solving the problem to output the human resource planning solution. Different from the general practice of focusing on strategic planning and then dealing with operational planning, the proposed method makes up for the separation of strategic and operational planning, allowing the optimal planning to be searched at the strategic and operational levels at the same time, and achieving a reasonable balance of the organizational personnel structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings of the embodiments of the present invention, wherein the drawings are only used to illustrate some embodiments of the present invention, but not to limit all embodiments of the present invention thereto.

[0040] Figure 1 is a flow chart of a method for human resource planning that simultaneously meets strategic and operational goals according to an embodiment of the present invention;

[0041] Figure 2 is a schematic diagram of the structure of a flow network model constructed according to an embodiment of the present invention;

[0042] Figure 3 It is a structural diagram of a certain layer in the flow network model constructed in an embodiment of the present invention;

[0043] Figure 4 is a schematic diagram of human resource distribution expected by an embodiment of the present invention, showing target distribution of occupational level and occupational type, job grade and job type respectively;

[0044] Figure 5 is the expected evolution of the distribution of human resources of different job types and different professional levels in the embodiment of the present invention;

[0045] Figure 6 It is the expected evolution of the distribution of human resources of different occupational types and different job levels in the embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings of specific embodiments of the present invention to clearly and completely describe the exemplary scheme of the embodiment of the present invention. Unless otherwise defined, the technical terms or scientific terms used in the present invention should be the common meanings understood by people with ordinary skills in the field.

[0047] like Figure 1 As shown, this embodiment discloses a human resource planning method that meets both strategic and operational goals, comprising the following steps:

[0048] Step S101: construct a flow network model according to the organization for which human resource planning is to be carried out, and express the human resource management strategy by defining the capacity of the nodes and the restrictions on the arcs.

[0049] Each node of the flow network model represents a homogeneous group of personnel, including personnel with the same characteristics (such as grade, qualifications, skills) and holding the same job requirements in a certain year. All possible nodes in the same year form a layer, expressing the distribution of human resources in that year. The arcs between nodes in different layers of the flow network represent the flow of human resources, including recruitment, promotion, transfer and retirement, and each arc represents the qualifications of one group of personnel to transfer to another group of personnel.

[0050] Each layer of the flow network model contains two special nodes, the source node and the sink node. The source node expresses the annual recruitment capacity of the organization and is provided to the basic nodes through arcs with limited capacity. The sink node represents the node that retires and leaves the organization, and the flow flowing to this node represents the personnel who are about to retire. The first node of each layer in the flow network is the source node, and its supply represents the initial human resources, while the last node is the sink node because there is no flow that can continue to move down. In addition, other basic nodes are represented as flow nodes. In order to consider the loss of human resources caused by leaving the organization other than retirement, the flow through the flow node will be lost according to a reduction rate.

[0051] The method of defining node capacity is to represent the human resource distribution according to the needs of the organization at the strategic and operational levels; and to convert the human resource distribution into the number of people in the node set. For example, if the organization requires a hierarchical distribution, all nodes representing the same level will be gathered in the same set to correspond to the classification of the required distribution.

[0052] Step S102: construct a mixed integer goal programming problem according to the organization's needs at the strategic level and the operational level.

[0053] The formulation of the mixed integer goal programming problem involves defining the decision variables, the objective function, and the constraints:

[0054] Let N be the number of personnel nodes at a certain level, M be the number of levels considered, and define the following variables: N rec is the source node, Nret is the sink node, Ly={1,2,...,N,Nrec,Nret} is the node set of the yth layer, K y is the number of demand sets at each level, SY is the service years (from recruitment to retirement), R y (i) is the node set of the i-th requirement subset on the y-th layer, rm y(i) is the number of the i-th demand subset on the y-th layer, A(i) is the initial personnel of node i∈L0, X y (i,j) is the distance from node i∈Ly to node j∈Ly +1 The flow of arcs, is the set of nodes connected to the source node at the yth layer (recruitment), is the set of nodes connected to the sink node at the yth layer (retired or resigned), is the maximum recruitment capacity allowed for the yth level, is the retirement capacity of the y≤SY layer (i.e., the initial number of people retiring in the yth year), α is the annual attrition rate, is the positive or negative deviation of the target value of the i-th demand subset on the y-th layer.

[0055] The objective function is defined as minimizing the sum of deviations from the target distribution:

[0056]

[0057] The first rigid constraint associated with the model is defined as the initial human resource condition, which requires that every person present in the first layer should move to the next layer:

[0058]

[0059] The second rigid constraint associated with the model is defined as the flow condition, which requires that for each node present in the middle layer, the total amount of flow from the previous layer must flow into the next layer:

[0060]

[0061] The rigid constraints related to personnel management are defined to meet different distributions of requirements at the strategic and operational levels, including recruitment policy for the entire study period, retirement policy depending on the initial human resources, and designated retirement policy dependent on the previous part of recruitment, as follows:

[0062]

[0063] The target constraint is expressed as the deviation between the number of personnel required each year and the target value:

[0064]

[0065] Step S103: Solve the mixed integer objective programming problem by using a mathematical optimization solver to determine the optimal flow of the network.

[0066] To solve the mixed integer goal programming problem, choose a suitable mathematical optimization solver, such as CPLEX, Gurobi, SCIP or Xpress, etc. These solvers are usually based on different algorithms, such as branch and bound method, cutting plane method, column generation method, etc. Taking the cutting plane method as an example, its solution process usually includes solving the relaxed problem, checking the optimal solution, adding cutting planes, and repeating the solution:

[0067] First, without considering the integer constraints, the mixed integer programming problem is transformed into a linear programming problem (called a relaxed problem); a linear programming solution algorithm (such as the simplex method) is used to solve the relaxed problem and obtain the optimal solution; check whether the optimal solution of the relaxed problem is an integer solution; if it is an integer solution, then this solution is the optimal solution to the mixed integer programming problem and the solution process ends; if it is not an integer solution, it is necessary to add a cutting plane, and a cutting plane is constructed based on the non-integer optimal solution of the relaxed problem. The cutting plane needs to meet the above two conditions, that is, it can cut off the non-integer optimal solution while retaining the integer feasible domain; the cutting plane is added to the original problem as a new constraint to form a new linear programming problem; repeat the above steps, continuously solve new linear programming problems, and add new cutting planes until an integer optimal solution is found.

[0068] Step S104: Analyze and evaluate the solution output by the solver, and output a human resource planning solution.

[0069] Analyze the solution given by the solver, including the objective function value, the value of the decision variables, etc., verify whether the solution meets all constraints, and evaluate the quality of the solution. If the solution does not meet the requirements or needs further optimization, you can adjust the model parameters, change the solution strategy, or try a different solver, and then solve it again.

[0070] Corresponding to the above method, this embodiment also discloses a human resource planning system that meets both strategic and operational goals. The system includes a model building module, a goal planning module, a solution module, and a solution output module, wherein:

[0071] The model building module is used to build a flow network model according to the organization that intends to carry out human resource planning, and to express the human resource management strategy by defining the capacity of the nodes and the restrictions on the arcs.

[0072] The goal planning module is used to formulate mixed integer goal planning problems based on the organization's strategic and operational needs.

[0073] The solution module is used to solve the mixed integer objective programming problem through a mathematical optimization solver to determine the optimal flow of the network.

[0074] The solution output module is used to analyze and evaluate the solution output by the solver and output the human resource planning solution.

[0075] In order to verify the effectiveness of this solution, further explanation is given below in combination with experimental data.

[0076] The organization that intends to conduct human resource planning in this experiment considers the distribution of career levels and career types at the strategic level, and job levels and job types at the operational level. There are three levels of careers, A, B and C, and two types of establishment and contract. There are three levels of jobs, b, c and d, and five types. Figure 2 The schematic diagram of the constructed flow network model is shown in Figure 2. Figure 3 A schematic diagram of a layer in a flow network.

[0077] This experiment intends to find a human resource allocation adjustment that will adjust the number of employees from more than 2,700 to less than 2,500 while respecting the new target allocation. Figure 4 As shown, the target distribution of occupational level and occupational type, and job grade and type are shown respectively.

[0078] This experiment intends to consider a maximum career planning period of 45 years for personnel development, set the time span of the entire human resource planning to 65 years, and estimate the annual attrition rate to be α = 1%. The organization's initial staff size is 2,784, including 299 people in training, and hopes to achieve the target distribution within ten years. The target constraints are:

[0079]

[0080] Using CPLEX optimizer (IBM CPLEX Optimizer, 2020), this mixed integer programming problem is solved and a solution is generated to derive the action plan to be executed and the expected development of human resources at different levels. Figure 5 The expected evolution of the distribution of human resources for different job types and different career levels is illustrated. Although the overall goal is to reduce the total number of personnel, it can be seen that there is a growth in personnel in the early stages of planning. The model assumes that the cost of the first 10 years of the study is zero in order to adjust the allocation of human resources to reach the target as soon as possible. After 10 years of planning, the expected distribution of each job type is close to the target, and the target is reached in about 15 years.

[0081] Figure 6The expected evolution of the distribution of human resources across career types and job grades is illustrated after the organization follows the strategic and operational plan. The target values ​​for job grades are met within 10 years, while the expected distribution for career types is met approximately over 40 years of the planning period, matching the longest career life and corresponding to the initial human resource retirements. Initially, this experiment was designed to find a solution that would achieve the target distribution within the required deadline. However, the results obtained from the model representing organizational behavior show that it would take more than 40 years to achieve all the target distributions. In order to achieve the target distribution, the organization needs to consider imposing rules, such as promoting voluntary retirement of personnel or mandatory mid-career retirement to increase opportunities for contract personnel.

[0082] Unless otherwise specifically stated, the components, steps, numerical expressions and values ​​set forth in these embodiments do not limit the scope of the present invention.

[0083] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0084] The units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person of ordinary skill in the art may use different methods to implement the described functions for each specific application, but such implementation is not considered to be beyond the scope of the present invention.

[0085] Those skilled in the art will appreciate that all or part of the steps in the above method can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, such as a read-only memory, a disk or an optical disk. Optionally, all or part of the steps in the above embodiment can also be implemented using one or more integrated circuits, and accordingly, each module / unit in the above embodiment can be implemented in the form of hardware or in the form of software function modules. The present invention is not limited to any specific form of combination of hardware and software.

[0086] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A human resource planning method that meets both strategic and operational objectives, characterized in that: The following steps are involved: Firstly, a flow network model is constructed according to the organization for which human resource planning is to be carried out, and the human resource management strategy is expressed by defining the capacity of nodes and the restrictions on arcs. Then, a mixed integer goal programming problem is constructed based on the organization’s needs at both the strategic and operational levels; Then the mixed integer objective programming problem is solved by a mathematical optimization solver to determine the optimal flow of the network; Finally, the solution output by the solver is analyzed and evaluated, and the human resource planning plan is output.

2. The method for human resource planning that simultaneously meets strategic and operational goals according to claim 1, characterized in that: Each node of the flow network model represents a homogeneous group of personnel; all possible nodes in the same year form a layer, expressing the distribution of human resources in that year; the arcs between nodes in different layers of the flow network represent the flow of human resources, and each arc represents the eligibility of one personnel group to transfer to another personnel group.

3. The method for human resource planning that simultaneously meets strategic and operational goals according to claim 2, characterized in that: Each layer of the flow network model contains two special nodes, a source node and a sink node. The source node expresses the annual recruitment capacity of the organization and is provided to the basic nodes through arcs with limited capacity. The sink node represents the node that retires and leaves the organization, and the flow flowing to the node represents the personnel who are about to retire. The first node of each layer in the flow network is the source node, and the last node is the sink node. In addition, other basic nodes are represented as flow nodes. In order to consider the loss of human resources caused by leaving the organization other than retirement situations, the flow passing through the flow nodes will be lost according to a attrition rate.

4. The method for human resource planning that simultaneously meets strategic and operational goals according to claim 1, characterized in that: The method for defining the capacity of a node is: expressing the human resource distribution according to the needs of the organization at the strategic level and the operational level, and converting the human resource distribution into the number of personnel in the node set.

5. The method for human resource planning that simultaneously meets strategic and operational goals according to claim 1, characterized in that: The formulation of the mixed integer goal programming problem involves defining the decision variables: Let N be the number of personnel nodes at a certain level, M be the number of levels considered, and define the following variables: N rec is the source node, N ret is the sink node, L y ={1,2,...,N,N rec ,N ret } is the node set of the yth layer, K y is the number of demand sets at each layer, SY is the service life, R y (i) is the node set of the i-th demand subset on the y-th layer, rm y (i) is the number of the i-th demand subset on the y-th layer, A(i) is the initial personnel of node i∈L0, X y (i,j) is the slave node i∈L y To node j∈L y+1 The flow of arcs, is the set of nodes connected to the source node in the yth layer, is the set of nodes connected to the sink node in the yth layer, is the maximum recruitment capacity allowed for the yth level, is the retirement capacity of the y≤SY layer, α is the annual attrition rate, is the positive or negative deviation of the target value of the i-th demand subset on the y-th layer.

6. The method for human resource planning that simultaneously meets strategic and operational goals according to claim 5, characterized in that: The formulation of the mixed integer goal programming problem consists of defining the objective function: The objective function is defined as minimizing the sum of deviations from the target distribution:

7. The method for human resource planning that simultaneously meets strategic and operational goals according to claim 6, characterized in that: The formulation of the mixed integer goal programming problem involves defining the constraints: The first rigid constraint associated with the model is defined as the initial human resource condition, which requires that every person present in the first layer should move to the next layer: The second rigid constraint associated with the model is defined as the flow condition, which requires that for each node present in the middle layer, the total amount of flow from the previous layer must flow into the next layer: The rigid constraints related to personnel management are defined as follows: recruitment policy for the entire study period, retirement policy that depends on the initial human resources, and specified retirement policy that depends on the previous part of recruitment, respectively: y∈{0,1,2,...,M-2,} y=0,1,...,SY-1 y=SY,SY+1,...,M-2 8. The method for human resource planning that simultaneously meets strategic and operational goals according to claim 7, characterized in that: The target constraint is expressed as the deviation between the number of personnel required each year and the target value:

9. The method of human resource planning that simultaneously meets strategic and operational goals according to claim 1, characterized in that: For solving mixed integer goal programming problems, choose CPLEX, Gurobi, SCIP or Xpress solvers.

10. A human resource planning system that meets both strategic and operational objectives, characterized in that: A method for human resource planning that simultaneously satisfies strategic and operational goals as claimed in any one of claims 1 to 9, the system comprising a model building module, a goal planning module, a solution module and a solution output module, wherein: The model building module is used to build a flow network model according to the organization that intends to carry out human resource planning, and to express the human resource management strategy by defining the capacity of the nodes and the restrictions on the arcs; The goal planning module is used to construct mixed integer goal planning problems based on the organization's strategic and operational needs; A solution module is used to solve the mixed integer objective programming problem through a mathematical optimization solver to determine the optimal flow of the network; The solution output module is used to analyze and evaluate the solution output by the solver and output the human resource planning solution.

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