Project resource scheduling method and device, equipment and storage medium

Abstract

The application discloses a project resource scheduling method, device and equipment and a storage medium, and relates to the technical field of project resource scheduling. The project resource scheduling method is applied to subcontract projects of service providers, and comprises the following steps: obtaining pre-input resource scheduling data; wherein the resource scheduling data comprises service provider parameters and task project parameters; constructing a target team sequence according to the service provider parameters and preset constraint condition data; performing team allocation processing on the target team sequence according to the task project parameters to obtain an initial task scheduling scheme; performing fitness calculation according to the initial task scheduling scheme to obtain a scheme fitness; and performing iterative updating on the initial task scheduling scheme according to the scheme fitness until iterative state data reaches preset iteration parameters, so that a target task scheduling scheme is obtained. The application can replace manual allocation of subcontract projects, and improves the allocation efficiency and resource utilization rate.

Description

Technical Field

[0001] This invention relates to the field of subcontracting project technology, and in particular to a project resource scheduling method, apparatus, equipment and storage medium. Background Technology

[0002] Currently, resource allocation for subcontracted projects still relies on manual allocation. This method can only rely on past experience to find relatively better allocation schemes in terms of cost or schedule, but it cannot find the optimal scheme for the whole project. This will result in a loss of efficiency and a waste of resources to some extent. Summary of the Invention

[0003] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention proposes a project resource scheduling method that can replace manual allocation of subcontracted projects, thereby improving allocation efficiency and resource utilization.

[0004] The present invention also proposes a resource scheduling device.

[0005] The present invention also proposes a resource scheduling device.

[0006] The present invention also proposes a computer-readable storage medium.

[0007] In a first aspect, one embodiment of the present invention provides a project resource scheduling method applied to a subcontracted project of a service provider, the project resource scheduling method comprising:

[0008] Obtain pre-input resource scheduling data; wherein, the resource scheduling data includes: service provider parameters and task item parameters;

[0009] A target team sequence is constructed based on the service provider parameters and preset constraint data;

[0010] Based on the task project parameters, the target team sequence is assigned a team to obtain an initial task scheduling scheme.

[0011] The fitness of the scheme is obtained by calculating the fitness of the scheme based on the initial task scheduling scheme;

[0012] The initial task scheduling scheme is iteratively updated based on the scheme's fitness until the iterative state data reaches the preset iterative parameters, thus obtaining the target task scheduling scheme.

[0013] The project resource scheduling method of this invention has at least the following beneficial effects: It acquires pre-input resource scheduling data, including service provider parameters and task project parameters; selects several teams that meet the conditions from the service provider parameters based on preset constraint data; constructs a sequence of these teams to obtain a target team sequence; performs team allocation processing on the target team sequence according to the task project parameters to assign each task to the corresponding team, obtaining an initial task scheduling scheme; calculates the fitness of each team in completing the task according to the initial task scheduling scheme, obtaining the scheme fitness; iteratively updates the initial task scheduling scheme based on the scheme fitness until the iteration state data reaches preset iteration parameters, obtaining the target task scheduling scheme. By acquiring input resource scheduling data, constructing a target team sequence based on service provider parameters and constraint data, allocating tasks to the target team sequence according to task project parameters to obtain an initial task scheduling scheme, calculating the scheme fitness based on the initial task scheduling scheme, and optimizing the initial task scheduling scheme based on the scheme fitness, an optimized target task scheduling scheme is obtained. This method can replace manual allocation of subcontracted projects, improving allocation efficiency and resource utilization.

[0014] According to other embodiments of the project resource scheduling method of the present invention, the step of constructing a candidate team sequence based on the service provider parameters and preset constraint data includes:

[0015] The service provider parameters and the constraint data are input into a preset genetic law calculation model; wherein, the genetic law calculation model includes: an initialization layer, an individual evaluation layer, an individual selection layer, a crossover operation layer, and a mutation operation layer;

[0016] An initial team sequence is generated using the initialization layer, the service provider parameters, and the constraints.

[0017] The team fitness is obtained by calculating the fitness using the individual evaluation layer and the service provider parameters.

[0018] Candidate team sequences are selected from the initial team sequence through the individual selection layer and the team fitness;

[0019] The candidate team sequences are subjected to sequence crossover operations using the crossover operation layer and preset crossover parameters to obtain the crossover team sequences.

[0020] The target team sequence is obtained by mutating the cross-team sequence using the mutation operation layer and preset mutation parameters.

[0021] According to other embodiments of the present invention, the project resource scheduling method, wherein the step of performing team allocation processing on the target team sequence based on the task project parameters to obtain an initial task scheduling scheme includes:

[0022] The task parameters and the target team sequence are input into a preset greedy rule calculation model; wherein, the greedy rule calculation model includes: a project evaluation layer, a task sorting layer, and a team matching layer;

[0023] The project evaluation layer performs project evaluation calculations on the task project parameters to obtain project evaluation values;

[0024] The projects are sorted in descending order using the task sorting layer and the project evaluation value to obtain the target task sequence.

[0025] The target team sequence and the target task sequence are matched by the team matching layer to obtain the initial task scheduling scheme.

[0026] According to other embodiments of the project resource scheduling method of the present invention, the step of performing team matching between the target team sequence and the target task sequence through the team matching layer to obtain the initial task scheduling scheme includes:

[0027] The service cost of obtaining the target team sequence is obtained through the team matching layer;

[0028] The target team sequence is sorted in descending order using the team matching layer and the service cost to obtain a sorted team sequence.

[0029] The initial task scheduling scheme is obtained by matching the sorted team sequence and the target task sequence through the team matching layer.

[0030] According to other embodiments of the project resource scheduling method of the present invention, the service provider parameters include service task type and service region, the task project parameters include reference task type and task region, and the step of performing team matching on the sorted team sequence and the target task sequence through the team matching layer to obtain the initial task scheduling scheme includes:

[0031] Task type matching is performed using the team matching layer, the service task type, and the reference task type to obtain the task type matching relationship;

[0032] Regional matching relationships are obtained by performing regional matching through the team matching layer, the service area, and the task area.

[0033] The initial task scheduling scheme is obtained by matching the sorted team sequence and the target task sequence through the team matching layer, the task type matching relationship and the region matching relationship.

[0034] According to other embodiments of the project resource scheduling method of the present invention, the step of matching the sorted team sequence and the target task sequence through the team matching layer, the task type matching relationship and the region matching relationship to obtain the initial task scheduling scheme includes:

[0035] Monthly share data is calculated using the team matching layer, the task type matching relationship, and the region matching relationship;

[0036] If the monthly share data is less than the preset monthly share constraint threshold, the sorted team sequence is rearranged through the team matching layer to obtain a rearranged team sequence;

[0037] The initial task scheduling scheme is obtained by matching the rearranged team sequence and the target task sequence through the team matching layer.

[0038] According to other embodiments of the present invention, after iteratively updating the initial task scheduling scheme based on the scheme fitness until the iterative state data reaches a preset iterative parameter to obtain the target task scheduling scheme, the project resource scheduling method further includes:

[0039] Obtain the task quantity data corresponding to the target team sequence;

[0040] The priority of the target team sequence is adjusted based on the task quantity data to obtain the team priority;

[0041] The target team sequence is sorted in descending order according to the team priority to obtain the sorted team sequence;

[0042] The target task scheduling scheme is updated based on the sorted team sequence.

[0043] Secondly, one embodiment of the present invention provides a resource scheduling device applied to a service provider's subcontracted project, the resource scheduling device comprising:

[0044] An initial data acquisition module is used to acquire pre-input resource scheduling data; wherein, the resource scheduling data includes: service provider parameters and task item parameters;

[0045] The team sequence construction module is used to construct a target team sequence based on the service provider parameters and preset constraint data;

[0046] The team matching module is used to perform team allocation processing on the target team sequence according to the task project parameters to obtain an initial task scheduling scheme.

[0047] The fitness calculation module is used to calculate the fitness of the scheme based on the initial task scheduling scheme;

[0048] The task scheduling optimization module is used to iteratively update the initial task scheduling scheme according to the scheme fitness until the iteration state data reaches the preset iteration parameters to obtain the target task scheduling scheme.

[0049] The resource scheduling device of this invention has at least the following beneficial effects: An initial data acquisition module acquires pre-input resource scheduling data, including service provider parameters and task item parameters. A team sequence construction module selects several teams that meet the conditions from the service provider parameters based on preset constraint data, and constructs a sequence of these teams to obtain a target team sequence. A team matching module performs team allocation processing on the target team sequence according to the task item parameters to assign each task to the corresponding team, obtaining an initial task scheduling scheme. A fitness calculation module calculates the fitness of each team in completing the task according to the initial task scheduling scheme, obtaining the scheme fitness. A task scheduling optimization module iteratively updates the initial task scheduling scheme according to the scheme fitness until the iteration state data reaches preset iteration parameters, obtaining the target task scheduling scheme. By acquiring input resource scheduling data, constructing a target team sequence based on service provider parameters and constraint data, allocating tasks to the target team sequence according to task item parameters to obtain an initial task scheduling scheme, calculating the scheme fitness based on the initial task scheduling scheme, and optimizing the initial task scheduling scheme based on the scheme fitness, an optimized target task scheduling scheme is obtained. This can replace manual allocation of subcontracted projects, improving allocation efficiency and resource utilization.

[0050] Thirdly, one embodiment of the present invention provides a resource scheduling device, comprising:

[0051] At least one processor, and,

[0052] A memory communicatively connected to the at least one processor; wherein,

[0053] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the project resource scheduling method as described in the first aspect.

[0054] Fourthly, one embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the project resource scheduling method as described in the first aspect.

[0055] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the description and the accompanying drawings. Attached Figure Description

[0056] Figure 1 This is a schematic flowchart of a specific embodiment of the project resource scheduling method in this invention.

[0057] Figure 2 yes Figure 1 A schematic flowchart of a specific embodiment of step S102;

[0058] Figure 3 yes Figure 1 A schematic diagram of a specific embodiment of step S103;

[0059] Figure 4 yes Figure 3 A schematic flowchart of a specific embodiment of step S304;

[0060] Figure 5 yes Figure 4 A schematic flowchart of a specific embodiment of step S403;

[0061] Figure 6 yes Figure 5 A schematic flowchart of a specific embodiment of step S503;

[0062] Figure 7 This is a schematic flowchart of another specific embodiment of the project resource scheduling method in this invention;

[0063] Figure 8 This is a module block diagram of a specific embodiment of the resource scheduling device in this invention;

[0064] Figure 9 This is a schematic flowchart of another specific embodiment of the project resource scheduling method in this invention;

[0065] Figure 10 This is a schematic flowchart of another specific embodiment of the project resource scheduling method in this invention.

[0066] Explanation of reference numerals in the attached figures:

[0067] Initial data acquisition module 801, team sequence construction module 802, team matching module 803, fitness calculation module 804, task scheduling optimization module 805. Detailed Implementation

[0068] The following will describe the concept and technical effects of the present invention clearly and completely with reference to embodiments, so as to fully understand the purpose, features and effects of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are all within the scope of protection of the present invention.

[0069] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0070] It should be noted that although the system diagram shows functional modules and the flowchart shows the logical order, in some cases, the steps shown or described may be executed in a different order than the module division in the system or the order in the flowchart.

[0071] In the description of this invention, unless otherwise explicitly defined, terms such as "set up," "install," and "connect" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0072] In the description of the embodiments of the present invention, the term "several" means one or more, and the term "multiple" means two or more. The terms "greater than," "less than," and "exceeding" should be understood as excluding the stated number, while the terms "above," "below," and "within" should be understood as including the stated number. The terms "first" and "second" should be understood as distinguishing technical features, and not as indicating or implying relative importance, the number of indicated technical features, or the order of the indicated technical features.

[0073] The parent company provides numerous projects through subcontracting. These projects may be homogeneous or of different types. Multiple service providers exist in the market, each with its own resource teams. These resource teams have their own areas of expertise, resulting in varying cost and timelines when handling different tasks within a project. Therefore, effectively matching the resource teams under the service providers with the tasks within the projects, and presenting a complete project completion plan in the form of a timetable or task schedule, becomes the subcontracted project resource scheduling problem studied in this invention.

[0074] Currently, existing resource scheduling technologies for subcontracting projects have the following drawbacks:

[0075] Resource allocation for subcontracted projects still relies on manual allocation. This method can only rely on past experience to find relatively better allocation schemes in terms of cost or schedule, but it cannot find the optimal scheme for the whole project. This will result in a loss of efficiency and a waste of resources to some extent.

[0076] Resource scheduling for subcontracting projects differs from parts-machine matching within a factory. Subcontracting project resource scheduling has some unique requirements. While some existing technologies have been designed with reference to similar fields, they still lack specific considerations for subcontracting operations. The unique requirements and constraints inherent in subcontracting operations are rarely seen in other fields. The lack of relevant research and technology makes it difficult for existing technologies to generate high-quality allocation solutions for subcontracting project resource scheduling.

[0077] Most existing technologies and algorithms perform well in resource scheduling for small-scale subcontracting projects, but they struggle to balance efficiency and effectiveness when faced with large-scale problems, resulting in poor algorithm results or excessively long algorithm execution times.

[0078] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention proposes a project resource scheduling method that can replace manual allocation of subcontracted projects, thereby improving allocation efficiency and resource utilization.

[0079] Please refer to Figure 1 , Figure 1 A flowchart illustrating a project resource scheduling method according to an embodiment of the present invention is shown. In some embodiments, the method is applied to subcontracted projects of service providers, and specifically includes, but is not limited to, steps S101 to S105.

[0080] Step S101: Obtain pre-input resource scheduling data; wherein, the resource scheduling data includes service provider parameters and task item parameters;

[0081] Step S102: Construct a target team sequence based on service provider parameters and preset constraint data;

[0082] Step S103: Perform team allocation processing on the target team sequence according to the task project parameters to obtain the initial task scheduling scheme;

[0083] Step S104: Calculate the fitness of the initial task scheduling scheme to obtain the scheme fitness.

[0084] Step S105: Iteratively update the initial task scheduling scheme according to the scheme fitness until the iteration state data reaches the preset iteration parameters to obtain the target task scheduling scheme.

[0085] In steps S101 to S105 of this embodiment, pre-input resource scheduling data is acquired. This data includes service provider parameters and task item parameters. Several teams meeting the conditions are selected from the service provider parameters based on preset constraint data, and these teams are sequenced to obtain a target team sequence. The target team sequence is then assigned tasks to corresponding teams based on the task item parameters, resulting in an initial task scheduling scheme. The fitness of each team in completing tasks is calculated based on the initial task scheduling scheme, yielding the scheme fitness. The initial task scheduling scheme is iteratively updated based on the scheme fitness until the iteration state data reaches preset iteration parameters, resulting in the target task scheduling scheme. By acquiring the input resource scheduling data, constructing the target team sequence based on service provider parameters and constraint data, assigning tasks to the target team sequence based on task item parameters, obtaining the initial task scheduling scheme, calculating the scheme fitness based on the initial task scheduling scheme, and optimizing the initial task scheduling scheme based on the scheme fitness, an optimized target task scheduling scheme is obtained. This can replace manual allocation of subcontracted projects, improving allocation efficiency and resource utilization.

[0086] In step S101 of some embodiments, the pre-input resource scheduling data is divided into service provider aspect and project aspect. The resource scheduling data includes service provider parameters and task / project parameters. Service provider parameters include the team's region, number of teams, types of tasks that the team can complete, and the time and cost required for the team to complete the task. Task / project parameters include the project's region, number of projects, project priority, constituent tasks of the project, and task order of the project.

[0087] Please refer to Figure 2 , Figure 2 A flowchart illustrating the project resource scheduling method in an embodiment of the present invention is shown. In some embodiments, constructing a candidate team sequence based on service provider parameters and preset constraint data specifically includes, but is not limited to, steps S201 to S206.

[0088] Step S201: Input the service provider parameters and constraint data into the preset genetic law calculation model; wherein, the genetic law calculation model includes: initialization layer, individual evaluation layer, individual selection layer, crossover operation layer and mutation operation layer;

[0089] Step S202: Generate an initial team sequence using initialization layer, service provider parameters, and constraint data;

[0090] Step S203: Fitness is calculated using individual evaluation layers and service provider parameters to obtain team fitness.

[0091] Step S204: Select candidate team sequences from the initial team sequence through individual selection layer and team fitness;

[0092] Step S205: Perform sequence crossover operation on the candidate team sequence through the crossover operation layer and preset crossover parameters to obtain the crossover team sequence;

[0093] Step S206: The cross-team sequence is mutated using a mutation operation layer and preset mutation parameters to obtain the target team sequence.

[0094] In steps S201 to S206 of this embodiment, service provider parameters and constraint data are input into a preset genetic law calculation model. Service provider parameters are input into an initialization layer, which filters out team sequences that meet the constraints based on the constraint data. The teams are then sequenced according to the service provider parameters to obtain an initial team sequence. Service provider parameters are input into an individual evaluation layer, which calculates the fitness of each team based on the service provider parameters. Team fitness and constraint data are input into an individual selection layer, which filters out superior team sequences from the initial team sequence based on the team fitness to obtain candidate team sequences. Candidate team sequences are input into a crossover operation layer, which randomly selects two candidate team sequences and performs sequence crossover according to preset crossover parameters to obtain a crossover team sequence. The crossover team sequence is then input into a mutation operation layer, which performs mutation processing on each crossover team sequence according to preset mutation parameters to obtain the target team sequence. By inputting service provider parameters and constraint data into the genetic law calculation model, the genetic law calculation model generates an initial team sequence based on the service provider parameters and constraint data, calculates team fitness based on the service provider parameters, selects candidate team sequences based on team fitness, performs crossover processing on the candidate team sequences based on crossover parameters, and performs mutation processing based on mutation parameters to obtain the target team sequence. It can select the optimal team sequence based on service provider parameters and constraint data.

[0095] In step S202 of some embodiments, teams that meet the conditions are selected based on constraint data, and a sequence is constructed for the teams that meet the conditions based on the teams' regions and the tasks they can complete, to obtain an initial team sequence. The constraint data includes:

[0096] Tasks in different regions are coupled in time; tasks in one region cannot be executed simultaneously, and teams cannot execute two tasks at the same time.

[0097] Each service provider needs to satisfy the share allocation constraint when executing a task in a certain region, that is, there are upper and lower bounds on the total number of tasks to be executed.

[0098] All tasks in all regions must be completed by the specified date, meaning the completion time for all tasks in all regions must be less than or equal to the deadline.

[0099] The service provider's team can only perform tasks in designated areas.

[0100] The team should complete tasks in the higher priority areas first, meaning the start time of tasks in higher priority areas should be less than or equal to the start time of tasks in lower priority areas.

[0101] Suppose that two adjacent tasks in the same area require a certain waiting time, which is independent of the queue and is a given parameter.

[0102] Each team can only perform one task at a time. For example, it takes at least one day to transfer from completing one task to starting another.

[0103] There are requirements for the number of tasks to be delivered within each time period, such as the target number of tasks to be delivered monthly and quarterly.

[0104] The service provider's teams have a limited monthly capacity, meaning there is a cap on the number of a certain type of task each team can perform per month.

[0105] There is a limit to the number of teams that a service provider can offer each month; that is, the number of teams that each service provider can offer each month must meet certain constraints.

[0106] Some service providers can do different tasks, and some teams can also do different tasks.

[0107] Different regions have different attributes, meaning that the types of tasks that constitute a region are different.

[0108] In step S203 of some embodiments, the total cost of the team is calculated by multiplying the time and cost required for the team to complete the task, and the total cost of the team is set as the fitness of the team to obtain the team fitness.

[0109] In step S204 of some embodiments, the service provider selects a candidate team sequence from the superior team sequence based on team fitness and the number of teams.

[0110] In step S205 of some embodiments, the crossover parameter ranges from 1 to 5, with a precision of 1, and a default initial value of 3. The crossover parameter can be a fixed exchange segment length or a random exchange segment length, used to determine the position for the crossover operation of the candidate team sequences. For example, the first candidate team sequence is [1,2,3,4,5,6], and the second candidate team sequence is [6,5,4,3,2,1]. The values ​​in the candidate team sequences include the number of teams specifically assigned by service provider A to execute tasks 1, 2, and 3, and the number of teams specifically assigned by service provider B to execute tasks 1, 2, and 3. When the first and second candidate team sequences are crossovered (assuming the middle two values ​​are crossovered), the result is that the first candidate team sequence is [1,2,4,3,5,6] and the second candidate team sequence is [6,5,3,4,2,1], meaning that the number of teams assigned by service provider A to execute task 3 and the number of teams assigned by service provider B to execute task 1 in the two candidate team sequences are exchanged. In this case, whether it is a single value swap or a multiple value swap, it is necessary to re-examine whether the candidate team sequence still meets the constraints after the swap.

[0111] In step S206 of some embodiments, the probability of the mutation parameter is 0-0.3, the probability precision is 0.01, and the default initial value is 0.1. When the value of the mutation parameter is a random number between 0 and 1, a determination is made on whether to perform a mutation operation on each team. When the value of the mutation parameter is a random number less than 0.1, a value in the selected valid team sequence is randomly reselected.

[0112] Please refer to Figure 3 , Figure 3 A flowchart illustrating the project resource scheduling method in an embodiment of the present invention is shown. In some embodiments, the initial task scheduling scheme is obtained by allocating teams to the target team sequence according to task project parameters, specifically including but not limited to steps S301 to S304.

[0113] Step S301: Input the task project parameters and target team sequence into the preset greedy rule calculation model; wherein, the greedy rule calculation model includes: project evaluation layer, task sorting layer and team matching layer;

[0114] Step S302: The project evaluation layer performs project evaluation calculations on the task project parameters to obtain the project evaluation value;

[0115] Step S303: Sort the projects in descending order through the task sorting layer and project evaluation value to obtain the target task sequence;

[0116] Step S304: The target team sequence and the target task sequence are matched by the team matching layer to obtain the initial task scheduling scheme.

[0117] In steps S301 to S304 of this embodiment, task project parameters and target team sequences are input into a preset greedy algorithm calculation model. Task project parameters are input into a project evaluation layer, which evaluates and calculates the priority of projects based on their priority and task order, obtaining project evaluation values. These evaluation values ​​are then input into a task sorting layer, which sorts the projects in descending order of priority based on the evaluation values, obtaining a target task sequence. Finally, the target task sequence is input into a team matching layer, which matches the target team sequence with the target task sequence to obtain an initial task scheduling scheme. By inputting task project parameters and target team sequences into a preset greedy algorithm calculation model, performing project evaluation calculations based on task project parameters to obtain project evaluation values, sorting projects in descending order based on project evaluation values ​​to obtain a target task sequence, and matching teams and tasks based on the target team sequence with the target task sequence to obtain an initial task scheduling scheme, this method can replace manual allocation of subcontracted projects, improving allocation efficiency and resource utilization.

[0118] In step S302 of some embodiments, a project evaluation calculation is performed based on the project's priority, the task order of the project, and the minimum start time of the project to obtain a project evaluation value. The project evaluation value is used to determine the final priority of the project.

[0119] Please refer to Figure 4 , Figure 4 The diagram illustrates a flowchart of a project resource scheduling method according to an embodiment of the present invention. In some embodiments, the team matching layer performs team matching on the target team sequence and the target task sequence to obtain an initial task scheduling scheme, specifically including but not limited to steps S401 to S403.

[0120] Step S401: Obtain the service cost of the target team sequence through the team matching layer;

[0121] Step S402: Sort the target team sequence in descending order by team matching layer and service cost to obtain the sorted team sequence;

[0122] Step S403: The sorted team sequence and the target task sequence are matched by the team matching layer to obtain the initial task scheduling scheme.

[0123] In steps S401 to S403 of this embodiment, the service cost for the target team sequence to complete the task is obtained through the team matching layer. The service cost is calculated from the time and cost required for the target team sequence to complete the task. The team matching layer sorts the target team sequence in descending order according to the service cost to obtain a sorted team sequence. Based on the ranking of the sorted team sequence and the ranking of the target task sequence, the project is assigned to the team from top to bottom to obtain the initial task scheduling scheme.

[0124] Please refer to Figure 5 , Figure 5 A flowchart illustrating the project resource scheduling method in an embodiment of the present invention is shown. In some embodiments, the service provider parameters include service task type and service area, and the task project parameters include reference task type and task area. The initial task scheduling scheme is obtained by matching the sorted team sequence and the target task sequence through a team matching layer, specifically including but not limited to steps S501 to S503.

[0125] Step S501: Perform task type matching through team matching layer, service task type and reference task type to obtain task type matching relationship;

[0126] Step S502: Perform regional matching through team matching layer, service area and task area to obtain regional matching relationship;

[0127] Step S503: Match the sorted team sequence and the target task sequence through team matching layer, task type matching relationship and region matching relationship to obtain the initial task scheduling scheme.

[0128] In steps S501 to S503 of this embodiment, the service task type of the team and the reference task type of the task are matched by the team matching layer to obtain a task type matching relationship. The service area of ​​the team and the task area of ​​the task are matched by the area matching layer to obtain an area matching relationship. If the task type matching relationship indicates that the service task type and the reference task type are the same task type, and the area matching relationship indicates that the service area and the task area are the same task area, then the project is assigned to the team from top to bottom according to the ranking of the sorted team sequence and the ranking of the target task sequence to obtain the initial task scheduling scheme.

[0129] In step S501 of some embodiments, the service task type is a task type that the team can complete, and the reference task type is a type of component task of the project.

[0130] In step S502 of some embodiments, the service area is the area of ​​the team, and the task area is the area of ​​the project.

[0131] Please refer to Figure 6 , Figure 6 A flowchart illustrating the project resource scheduling method in an embodiment of the present invention is shown. In some embodiments, the sorted team sequence and the target task sequence are matched through a team matching layer, a task type matching relationship, and a region matching relationship to obtain an initial task scheduling scheme, specifically including but not limited to steps S601 to S603.

[0132] Step S601: Calculate monthly share data through team matching layer, task type matching relationship and regional matching relationship;

[0133] Step S602: If the monthly share data is less than the preset monthly share constraint threshold, the sorted team sequence is rearranged through the team matching layer to obtain the rearranged team sequence.

[0134] Step S603: The initial task scheduling scheme is obtained by matching the rearranged team sequence and the target task sequence through the team matching layer.

[0135] In steps S601 to S603 of this embodiment, task data is allocated to each team according to the task type matching relationship and the region matching relationship, and the monthly share data is calculated based on the tasks completed by the team in the current month. If the monthly share data is less than the preset monthly share constraint threshold, the team sequence that does not meet the monthly share constraint threshold in the sorted team sequence is rearranged to obtain the rearranged team sequence. Then, according to the ranking of the rearranged team sequence and the ranking of the target task sequence, the project is assigned to the team from top to bottom to obtain the initial task scheduling scheme.

[0136] In step S105 of some embodiments, the iteration state data is the iteration time, the number of iterations, or the iteration convergence parameter. The iteration parameter is a pre-set upper limit for iteration time, a pre-set upper limit for the number of iterations, or a convergence condition.

[0137] Please refer to Figure 7 , Figure 7 A flowchart illustrating the project resource scheduling method in an embodiment of the present invention is shown. In some embodiments, after iteratively updating the initial task scheduling scheme according to the scheme fitness until the iterative state data reaches the preset iterative parameters to obtain the target task scheduling scheme, the project resource scheduling method further includes, but is not limited to, steps S701 to S704.

[0138] Step S701: Obtain the task quantity data corresponding to the target team sequence;

[0139] Step S702: Adjust the priority of the target team sequence based on the task quantity data to obtain the team priority;

[0140] Step S703: Sort the target team sequence in descending order according to team priority to obtain the sorted team sequence;

[0141] Step S704: Update the target task scheduling scheme according to the sorted team sequence.

[0142] In steps S701 to S704 of this embodiment, task quantity data corresponding to the target team sequence is obtained from the initial task scheduling scheme. This task quantity data indicates the number of tasks completed by the target team sequence in the current month. If the number of completed tasks is low, the priority is lowered; if the number of completed tasks is high, the priority is increased, thus obtaining the team priority. The target team sequence is then re-sorted in descending order according to the team priority to obtain a sorted team sequence. The target task scheduling scheme is then updated based on the sorted team sequence.

[0143] It should be noted that if a service provider is assigned too few tasks or too low a share, the system will randomly determine whether to swap the position of its team in the available team list with that of a team that is ranked higher in the list when sorting the teams.

[0144] Please refer to Figure 9 , Figure 9A flowchart illustrating the project resource scheduling method in an embodiment of the present invention is shown. In some embodiments, it can be understood that: First, a genetic algorithm generates multiple effective team sequences under constraints, i.e., the number of different types of resource teams provided by different service providers. The type of resource team in the team sequence refers to the type of task that the resource team is specifically assigned to within the algorithm framework. These sequences are used as the initial population of the genetic algorithm. Each individual in the initial population, i.e., each effective team sequence, must satisfy the constraints during initialization and cannot be a completely randomly generated team sequence. Then, a greedy algorithm designed below is applied to each team sequence for scheduling, i.e., matching teams with tasks, generating an actual business scheduling table, and calculating the fitness of the scheduling scheme, i.e., the total cost of the scheme. Each team incurs a corresponding cost when completing the assigned task in the plan, so the total fitness is also the total cost of the entire plan. According to the content of the genetic algorithm, initially, the present invention sets the fitness to the cost of the subcontracted project resource scheduling plan, and the initial population is a series of effective team sequences generated by the genetic algorithm. Subsequently, a crossover operator, also known as a crossover operation, is used. This operator can choose a fixed or random length for the exchange segment, considering the crossover position. It swaps one or more values ​​representing the number of teams performing the same task in two team sequences. A mutation operator then randomly reselects a value representing the number of teams in a team sequence within its upper and lower limits. In each iteration, after processing with the crossover operator, a random number between 0 and 1 is used to determine whether to perform a mutation operation on each individual. If the random number is less than 0.1, a value in the selected valid team sequence is randomly reselected. This generates a new generation of the population. One team sequence represents one individual, and a population contains many team sequences, corresponding to many specific allocation and scheduling schemes. A greedy algorithm is then used to schedule the individuals within the population. Multiple iterations are performed on these individuals. Specifically, in each iteration, individuals in the population are selected pairwise for crossover, and then a mutation operation is performed randomly using a mutation operator. After the above operations are completed, a new generation of population is generated. Each individual in the new generation of population is scheduled using a greedy scheduling algorithm, and the fitness of each individual is calculated. This completes one iteration. The algorithm continues until it reaches the iteration termination conditions, including: (1) reaching the set upper limit of iteration time; (2) reaching the set upper limit of iteration rounds; (3) reaching the convergence condition. Finally, the solution with the lowest total cost is selected as the output of the algorithm.

[0145] The effective team sequence refers to the number of teams provided by different service providers for different sites in different regions. For example, in a scenario with 100 sites (including three types of tasks: Task 1, Task 2, and Task 3) located in only one geographical area, with only one type of task constituting a site (project), and one service provider, the effective team sequence [2,3,4] represents that the service provider selected 2 teams to complete Task 1, 3 teams to complete Task 2, and 4 teams to complete Task 3. These teams can complete the corresponding tasks multiple times, but cannot be scheduled for other types of tasks during the scheduling process.

[0146] When setting and iterating team sequences, the genetic algorithm generates multiple valid team sequences under constraints. The algorithm framework needs to satisfy the following two constraints:

[0147] (1) The number of teams selected in different tasks must be less than the maximum number that the service provider can provide in that task, i.e., share constraint.

[0148] (2) In a case with multiple service providers, the same task cannot be performed by only one service provider's team, i.e., monopoly constraint.

[0149] Please refer to Figure 10 , Figure 10 A flowchart illustrating the project resource scheduling method in an embodiment of the present invention is shown. In some embodiments, it can be understood that... Figure 10 for Figure 9The flowchart in the "Greedy Scheduling" module illustrates that the greedy scheduling algorithm first sorts the task list by priority and minimum start time, and then sorts the teams by cost. Next, the task list is initialized as an incomplete task list, and the team list is initialized as an available team list. The initialization time is set to day one. On that day, tasks in the incomplete task list are matched sequentially with teams in the available list based on cost performance, site type matching, and region matching. First, the incomplete task list is sorted in descending order by task order and priority, selecting tasks from top to bottom. Second, the available team list is sorted in descending order by cost performance. Teams in the same region as the selected task are selected and matched. Matched tasks and teams need to be updated in the list. If the time frame is less than one month, the scheduling continues to the next day. When 30 days have passed, it is necessary to determine whether the service provider for that month meets the share constraints and other limitations. If they do, the scheduling continues to the next day until all tasks are scheduled. If the requirements are not met, the scheduling work of the previous 30 days must be overturned. For teams that do not meet the constraints, adjustments will be made to the team list. One potential scenario is that a service provider is assigned too few tasks or has too low a share. In this case, during team sorting, it will be randomly determined whether to swap the position of that service provider's team in the available team list with teams ranked higher in the list. During rescheduling, the resources of this service provider will be given higher priority, thereby increasing or decreasing the priority of the corresponding teams. Teams with a share lower than the demand will be prioritized, while teams with excessively high shares will be de-prioritized, and rescheduling will proceed. Once a team is selected to participate in a task, it will be set as a working team in the available team list until the task's deadline is completed, at which point it can be reassigned as an unavailable team.

[0150] When matching teams and sites, the following constraints need to be considered:

[0151] (1) Arrange the sites in descending order of site priority and execute the sites with higher priority first.

[0152] (2) Arrange the task baselines of each service provider in order of time, and prioritize the resource team that has the shortest task time and meets the regional and station type requirements to execute the task.

[0153] In addition, this application also discloses a project resource scheduling device, please refer to... Figure 8 , Figure 8This invention discloses a module block diagram of a project resource scheduling device according to an embodiment of the present invention. The project resource scheduling device is applied to subcontracted projects of service providers and can implement the aforementioned project resource scheduling method. The project resource scheduling device includes: an initial data acquisition module 801, a team sequence construction module 802, a team matching module 803, a fitness calculation module 804, and a task scheduling optimization module 805. The initial data acquisition module 801, team sequence construction module 802, team matching module 803, fitness calculation module 804, and task scheduling optimization module 805 are all communicatively connected.

[0154] The initial data acquisition module 801 acquires pre-input resource scheduling data, including service provider parameters and task item parameters. The team sequence construction module 802 constructs a target team sequence based on the service provider parameters and preset constraint data. The team matching module 803 performs team allocation processing on the target team sequence according to the task item parameters to obtain an initial task scheduling scheme. The fitness calculation module 804 calculates the fitness of the initial task scheduling scheme to obtain the scheme fitness. The task scheduling optimization module 805 iteratively updates the initial task scheduling scheme based on the scheme fitness until the iteration state data reaches the preset iteration parameters, thus obtaining the target task scheduling scheme.

[0155] The initial data acquisition module 801 acquires pre-input resource scheduling data, which includes service provider parameters and task item parameters. The team sequence construction module 802 selects several teams that meet the conditions from the service provider parameters according to the preset constraint data, and constructs a sequence of these teams to obtain the target team sequence. The team matching module 803 performs team allocation processing on the target team sequence according to the task item parameters to assign each task to the corresponding team to obtain the initial task scheduling scheme. The fitness calculation module 804 calculates the fitness of each team in completing the task according to the initial task scheduling scheme to obtain the scheme fitness. The task scheduling optimization module 805 iteratively updates the initial task scheduling scheme according to the scheme fitness until the iteration state data reaches the preset iteration parameters to obtain the target task scheduling scheme. By acquiring input resource scheduling data, constructing a target team sequence based on service provider parameters and constraint data, assigning tasks to the target team sequence according to task project parameters, obtaining an initial task scheduling scheme, calculating the scheme fitness based on the initial task scheduling scheme, and optimizing the initial task scheduling scheme based on the scheme fitness, an optimized target task scheduling scheme is obtained. This can replace manual allocation of subcontracted projects, improving allocation efficiency and resource utilization.

[0156] The operation process of the project resource scheduling device in this embodiment is specifically described above. Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 and Figure 7 The steps S101 to S105, S201 to S206, S301 to S304, S401 to S403, S501 to S503, S601 to S603, and S701 to S704 of the project resource scheduling method are not described in detail here.

[0157] Another embodiment of the present invention discloses a project resource scheduling device, comprising: at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform, for example... Figure 1 Control method steps S101 to S105 Figure 2 Control method steps S201 to S206 Figure 3 Control method steps S301 to S304 Figure 4 Control method steps S401 to S403 Figure 5 Control method steps S501 to S503 Figure 6 The control method steps S601 to S603 and Figure 7 The project resource scheduling method in steps S701 to S704 of the control method.

[0158] Another embodiment of the present invention discloses a computer-readable storage medium, the storage medium comprising: storing computer-executable instructions for causing a computer to perform... Figure 1 Control method steps S101 to S105 Figure 2 Control method steps S201 to S206 Figure 3 Control method steps S301 to S304 Figure 4 Control method steps S401 to S403 Figure 5 Control method steps S501 to S503 Figure 6 The control method steps S601 to S603 and Figure 7 The project resource scheduling method in steps S701 to S704 of the control method.

[0159] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0160] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0161] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments, and various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention. Furthermore, the embodiments of the present invention and the features thereof can be combined with each other unless otherwise specified.

Claims

1. A project resource scheduling method, characterized in that, The project resource scheduling method, applied to subcontracted projects of service providers, includes: Obtain pre-input resource scheduling data; wherein, the resource scheduling data includes: service provider parameters and task item parameters, the service provider parameters include service task type and service area, and the task item parameters include reference task type and task area; A target team sequence is constructed based on the service provider parameters and preset constraint data; Based on the task project parameters, the target team sequence is assigned a team to obtain an initial task scheduling scheme. The fitness of the scheme is obtained by calculating the fitness of the scheme based on the initial task scheduling scheme; The initial task scheduling scheme is iteratively updated based on the scheme fitness until the iteration state data reaches the preset iteration parameters, thereby obtaining the target task scheduling scheme. The step of performing team allocation processing on the target team sequence based on the task project parameters to obtain an initial task scheduling scheme includes: The task parameters and the target team sequence are input into a preset greedy rule calculation model; wherein, the greedy rule calculation model includes: a project evaluation layer, a task sorting layer, and a team matching layer; The project evaluation layer performs project evaluation calculations on the task project parameters to obtain project evaluation values; The projects are sorted in descending order using the task sorting layer and the project evaluation value to obtain the target task sequence. The service cost of obtaining the target team sequence is obtained through the team matching layer; The target team sequence is sorted in descending order using the team matching layer and the service cost to obtain a sorted team sequence. Task type matching is performed using the team matching layer, the service task type, and the reference task type to obtain the task type matching relationship; Regional matching relationships are obtained by performing regional matching through the team matching layer, the service area, and the task area. Monthly share data is calculated using the team matching layer, the task type matching relationship, and the region matching relationship; If the monthly share data is less than the preset monthly share constraint threshold, the sorted team sequence is rearranged through the team matching layer to obtain a rearranged team sequence; The initial task scheduling scheme is obtained by matching the rearranged team sequence and the target task sequence through the team matching layer.

2. The project resource scheduling method according to claim 1, characterized in that, The step of constructing a candidate team sequence based on the service provider parameters and preset constraint data includes: The service provider parameters and the constraint data are input into a preset genetic law calculation model; wherein, the genetic law calculation model includes: an initialization layer, an individual evaluation layer, an individual selection layer, a crossover operation layer, and a mutation operation layer; An initial team sequence is generated using the initialization layer, the service provider parameters, and the constraint data. The team fitness is obtained by calculating the fitness using the individual evaluation layer and the service provider parameters. Candidate team sequences are selected from the initial team sequence through the individual selection layer and the team fitness; The candidate team sequences are subjected to sequence crossover operations using the crossover operation layer and preset crossover parameters to obtain the crossover team sequences. The target team sequence is obtained by mutating the cross-team sequence using the mutation operation layer and preset mutation parameters.

3. The project resource scheduling method according to claim 2, characterized in that, After iteratively updating the initial task scheduling scheme based on the scheme fitness until the iteration state data reaches the preset iteration parameters to obtain the target task scheduling scheme, the project resource scheduling method further includes: Obtain the task quantity data corresponding to the target team sequence; The priority of the target team sequence is adjusted based on the task quantity data to obtain the team priority; The target team sequence is sorted in descending order according to the team priority to obtain the sorted team sequence; The target task scheduling scheme is updated based on the sorted team sequence.

4. A resource scheduling device, characterized in that, The resource scheduling device, applied to subcontracting projects of service providers, includes: An initial data acquisition module is used to acquire pre-input resource scheduling data; wherein, the resource scheduling data includes: service provider parameters and task item parameters, the service provider parameters include service task type and service area, and the task item parameters include reference task type and task area; The team sequence construction module is used to construct a target team sequence based on the service provider parameters and preset constraint data; The team matching module is used to perform team allocation processing on the target team sequence according to the task project parameters to obtain an initial task scheduling scheme. The fitness calculation module is used to calculate the fitness of the scheme based on the initial task scheduling scheme; The task scheduling optimization module is used to iteratively update the initial task scheduling scheme according to the scheme fitness until the iteration state data reaches the preset iteration parameters to obtain the target task scheduling scheme. The step of performing team allocation processing on the target team sequence based on the task project parameters to obtain an initial task scheduling scheme includes: The task parameters and the target team sequence are input into a preset greedy rule calculation model; wherein, the greedy rule calculation model includes: a project evaluation layer, a task sorting layer, and a team matching layer; The project evaluation layer performs project evaluation calculations on the task project parameters to obtain project evaluation values; The projects are sorted in descending order using the task sorting layer and the project evaluation value to obtain the target task sequence. The service cost of obtaining the target team sequence is obtained through the team matching layer; The target team sequence is sorted in descending order using the team matching layer and the service cost to obtain a sorted team sequence. Task type matching is performed using the team matching layer, the service task type, and the reference task type to obtain the task type matching relationship; Regional matching relationships are obtained by performing regional matching through the team matching layer, the service area, and the task area. Monthly share data is calculated using the team matching layer, the task type matching relationship, and the region matching relationship; If the monthly share data is less than the preset monthly share constraint threshold, the sorted team sequence is rearranged through the team matching layer to obtain a rearranged team sequence; The initial task scheduling scheme is obtained by matching the rearranged team sequence and the target task sequence through the team matching layer.

5. A resource scheduling device, characterized in that, include: At least one processor, and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the project resource scheduling method as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform the project resource scheduling method as described in any one of claims 1 to 3.

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