Project resource allocation method and allocation system based on dynamic scheduling

Abstract

The invention provides a project resource allocation method and allocation system based on dynamic scheduling, and belongs to the technical field of intelligence. The allocation method comprises the following steps: inputting project resources, a task set of a project and a demand resource set corresponding to the task set into a dynamic scheduling model of the project; according to the dynamic scheduling model, a feasible allocation scheme set of the project is determined, and each feasible allocation scheme enables available resources of project resources on any time sequence to meet demand resources corresponding to a second task, in a processing state, of the multiple tasks under the time sequence; and determining the feasible allocation scheme with the minimum completion time in the feasible allocation scheme set as a target allocation scheme. According to the method designed by the invention, different key paths can be formed through different resource allocation schemes in a resource shortage competition environment, all formed key paths are compared, and a path with earliest completion time is found out as an optimal path, so that the purposes of fully utilizing resources and shortening a project period are achieved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent technology, and in particular to a project resource allocation method and allocation system based on dynamic scheduling. Background Art

[0002] Traditional project resource allocation methods often lack solutions for changes in project paths and cycles caused by resource shortages. For example, the traditional critical path method not only presets the project execution path and cycle, but also presets the abundance of resources. Under these two premises, the invariance of the critical path is ensured, and the overall progress of the project is guaranteed by allocating resources to the task nodes on the critical path first.

[0003] However, this unfair resource competition and allocation strategy method ignores the possible congestion and delays that may occur when task nodes do not receive corresponding resources in the case of resource shortage. The delayed tasks will cause the original critical path to change and become nodes on the new critical path, greatly reducing the efficiency of the allocation plan based on the original critical path.

[0004] After long-term practice, we have found that when optimizing the allocation of project resources, it is necessary not only to establish the correlation between tasks, but also to comprehensively evaluate the progress and path changes brought about by different resource allocation methods, which often faces great difficulties. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a project resource allocation method and allocation system based on dynamic scheduling, aiming to optimize the allocation of project resources by using the dynamic scheduling method. The method can comprehensively analyze the dependency of each task node on resources, calculate the possibility of different resource allocation methods, dynamically update the critical path, and finally find the optimal solution among various changes through a suitable algorithm, thereby solving the above-mentioned problems.

[0006] In order to achieve the above-mentioned purpose, the present invention provides a project resource allocation method based on dynamic scheduling, the allocation method comprising: inputting the project resources, the task set of the project and the demand resource set corresponding to the task set into the dynamic scheduling model of the project, wherein the task set includes multiple tasks, the demand time of each task in the multiple tasks and a binary relationship matrix composed of the relationship types between any two tasks in the multiple tasks, and the demand resource set is a collection of demand resources corresponding to each task; according to the dynamic scheduling model, determining a set of feasible allocation schemes for the project, wherein each feasible allocation scheme in the set of feasible allocation schemes can make the available resources of the project resources at any time sequence meet the demand resources corresponding to the second task of the multiple tasks in the processing state at the time sequence; and determining the feasible allocation scheme with the smallest completion time in the set of feasible allocation schemes as the target allocation scheme.

[0007] Optionally, the dynamic scheduling model is used to perform the following functions: determine the available resources and the first task in an unprocessed state in a time sequence according to the project resources and the starting state matrix of the task set in the time sequence, wherein the first task in the initial time sequence is all the tasks in the task set; determine the state change behavior of the task as a decision on the task according to the available resources in the time sequence and the required resources corresponding to any first task, wherein the decision includes an active decision to change the first task to the second task and a passive decision to change the second task to a third task in a processed state; after the decision of any task, determine the state change matrix of the task set according to the binary relationship matrix as the starting state matrix of the task set before the next active decision; and make active decisions for each task in the task set in an iterative manner until the first task no longer exists in the task set.

[0008] Optionally, the passive decision includes: changing the second task to a third task in a processed state according to a required time of the second task.

[0009] Optionally, the demand resources include consumable resources and usage resources, and determining the available resources in a time sequence according to the project resources and the starting state matrix of the task set in the time sequence includes: determining the second task and the third task in the time sequence according to the starting state matrix of the task set in the time sequence; summing the consumable resources in the demand resources corresponding to the second task and the demand resources corresponding to the third task to determine the occupied resources in the time sequence; and determining the remaining resources after deducting the occupied resources from the project resources as the available resources in the time sequence.

[0010] Optionally, determining a set of feasible allocation solutions for the project based on the dynamic scheduling model includes: obtaining a decision set for making active decisions on each task in the task set based on the dynamic scheduling model; using a select-all or select-optimal method, selecting decisions from the decision set for combination to obtain a strategy set, wherein each decision in the strategy set uniquely corresponds to each task; and determining the strategy set sorted according to the occurrence sequence of each decision in the strategy set as a set of feasible allocation solutions for the project.

[0011] Optionally, the fully selected methods include a dynamic programming method; and / or the preferred methods include one or more of the following: simulated annealing algorithm, ant colony algorithm, genetic algorithm, reinforcement learning and deep learning.

[0012] Optionally, the relationship types include: start after start, start after end, end after end, and no relationship, wherein, when the relationship type between a benchmark task and another comparison task is start after start or start after end, the benchmark task is used as the predecessor point of the comparison task, and the comparison task is used as the successor point of the benchmark task.

[0013] Optionally, the binary relationship matrix is ​​determined in the following manner: based on the relationship type between any two tasks among the multiple tasks, a set of tasks without the predecessor point is determined as a starting point set; and based on the subsequent point task corresponding to any task in the starting point set, a subsequent point set for each task is determined.

[0014] Optionally, determining the feasible allocation scheme with the smallest completion time in the set of feasible allocation schemes as the target allocation scheme includes: determining the start time and the end time of each task in the task set of each feasible allocation scheme in the set of feasible allocation schemes, wherein the end time of each task is determined by summing the start time of each task and the required time of the task; subtracting the latest end time from the start time of the starting task to obtain the completion time of each feasible allocation scheme; and determining the feasible allocation scheme with the smallest completion time in the set of feasible allocation schemes as the target allocation scheme.

[0015] On the other hand, the present invention also provides a project resource allocation system based on a dynamic scheduling model, the allocation system comprising: a model determination device, used to input the project resources, the task set of the project and the demand resource set corresponding to the task set into the dynamic scheduling model of the project, wherein the task set includes multiple tasks, the demand time of each task in the multiple tasks and a binary relationship matrix composed of the relationship type between any two tasks in the multiple tasks, and the demand resource set is a set of demand resources corresponding to each task; a strategy set determination device, used to determine a set of feasible allocation schemes for the project according to the dynamic scheduling model, wherein each feasible allocation scheme in the set of feasible allocation schemes can make the available resources of the project resources at any time sequence meet the demand resources corresponding to the second task of the multiple tasks in the processing state at the time sequence; and a critical path determination device, used to determine the feasible allocation scheme with the smallest completion time in the set of feasible allocation schemes as the target allocation scheme.

[0016] Through the above technical solution, this paper proposes a project resource allocation method based on dynamic scheduling, generates a critical path in the process of resource allocation, and finally finds the optimal path that can be realized in the actual process through algorithm iteration. The beneficial effect of the present invention is that the designed method can form different critical paths through different resource allocation schemes in an environment of resource shortage and competition, compare all the formed critical paths, and find a path with the earliest completion time as the optimal path, so as to achieve the purpose of full utilization of resources and shortening the project cycle.

[0017] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings: Figure 1 is a flowchart of a project resource allocation method based on dynamic scheduling according to an embodiment of the present invention; Figure 2 is a specific flow chart of a project resource allocation method provided according to an embodiment of the present invention; Figure 3-7 is a schematic diagram of a process of executing a project task provided according to an embodiment of the present invention; Figure 8 It is a structural diagram of a project resource allocation system based on dynamic scheduling according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0020] The present invention first provides a project resource allocation method 100 based on dynamic scheduling, such as Figure 1 As shown, the allocation method 100 may include: Step S110, input the project resources, the task set of the project and the required resource set corresponding to the task set into the dynamic scheduling model of the project. The task set may include multiple tasks, the required time of each task in the multiple tasks and a binary relationship matrix composed of the relationship types between any two tasks in the multiple tasks. In addition, the required resource set is a collection of required resources corresponding to each task.

[0021] In this step, before determining the dynamic scheduling model of the project, it is necessary to first perform structural modeling based on the relevant information of the project during execution, so that the required relevant information can be collected in advance and provided to the dynamic scheduling model. Among them, structural modeling can be understood as the process of determining the constraint boundaries of various parameters, which can include the definition of elements such as task decomposition, specifying the dependencies between task nodes, and resource requirements, etc., for example, in the form of the following set: G=(K,S,M d ,B,U)

[0022] in: K=(k1,k2,...,k n ) represents the task set of the project, and n is the number of tasks in the multiple tasks.

[0023] S=(s1,s2,...,s n ) is the state set of the task.

[0024] M d is the binary relationship matrix between task nodes.

[0025] B=(b1,b2,...,b l ) is the project resource, that is, the total available resource collection.

[0026] U=(u1,u2,...,u n ) is the required resource set corresponding to the task set, that is, the total resource set required by the project.

[0027] Secondly, it is necessary to collect the project data set and establish a database around the structure of the dynamic scheduling model (used to characterize the relevant information of the project during execution). For example, it can be based on the above definition of the project ontology: G = (K, S, M d,B,U), select a database system, for example, you can choose tdsql, mysql, sqlserver, mongodb, postgresql, etc., so as to establish a database that can carry and store project-related data sets.

[0028] Then, the task data of the project is collected. Task data is the data formed after the project is decomposed through methods such as WBS (Work Breakdown Structure), generally including task names, requirements, specifications, etc. For example, the original data such as project resources, project task sets, and demand resource sets corresponding to task sets can be collected, so as to fill the data of each element and set according to the structure of the dynamic scheduling model to determine the dynamic scheduling model of the project.

[0029] Specifically, this step can be centered around the definition of the task set in the project model G: K = (k1, k2, ..., k n ), collect task-related data. At the same time, we can build a task relationship set M based on the interdependence (relationship type) between tasks. d ,in:

[0030] m ij Represents task k i With task k j The type of relationship between. Where E = (e1, e2, ..., e k ) is the relationship type, which can include: SS Start to Start, FS Finish to Start, FF Finish to Finish, and no relationship. Specifically, if the relationship type between task A and task B is SS Start to Start, it means that task B can only start after task A starts; if the relationship type between task A and task B is Start after Finish, it means that task B can only start after task A ends; if the relationship type between task A and task B is Finish after Finish, it means that task B can only end after task A ends; and no relationship means that there is no association relationship between task A and task B, that is, no matter whether task A starts or ends, task B can start or end. For example, in a construction project, there may be an SS relationship between the architect's design work (task A) and the construction team's preparatory work (task B). The construction team can only start preparatory work when the architect starts designing. However, this does not mean that the architect must complete the design before the construction team can start preparatory work. As long as the architect has started designing, the construction team can start preparatory work at the same time.

[0031] For example, in a software development project, the programming work of the development team (task A) and the testing work of the testing team (task B) may have a FF relationship. The testing work of the testing team can only be completed when the development team completes the programming work. This is because the testing team needs to complete all the testing work after the development team completes all the programming work.

[0032] In the case where the relationship type between the reference task and another comparison task is SS or FS, the reference task is used as the predecessor of the comparison task, and the comparison task is used as the successor of the reference task. That is, in the above example, the reference task is A and the comparison task is B, then task A is used as the predecessor of task B, and task B is used as the successor of task A.

[0033] Alternatively, the binary relationship matrix can be determined as follows: 1) according to the relationship type between any two tasks among the multiple tasks, determining a set of tasks without predecessor points as a starting point set; and 2) Determine the subsequent point set for each task based on the subsequent point task corresponding to any task in the starting point set.

[0034] Finally, it is necessary to collect project resources (total project resource data) and the required resource set corresponding to the task set. Among them, the total project resource data is the total number of all resources owned by the project. Resources are generally personnel with specific skills, equipment, environment space, etc. It can be based on the following set: B = (b1, b2, ..., b l ) for data collection, where b i =(r i , o i ),r i is the resource type, r i ∈R(r1,r2,...,r l ), R is all resource types, o i The number of resources available. Among them, resources can be divided into "usable" resources and "consumable" resources. The former will return to the total resource set after the task is completed and will be reflected in the available quantity, while the latter will no longer return to the total resource set after the task is completed.

[0035] The required resource set corresponding to the task set is the resource data required for the task (also called task resource dependency data). That is, the number of personnel with specific skills, the number of equipment, the number of materials, etc. required for a task. At the same time, the time required for the task is a numerical value that the present invention pays special attention to. It is processed as an independent object, not included in the resource set, and is determined during data collection. Among them, for "usage-type" resources, the time required for the task is the estimated occupancy time of the resource, and the resource will be automatically released when the task is completed. The specific definition can refer to the following formula: U = (u1, u2, ..., u n ) is the required resource set, u i =(k i , A i , w i ), w i is the demand time, A i =(a i1 , a i2 , ..., a il ) is task t i The dependent resource vector, a ij =(r j ,q i ), r j ∈R,q i For task k i The amount of resources required.

[0036] Through the above specific steps, the project resources, the task set of the project and the required resource set corresponding to the task set can be firstly collected, and then the above collected information can be input into the dynamic scheduling model of the project.

[0037] Step S120, determining a set of feasible allocation schemes for the project based on the dynamic scheduling model, wherein each feasible allocation scheme in the set of feasible allocation schemes can make the available resources of the project resources at any time sequence meet the required resources corresponding to the second task in the processing state of multiple tasks at that time sequence.

[0038] After the above data is collected and input into a dynamic scheduling model, the dynamic scheduling model can be used to perform the following functions 1)-4): 1) According to the initial state matrix of the project resources and the task set in a time sequence, the available resources and the first task in an unprocessed state in the time sequence are determined. The first task in the initial time sequence is all the tasks in the task set.

[0039] Among them, firstly, according to the task state set defined above, a first task in an unprocessed state, a second task in a processed state, and a third task in a processed state can be determined. That is, for: S = (s1, s2, ..., s n), where s i Represents task k i The status may include "0-unprocessed, 1-processing, 2-processed", etc. It can also be understood that when the project data is initially collected, its initial value is: 0-unprocessed.

[0040] As mentioned above, the required resources include consumable resources and use resources. Therefore, the step of "determining the available resources in a time sequence according to the starting state matrix of the project resources and the task set in a time sequence" may include the following steps a)-c): a) Determine the second task and the third task in the time sequence according to the initial state matrix of the task set in the time sequence; the specific determination method is as described above and will not be repeated here.

[0041] b) summing up the consumable resources in the demand resources corresponding to the second task and the demand resources corresponding to the third task to determine the occupied resources under the time sequence.

[0042] c) The remaining resources after deducting the occupied resources from the project resources are determined as the available resources under the time sequence.

[0043] Therefore, through the above steps a)-c), the available resources under the timing can be determined.

[0044] 2) According to the available resources in the time sequence and the required resources corresponding to any first task, the state change behavior of the task is determined as the decision for the task.

[0045] The decision includes active decision to change the first task to the second task and passive decision to change the second task to the third task in the processed state. The passive decision may include: changing the second task to the third task in the processed state according to the required time of the second task. That is, when the task obtains the required resources, the state can be changed from "0-unprocessed" to "1-processing". This process is called active decision; and after the required time w in this state, the state is changed to "1-processing". i After that, the status can be changed to "2-Processed", and this process is called passive decision.

[0046] Specifically, each task node K=(k1, k2, ..., k n ), and task status S = (s1, s2, ..., s n ), the task node k i Change to status Determine the decision on the task. Represents all currently available decisions, that is, the set of feasible states determined by the resource status. Its boundary condition is the sufficiency of the number of resources, that is, the amount of resources required by the current task volume must be less than or equal to the amount of available resources (corresponding to different resource types), where:

[0047] That is to say, only when there are available resources in the current time sequence can it be changed to the "1-Processing" state, and the resources will also enter the state of being consumed or occupied. After the "Processing" time reaches the time required for the task, it can be changed to the "2-Processed" state, and non-consumable resources will be released at the same time.

[0048] 3) After the decision of any task, the state change matrix of the task set is determined according to the binary relationship matrix to serve as the starting state matrix of the task set before the next active decision.

[0049] 4) Actively make decisions for each task in the task set in an iterative manner until the first task no longer exists in the task set.

[0050] Specifically, after each decision, the state change can be output according to the determined binary relationship matrix, and the obtained state matrix is ​​used as the starting matrix before the next decision, and iterative calculation is performed accordingly. This process is called the state transfer process, which can be expressed by the following state transfer equation:

[0051] Through the state transition equation, we can determine the satisfaction of the current available resources for the task and the global needs of the algorithm, and the corresponding relationship for the deterministic change of the state. When the state of any task changes, it can be determined through the binary relationship matrix M d Update current plan Z i Medium Element of

[0052] In summary, through the above four steps 1)-4), the dynamic scheduling model can be used to perform an iterative process to determine the active decision set for each task. Among them, iteration is a solution method used to approximate the optimal solution. This paper uses a dynamic programming model to exhaust all strategies, update the timeline, generate critical paths, and use the minimum completion time as a comparison indicator to find the feasible optimal critical path.

[0053] In one embodiment, step S120 may further include: Step S121, obtaining a decision set for actively making decisions for each task in the task set according to the dynamic scheduling model.

[0054] Step S122 , using a full selection or optimization method, select decisions from the decision set for combination to obtain a strategy set, wherein each decision in the strategy set uniquely corresponds to each task.

[0055] Among them, the strategy is a collection of a series of decisions. For example, starting from the i-th task node, the strategy of the j-th task node is:

[0056] A complete strategy is the situation when i=0, j=n in the above formula, and i≥0, j≤n, i≤j is a sub-strategy of the complete strategy. When a strategy is a feasible strategy, it is the decision set formed when the states corresponding to the tasks included are all "2-processed".

[0057] In addition, the method of selecting all can include a dynamic programming method, that is, a process of screening and allocating by fully combining all feasible decisions. The advantage of this method is that it is a comprehensive traversal, so the result is more accurate. However, the disadvantage is that there are a large number of invalid traversals, so it takes more computing resources, resulting in low execution efficiency. The preferred method is to find a relatively optimal solution through a set algorithm without traversing all combinations, which will improve execution efficiency. For example, the preferred method may include one or more of the following: simulated annealing algorithm, ant colony algorithm, genetic algorithm, reinforcement learning, and deep learning.

[0058] Step S123: Determine the strategy set sorted according to the occurrence sequence of each decision in the strategy set as a feasible allocation solution set for the project.

[0059] Each feasible allocation scheme in the feasible allocation scheme set may include the start time and the end time of each task in the task set, and the end time may be determined by summing the start time of each task and the required time of the task.

[0060] Step S130: determine the feasible allocation scheme with the shortest completion time in the feasible allocation scheme set as the target allocation scheme.

[0061] The essence of the algorithm involved in this article is to establish different critical paths through different allocation plans for the resources required for the task, compare all the critical paths, and find a path with the earliest completion time as the optimal path to achieve the purpose of fully utilizing resources and shortening the project cycle. In other words, it is necessary to find a planning plan with the earliest completion time, which can be expressed as follows:

[0062] Specifically, step S130 may further include: Step S131, determining the start time and end time of each task in the task set of each feasible allocation solution in the feasible allocation solution set, wherein the end time of each task is determined by summing the start time of each task and the required time of the task.

[0063] Among them, the set of all feasible allocation solutions is: Z=(Z1,Z2,...)

[0064] Where Z i =(z i1 , z i2 , ..., z in ), Represents allocation scheme Z i The task k j The final result, The task start time is the time to allocate resources and perform state transition. The task end time.

[0065] Step S132, subtract the latest end time from the start time of the start task to obtain the completion time of each feasible allocation solution. The completion time can also be called the maximum end time.

[0066] Let the set K p =(k p1 , k p2 , ..., k pv ) is the binary relationship matrix M d The calculated task k j All related predecessor tasks of , then:

[0067] thereby

[0068] Step S133: determine the feasible allocation scheme with the shortest completion time in the feasible allocation scheme set as the target allocation scheme.

[0069] Let Z * is the optimal solution, then:

[0070] That is, the plan with the smallest "maximum end time" among all allocation plans is the optimal plan.

[0071] Through the above technical solution, this paper proposes a project resource allocation method based on dynamic scheduling, generates a critical path in the process of resource allocation, and finally finds the optimal path that can be realized in the actual process through algorithm iteration. The beneficial effect of the present invention is that the designed method can form different critical paths through different resource allocation schemes in an environment of resource shortage and competition, compare all the formed critical paths, and find a path with the earliest completion time as the optimal path, so as to achieve the purpose of full utilization of resources and shortening the project cycle.

[0072] Example In order to further explain the present invention, embodiments of specific applications are provided. Figure 2 , the process is as follows: 1. Data import: The data in the database are structured according to the definition specified by the dynamic scheduling model and then imported into the dynamic scheduling model to solve the required data set.

[0073] 2. Generate a binary relationship matrix: Traverse the known set of task-to-task association relationships (relationship types), obtain the starting point set (i.e., the task set without predecessor points), and for each starting point, traverse the task-to-task association relationships to form a subsequent point set, which is written into the binary relationship matrix.

[0074] 3. Generate available decision sets: Through a set of subsequent points of a task, the available resource set is matched and calculated at the same time to generate an available decision set. When an available decision is generated and applied, for the occupied "usage" resources, after the required task time has passed, the task will be automatically completed and the released resources will be included in the available resource set.

[0075] 4. Make a choice for decision: According to the actual data and algorithm environment, use the full selection or optimal selection method to select a combination of decision-making strategies. The optimal methods include heuristic algorithms such as simulated annealing algorithm, ant colony algorithm, genetic algorithm, etc., as well as reinforcement learning, deep learning and other algorithms that compress the hypothesis space through data distribution.

[0076] 5. Strategy Generation Put the selected decision into the policy set and update the timeline of the selected decision. Record and save the information generated on the policy.

[0077] 6. Recursively generate subsequent decisions Go back to point 3, continue to select a set of subsequent points, select decisions from the available decision sets corresponding to the subsequent points, and continue to combine and generate new strategies.

[0078] 7. Calculate the critical path complete strategy When all tasks have been decided and included in the strategy, the strategy is a complete strategy. For the generated complete strategy, calculate its critical path.

[0079] 8. Iterative Generation Strategy After completing the generation and saving of a complete strategy, we return to the available decision set at the initial point to select unused decisions, generate a new strategy according to the above steps, and calculate a new critical path.

[0080] 9. Optimal solution Compare the critical paths of all strategies and select the critical path with the smallest "maximum completion time" as the optimal strategy.

[0081] In addition, in the process of applying the present invention, the implementation process is as follows: Figure 3-6 As shown, Figure 3 It is the management interface of the project group and provides overall management of all projects, including project information maintenance, resource allocation, project team allocation, risk control, etc. Figure 4 and Figure 5 Resource function definitions for personnel skills and equipment usage, respectively. Figure 6 To define the functions of the available resources for the project, resources with a certain function can meet the corresponding tasks that require the function. In addition, the calculated optimal solution is output as a Gantt chart of the project task execution diagram with a timeline, as shown in the following figure: Figure 7 shown. Figure 7 The resource dependency diagram of the project tasks is displayed. Different project tasks will show different "functional requirements". The available resources are matched by functions, so as to allocate and plan the execution of the project.

[0082] On the other hand, the present invention further provides a project resource allocation system 200 based on dynamic scheduling, which can be implemented based on the above project resource allocation method 100 based on dynamic scheduling. Figure 8 As shown, the allocation system 200 may include: a model determining device 210, which is used to input project resources, a task set of the project, and a required resource set corresponding to the task set into a dynamic scheduling model of the project, wherein the task set includes a plurality of tasks, a required time of each task in the plurality of tasks, and a binary relationship matrix composed of relationship types between any two tasks in the plurality of tasks, and the required resource set is a collection of required resources corresponding to each task; A strategy set determining means 220, for determining a set of feasible allocation schemes for a project according to a dynamic scheduling model, wherein each feasible allocation scheme in the set of feasible allocation schemes can enable the available resources of the project resources at any time sequence to meet the required resources corresponding to the second tasks in the processing state of the plurality of tasks at the time sequence; and The critical path determining means 230 is used to determine the feasible allocation scheme with the shortest completion time in the feasible allocation scheme set as the target allocation scheme.

[0083] In one embodiment, the dynamic scheduling model is used to perform the following functions: determine the available resources and the first task in an unprocessed state in a time sequence according to the project resources and the initial state matrix of the task set in the time sequence, wherein the first task in the initial time sequence is all the tasks in the task set; determine the state change behavior of the task as a decision on the task according to the available resources in the time sequence and the required resources corresponding to any first task, wherein the decision includes an active decision to change the first task to the second task and a passive decision to change the second task to a third task in a processed state; after the decision of any task, determine the state change matrix of the task set according to the binary relationship matrix as the initial state matrix of the task set before the next active decision; and make active decisions for each task in the task set in an iterative manner until the first task no longer exists in the task set.

[0084] In one embodiment, the passive decision includes: changing the second task to a third task in a processed state according to the required time of the second task.

[0085] In one embodiment, the demand resources include consumable resources and usage resources, and determining the available resources in a time sequence based on the project resources and the starting state matrix of the task set in the time sequence includes: determining the second task and the third task in the time sequence based on the starting state matrix of the task set in the time sequence; summing the consumable resources in the demand resources corresponding to the second task and the demand resources corresponding to the third task to determine the occupied resources in the time sequence; and determining the remaining resources obtained by subtracting the occupied resources from the project resources as the available resources in the time sequence.

[0086] In one embodiment, the strategy set determination device 220 is specifically used to perform the following functions: according to the dynamic scheduling model, obtain a decision set for making the active decision for each task in the task set; use a full selection or optimization method to select decisions from the decision set for combination to obtain a strategy set, wherein each decision in the strategy set uniquely corresponds to each task; and determine the strategy set sorted according to the occurrence sequence of each decision in the strategy set as a feasible allocation plan set for the project.

[0087] In one embodiment, the fully selected methods include a dynamic programming method; and / or the preferred methods include one or more of the following: simulated annealing algorithm, ant colony algorithm, genetic algorithm, reinforcement learning and deep learning.

[0088] In one embodiment, the relationship types include: start after start, start after end, end after end, and no relationship, wherein, when the relationship type between a benchmark task and another comparison task is start after start or start after end, the benchmark task is used as the predecessor point of the comparison task, and the comparison task is used as the successor point of the benchmark task.

[0089] In one embodiment, the binary relationship matrix is ​​determined in the following manner: based on the relationship type between any two tasks among the multiple tasks, a set of tasks without the predecessor point is determined as a starting point set; and based on the subsequent point task corresponding to any task in the starting point set, a subsequent point set of each task is determined.

[0090] In one embodiment, the critical path determination device 230 is specifically used to perform the following functions: determine the start time and end time of each task in the task set of each feasible allocation scheme in the feasible allocation scheme set, wherein the end time of each task is determined by summing the start time of each task and the required time of the task; subtracting the latest end time from the start time of the starting task to obtain the completion time of each feasible allocation scheme; and determining the feasible allocation scheme with the smallest completion time in the feasible allocation scheme set as the target allocation scheme.

[0091] In summary, through the above technical solutions, this paper proposes a project resource allocation method based on dynamic scheduling, generates a critical path in the process of resource allocation, and finally finds the optimal path that can be realized in the actual process through algorithm iteration. The beneficial effect of the present invention is that the designed method can form different critical paths through different resource allocation schemes in an environment of resource shortage and competition, compare all the formed critical paths, and find a path with the earliest completion time as the optimal path, so as to achieve the purpose of full utilization of resources and shortening the project cycle.

[0092] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0093] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A project resource allocation method based on a dynamic scheduling model, characterized in that: The allocation method includes: Input the project resources, the task set of the project and the required resource set corresponding to the task set into the dynamic scheduling model of the project, wherein the task set includes multiple tasks, the required time of each task in the multiple tasks and a binary relationship matrix composed of the relationship types between any two tasks in the multiple tasks, and the required resource set is a collection of required resources corresponding to each task; Determine a set of feasible allocation schemes for the project according to the dynamic scheduling model, wherein each feasible allocation scheme in the set of feasible allocation schemes can enable the available resources of the project resources at any time sequence to meet the required resources corresponding to the second task in the processing state of the multiple tasks at the time sequence; and The feasible allocation scheme with the shortest completion time in the set of feasible allocation schemes is determined as the target allocation scheme.

2. The distribution method according to claim 1, characterized in that: The dynamic scheduling model is used to perform the following functions: according to the project resources and the initial state matrix of the task set in a time sequence, determine the available resources and the first task in an unprocessed state in the time sequence, wherein the first task in the initial time sequence is all the tasks in the task set; According to the available resources in the time sequence and the required resources corresponding to any first task, determining the state change behavior of the task as a decision on the task, wherein the decision includes an active decision to change the first task to the second task and a passive decision to change the second task to a third task in a processed state; After any task is decided, a state change matrix of the task set is determined according to the binary relationship matrix to serve as a starting state matrix of the task set before the next active decision; and Active decision making is performed on each task in the task set in an iterative manner until the first task no longer exists in the task set.

3. The distribution method according to claim 2, characterized in that: The passive decision includes: changing the second task to a third task in a processed state according to the required time of the second task.

4. The distribution method according to claim 2, characterized in that: The required resources include consumable resources and use resources. The determining of available resources in a time sequence according to the project resources and the initial state matrix of the task set in a time sequence includes: Determine the second task and the third task in the time sequence according to the starting state matrix of the task set in the time sequence; summing up the consumable resources in the required resources corresponding to the second task and the required resources corresponding to the third task to determine the occupied resources under the time sequence; and The remaining resources obtained by subtracting the occupied resources from the project resources are determined as the available resources at the time sequence.

5. The distribution method according to claim 2, characterized in that: Determining a set of feasible allocation schemes for the project according to the dynamic scheduling model includes: According to the dynamic scheduling model, obtaining a decision set for making the active decision on each task in the task set; Using a full selection or optimization method, selecting decisions from the decision set for combination to obtain a strategy set, wherein each decision in the strategy set uniquely corresponds to each task; and The strategy set sorted according to the occurrence sequence of each decision in the strategy set is determined as a feasible allocation solution set for the project.

6. The distribution method according to claim 5, characterized in that: The method of selecting all includes a dynamic programming method; and / or The preferred methods include one or more of the following: simulated annealing algorithm, ant colony algorithm, genetic algorithm, reinforcement learning and deep learning.

7. The distribution method according to claim 1, characterized in that: The relationship types include: start after start, start after end, end after end, and no relationship. Wherein, when the relationship type between the reference task and another comparison task is start after start or start after end, the reference task is used as the predecessor of the comparison task, and the comparison task is used as the successor of the reference task.

8. The distribution method according to claim 7, characterized in that: The binary relationship matrix is ​​determined by: according to the relationship type between any two tasks among the plurality of tasks, determining a set of tasks without the predecessor point as a starting point set; as well as According to the subsequent point task corresponding to any task in the starting point set, a subsequent point set of each task is determined.

9. The distribution method according to claim 1, characterized in that: The step of determining the feasible allocation scheme with the shortest completion time in the set of feasible allocation schemes as the target allocation scheme comprises: Determine the start time and end time of each task in the task set of each feasible allocation solution in the feasible allocation solution set, wherein the end time of each task is determined by summing the start time of each task and the required time of the task; Subtract the latest finish time from the start time of the start task to obtain the completion time of each feasible allocation solution; and The feasible allocation scheme with the shortest completion time in the set of feasible allocation schemes is determined as the target allocation scheme.

10. A project resource allocation system based on a dynamic scheduling model, characterized in that: The allocation system comprises: a model determination device, which is used to input the project resources, the task set of the project and the required resource set corresponding to the task set into the dynamic scheduling model of the project, wherein the task set comprises a plurality of tasks, the required time of each task in the plurality of tasks and a binary relationship matrix composed of the relationship types between any two tasks in the plurality of tasks, and the required resource set is a collection of required resources corresponding to each task; a strategy set determining device, configured to determine a set of feasible allocation schemes for the project according to the dynamic scheduling model, wherein each feasible allocation scheme in the set of feasible allocation schemes can enable the available resources of the project resources at any time sequence to meet the required resources corresponding to the second task in the processing state of the multiple tasks at the time sequence; and The critical path determination device is used to determine the feasible allocation scheme with the shortest completion time in the set of feasible allocation schemes as the target allocation scheme.

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