CN117132232A - Project scheduling method and device - Google Patents

Project scheduling method and device Download PDF

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CN117132232A
CN117132232A CN202311108897.5A CN202311108897A CN117132232A CN 117132232 A CN117132232 A CN 117132232A CN 202311108897 A CN202311108897 A CN 202311108897A CN 117132232 A CN117132232 A CN 117132232A
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planned
resource allocation
scheduling
projects
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孙华
王世建
张克典
韩彩夏
吕荣水
王强
李智皓
鲁殿君
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CRRC Qingdao Sifang Co Ltd
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Abstract

The invention relates to the technical field of data processing, and provides a project scheduling method and device, wherein the method comprises the following steps: acquiring project priorities of a plurality of projects and available resources; acquiring a pre-constructed construction period objective function and pre-defined constraint conditions; the construction period objective function is a particle fitness function constructed according to the total construction period of a plurality of projects, the construction period objective function expresses that the weighted total construction period of the plurality of projects is minimized, the total construction period is determined based on the project priority, and the constraint condition is determined according to project information of the plurality of projects and available resources; according to the construction period objective function and the constraint condition, an optimal resource allocation scheme is obtained by utilizing a predefined scheduling solving algorithm, wherein the predefined scheduling solving algorithm comprises a particle swarm algorithm; and generating a scheduling plan according to the optimal resource allocation scheme. The invention can obtain the scheduling scheme with the shortest total period of a plurality of items under the condition of limited production resources, ensures the reasonable configuration of the generated resources and realizes the intelligent scheduling.

Description

Project scheduling method and device
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method and an apparatus for project scheduling.
Background
At present, the machining industry has the characteristics of high customization degree, small batch, tension in delivery cycle, vigorous competition and the like, and the production scheduling is an extremely important ring in the machining production process. In actual production, products of different projects need to be scheduled and produced simultaneously, and the problem belongs to the non-deterministic polynomial (NP-hard) problem. The existing project scheduling method only depends on manual experience for scheduling, which causes low efficiency, and cannot achieve the goal of shortest period of multiple projects under the condition of limited production resources, and a production enterprise cannot reasonably deal with the problems in a short time, so that the production rhythm is interrupted, and the production plan cannot be completed on time.
Disclosure of Invention
The invention provides a project scheduling method and related equipment, which are used for solving the defects in the prior art.
The invention provides a project scheduling method, which comprises the following steps:
acquiring project priorities of a plurality of projects and available resources;
acquiring a pre-constructed construction period objective function and pre-defined constraint conditions; wherein the project period objective function is a particle fitness function constructed according to the total project period of the plurality of projects, the project period objective function expresses that the weighted total project period of the plurality of projects is minimized, the total project period is determined based on the project priority, and the constraint condition is determined according to project information of the plurality of projects and the available resources;
According to the construction period objective function and the constraint condition, an optimal resource allocation scheme is obtained by utilizing a predefined scheduling solving algorithm, wherein the predefined scheduling solving algorithm comprises a particle swarm algorithm;
and generating a scheduling plan according to the optimal resource allocation scheme.
According to the project scheduling method provided by the invention, the optimal resource allocation scheme is obtained by utilizing a predefined scheduling solution algorithm according to the construction period objective function and the constraint condition, and the method comprises the following steps:
a resource initializing step: initializing available resources to generate initial particles, an initial planned procedure set and an initial to-be-planned procedure set, wherein the initial planned procedure set and the initial to-be-planned procedure set form a resource initial allocation scheme;
determining a procedure to be planned: determining a procedure to be planned from the initial procedure set to be planned according to the project priority;
a resource allocation adjustment step: under the condition that the resource demand corresponding to the determined to-be-planned working procedure is not greater than the resource residual quantity, the determined to-be-planned working procedure is put into an initial planned working procedure set to obtain a new to-be-planned working procedure set and a new planned working procedure set, and the planning time of the planned working procedure is calculated according to the new planned working procedure set; the new working procedure set to be planned and the new planned working procedure set form an adjusted resource allocation scheme;
Determining an optimal resource allocation scheme: and repeating the step of determining the procedure to be planned to the step of adjusting the resource allocation until a preset condition is reached, and determining an optimal resource allocation scheme from all the adjusted resource allocation schemes according to the planning time.
According to the project scheduling method provided by the invention, the optimal resource allocation scheme determining step comprises the following steps:
repeating the step of determining the working procedure to be planned until the resource allocation is adjusted under the condition that the new working procedure set to be planned is not empty, until the new working procedure set to be planned is empty;
and under the condition that the new working procedure set to be planned is empty, judging whether the quantity of the initial particles meets the requirement of the particle population scale, and under the condition that the quantity of the initial particles does not meet the requirement of the particle population scale, repeating the resource initializing step to the resource allocation adjusting step until the quantity of the initial particles meets the requirement of the particle population scale, so as to obtain a plurality of adjusted resource allocation schemes, and determining an optimal resource allocation scheme according to the planning time corresponding to the plurality of adjusted resource allocation schemes.
According to the project scheduling method provided by the invention, the project priority of a plurality of projects is obtained, and the project scheduling method comprises the following steps:
acquiring an index value matrix of a plurality of items, wherein the index value matrix comprises a plurality of index values of each item;
performing dimensionless conversion on the index value matrix to obtain a converted matrix;
performing association coefficient calculation on elements in the converted matrix to obtain an association coefficient matrix;
and calculating the item priority of each item according to the association coefficient matrix and the index weight corresponding to the index value.
According to the project scheduling method provided by the invention, the dimensionless transformation is carried out on the index value matrix to obtain a transformed matrix, and the project scheduling method comprises the following steps:
acquiring index values corresponding to the j-th index of all the items from the index value matrix, and determining a maximum index value and a minimum index value from the acquired index values;
respectively calculating a first difference value between the jth index value and the minimum index value of the ith item and a second difference value between the maximum index value and the minimum index value;
and determining the ratio between the first difference value and the second difference value as the dimensionless index value of the jth item, wherein i and j are natural numbers.
According to the project scheduling method provided by the invention, the method for acquiring the pre-constructed project period objective function comprises the following steps:
acquiring initial task starting time and final task finishing time of a plurality of projects;
calculating a time difference between the initial task start time and the final task completion time;
carrying out weighted summation calculation according to the project priority and the time difference value to obtain the total construction period of all projects;
and constructing a construction period objective function by taking the minimum total construction period as a target.
According to the project scheduling method provided by the invention, the acquisition of the predefined constraint conditions comprises the following steps:
acquiring process information and project resource demand information in each project according to project information of a plurality of projects;
determining serial constraints among the working procedures according to the working procedure information;
and determining a shared resource constraint according to the project resource demand information and the available resources, wherein the serial constraint among the working procedures and the shared resource constraint jointly form the constraint condition.
The invention also provides a project scheduling device, which comprises:
the project information acquisition module is used for acquiring project priorities and available resources of a plurality of projects;
The objective function and constraint condition acquisition module is used for acquiring a pre-constructed construction period objective function and a pre-defined constraint condition; wherein the project period objective function is a particle fitness function constructed according to the total project period of the plurality of projects, the project period objective function expresses that the weighted total project period of the plurality of projects is minimized, the total project period is determined based on the project priority, and the constraint condition is determined according to project information of the plurality of projects and the available resources;
the optimal resource allocation scheme determining module is used for obtaining an optimal resource allocation scheme by utilizing a predefined scheduling solution algorithm according to the construction period objective function and the constraint condition, wherein the predefined scheduling solution algorithm comprises a particle swarm algorithm;
and the scheduling plan generating module is used for generating a scheduling plan according to the optimal resource allocation scheme.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the project scheduling method as described in any one of the above when executing the program.
The invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the project scheduling method as described in any of the above.
According to the project scheduling method and device provided by the invention, the minimum total construction period of a plurality of projects is used as a construction period objective function, the available resources and project information are used as constraint conditions, an optimal resource allocation scheme is solved by utilizing a particle swarm algorithm, and a scheduling plan is obtained according to the optimal resource allocation scheme. Under the condition of limited productivity, the invention provides more reasonable and intelligent planning pre-arrangement capability, improves the on-time delivery rate of products, shortens the production process time of the products, establishes reasonable resource allocation for a plurality of commonly implemented projects, ensures the shortest project period of the plurality of projects and achieves the aim of optimal quality.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a project scheduling method according to the present invention;
FIG. 2 is a second flow chart of the project scheduling method according to the present invention;
FIG. 3 is a schematic view of a discharging device according to the present invention;
fig. 4 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
FIG. 1 is a schematic flow chart of a method for producing an item according to the present invention, and FIG. 2 is a second schematic flow chart of the method for producing an item according to the present invention; as shown in fig. 1 and 2, a project scheduling method includes the following steps:
step S101: item priorities of a plurality of items and available resources are obtained.
In this step, the item priority is determined according to the item information, where the item information specifically includes factors affecting the item priority and all correspond to respective weight values, and then the item priority is obtained by solving using a gray correlation analysis algorithm, and a specific solving process is described below.
In addition, available resource R is calculated according to the production capacity of the equipment k =wp×tb×ps×pt, where Wp is the number of K-class resources (number of bits); tb is the working time of each resource (each device); ps is the equipment operating rate; pt is the productivity (the capacity of a device, i.e., the number of parts processed per unit time of the device).
Step S102: acquiring a pre-constructed construction period objective function and pre-defined constraint conditions; wherein the project period objective function is a particle fitness function constructed according to the total project period of the projects, the project period objective function expresses that the weighted total project period of the projects is minimized, the total project period is determined based on the project priority, and the constraint condition is determined according to project information of the projects and the available resources.
The project information of the project includes a production process determined according to the product corresponding to each project, specifically, taking vehicle manufacturing as an example, the processes are classified according to the production process of the product, including a manufacturing process, a quality inspection process and an assembly process, and the process parameters related in the middle include a BOM, a size, an accuracy and vibration of the product. The product BOM is mainly used for generating a plan and a sub-plan; product size, accuracy and vibration are criteria for checking whether a product is acceptable.
In this step, an optimal solution problem, which aims at seeking the shortest total construction period of the project parallel production under the condition of limited productivity, is converted into a mathematical model, and a particle fitness function constructed according to the total construction period of the plurality of projects is used as a construction period objective function, that is, the construction period objective function is optimal when m projects share K kinds of production resources, and competition of the m projects to the limited resources is the only relation. The acquisition of the objective function and the constraint condition in the specific construction period is described below.
Step S103: and obtaining an optimal resource allocation scheme by utilizing a predefined scheduling solving algorithm according to the construction period objective function and the constraint condition, wherein the predefined scheduling solving algorithm comprises a particle swarm algorithm.
Step S104: and generating a scheduling plan according to the optimal resource allocation scheme.
According to the project scheduling method provided by the embodiment, the minimum total construction period of a plurality of projects is used as a construction period objective function, available resources and project information are used as constraint conditions, an optimal resource allocation scheme is solved by using a particle swarm algorithm, and a scheduling plan is obtained according to the optimal resource allocation scheme. Under the condition of limited productivity, the invention provides more reasonable and intelligent planning pre-arrangement capability, improves the on-time delivery rate of products, shortens the production process time of the products, establishes reasonable resource allocation for a plurality of commonly implemented projects, ensures the shortest project period of the plurality of projects and achieves the aim of optimal quality.
In some embodiments, step S103 includes:
a resource initializing step: and initializing available resources to obtain initial particles, an initial planned procedure set and an initial procedure set to be planned.
The initial planned working procedure set and the initial working procedure set to be planned form a resource initial allocation scheme.
Determining a procedure to be planned: and determining a procedure to be planned from the initial procedure set to be planned according to the project priority.
A resource allocation adjustment step: and under the condition that the resource demand corresponding to the determined to-be-planned working procedure is not greater than the resource residual quantity, the determined to-be-planned working procedure is put into an initial planned working procedure set, a new initial to-be-planned working procedure set and a new initial planned working procedure set are obtained, and the planning time of the planned working procedure is calculated according to the new initial planned working procedure set.
Wherein the new set of work procedures to be planned and the new set of planned work procedures constitute an adjusted resource allocation scheme.
Determining an optimal resource allocation scheme: repeating the step of determining the procedure to be planned to the step of adjusting the resource allocation until a preset condition is reached, and determining an optimal resource allocation scheme from all the adjusted resource allocation schemes according to the planning time; and generating a scheduling plan according to the optimal resource allocation scheme.
Specifically, the step of determining the optimal resource allocation scheme includes:
and repeating the step of determining the working procedure to be planned until the resource allocation is adjusted under the condition that the new initial working procedure set to be planned is not empty until the new initial working procedure set to be planned is empty.
And under the condition that the new initial procedure set to be planned is empty, judging whether the quantity of the initial particles meets the requirement of the particle population scale, and under the condition that the quantity of the initial particles does not meet the requirement of the particle population scale, repeating the resource initializing step to the resource allocation adjusting step until the quantity of the initial particles meets the requirement of the particle population scale, so as to obtain a plurality of adjusted resource allocation schemes, and determining an optimal resource allocation scheme according to the planning time corresponding to the plurality of adjusted resource allocation schemes.
In this embodiment, the particle swarm algorithm is used to optimally solve the problem that the project objective function is the minimum total project period of a plurality of projects and the constraint condition is available resources and the product manufacturing process, and the optimal resource allocation of each process in each project is obtained by solving. Further, the production cycle of each process (that is, the production cycle of the critical task in each project) is determined based on the optimal resource allocation, and a scheduling plan, which is a monthly plan for each project, is created based on the production cycle, the schedule of each project, and the Gantt chart.
In addition, after the initial scheduling plan is obtained, the method is executed according to the scheduling plan, the initial scheduling plan is dynamically adjusted according to the actual execution condition, and then the method is executed based on the adjusted scheduling plan and is repeated continuously.
In this embodiment, the solving process of the optimal resource allocation scheme includes the following steps:
s201: and initializing particle swarm parameters, particles, initialization, a planned procedure set and a to-be-planned procedure set to obtain information such as initial particles, an initial planned procedure set and an initial to-be-planned procedure set.
Wherein the initial particle swarm parameters comprise particle swarm count pop=50, iteration count itmaxgen=200, initial inertia coefficient ω max ＝0.9，ω min =0.2, learning coefficient c 1 ＝c 2 ＝2。
Particle initialization is the process of selecting the n=1 th particle as the initial particle, n=1, 2.
Initial waiting for planning procedure set C n Initial planned procedure set S n Time t=0.
S202: from the initial set of waiting-to-be-planned procedures C according to project priorities n Selecting a priority from a set of initial processes to be planned for an nth particleThe high process j is used as the process to be planned, and the standard period d of the determined process j to be planned is obtained j 。
S203: judging the demand r of the process j to be planned for the kth resource jk Whether or not the remaining quantity DeltaR of k resources at the time t is less than kt I.e. r jk <ΔR kt . At r jk <ΔR kt In the case of (1), the process j to be planned is put into the set S as a new planned process n In the meantime, in set C n And deleting the determined working procedure j to be planned, thereby obtaining a new working procedure set to be planned and a new working procedure set to be planned, wherein the new working procedure set to be planned and the new working procedure set to be planned are the adjusted resource allocation scheme.
After obtaining the new set of planned processes, the earliest start time EST of process j is calculated j And earliest end time EFT j 。
By recording the earliest start time EST of each process j j And earliest end time EFT j So that the earliest start time, the latest start time, the earliest end time and the latest end time in the actual task execution can be determined.
S204: judging whether the process J is the last process J of the project, if j=j, executing S205, and if J is not the last process J of the project, j=j+1, repeating S202-S204.
S205: judging whether the number n of the initial particles reaches the particle population scale P, namely whether n is P, if n=P, selecting an adjusted resource allocation scheme with the minimum planning time of all planned procedures from P adjusted resource allocation schemes, and taking the adjusted resource allocation scheme as an optimal resource allocation scheme; if n+.p, let n=n+1, repeat S201-S205.
During particle population initialization, the particle code length l=n 1 +n 2 +...+n i +…n m +2, where n i The number of steps of the ith item, n m The number of steps for the mth item, m representing the total number of items.
The 1 st node is constructed as a virtual starting node, the n node is a virtual ending node, the construction period and the resource requirement of the node are all 0, so that the total node number is the sum of the number of all project steps plus 2, the dimension of each particle is set to be L, L elements of each particle represent the whole process contained in a plurality of projects, and L parameters of the optimal particle represent the task priority.
Position X of nth particle of particle group n ＝(x n1 ,x n2 ,……x nl ……x nL ) Wherein x is nl For the nth particle, the first dimension value, l=1, 2,.. nl Indicating the process priority value. X is under the constraint of the relation between the front and the back of the working procedure n The value of (2) represents the priority level of the corresponding procedure, and the elements in the position vector are ordered to obtain a node number ordering sequence, so that a feasible scheduling scheme is obtained.
Setting a particle fitness function according to a project scheduling optimization construction period objective function:
wherein C is a non-zero non-negative fitness function adjustment coefficient, m items total number, n i For the number of steps of item i, T is the project objective function, A is the time difference between the last procedure of the project i and the first procedure of the project i i Is the priority weight of item i. Fitness (X) n ) The larger the value, the smaller the construction period objective function T, and the better the completion time of the planning result.
The particle fitness function is an initial parameter of a particle swarm algorithm and is used for evaluating the position of particles. The particle applicability value can be obtained by the particle applicability function. If the current fitness value is greater than the previously calculated optimal value, the current position is the optimal position for the particle experience, at which point the current fitness is the optimal fitness for the particle experience.
According to the project scheduling method provided by the embodiment of the invention, the minimum total construction period of a plurality of projects is used as a construction period objective function, the available resources and the product manufacturing procedures are used as constraint conditions, the period of each procedure in each project is obtained by solving through a particle swarm algorithm, and then an optimal asset allocation scheme is obtained, and a scheduling plan is obtained according to the optimal resource allocation scheme. Under the condition of limited productivity, the invention provides more reasonable and intelligent planning pre-arrangement capability, improves the on-time delivery rate of products, shortens the production process time of the products, establishes reasonable resource allocation for a plurality of commonly implemented projects, ensures the shortest project period of the plurality of projects and achieves the aim of optimal quality.
Further, on the basis of the above embodiment, in step S101, the acquiring the item priorities of the plurality of items includes:
an index value matrix of a plurality of items is obtained, the index value matrix including a plurality of index values for each item.
Wherein the index value includes a demand index value, a delivery time index value, and an urgency index value.
Specifically, if m items are set and item priority calculation is required for the m items, the index value matrix a= [ a ] 1 ,A 2 ……A m ] T . Each item corresponds to a plurality of index values, in this embodiment, a demand index value, a delivery time index value, and an urgency index value, i.e., an index quantization score A of item i are selected i ＝[a i1 ,a i2 ,a i3 ],(i＝1,2……m)。
Constructing a multi-item index value matrix A:
wherein a is ij Represents the j-th index value of item i.
And carrying out dimensionless conversion on the index value matrix to obtain a converted matrix. The method specifically comprises the following steps:
from a matrix of index valuesAcquiring index values corresponding to the j-th index of all the items, and determining a maximum index value a from the acquired index values jmax And minimum index value a jmin ；
Respectively calculating a first difference value between the jth index value and the minimum index value of the ith item and a second difference value between the maximum index value and the minimum index value;
And determining the ratio between the first difference value and the second difference value as the dimensionless index value of the jth item. Namely, index value a ij Conversion to dimensionless b ij ：
Wherein b ij The larger the value, the closer the index is to the index optimum value, a jmax And a jmin The minimum value and the maximum value of the j index value of the item are respectively.
All index values a ij After dimensionless conversion, a converted matrix B is obtained,
and carrying out association coefficient calculation on the elements in the converted matrix by using a gray association coefficient analysis algorithm to obtain an association coefficient matrix.
In the present embodiment, the reference matrix is determined from the converted matrix B And record all element relation numbers of the project as:
wherein eta ij For the correlation coefficient between the jth index value and the index optimum value of the ith item, ρ is a resolution coefficient (in this embodiment, ρ=0.5),is the optimal value of the j index in the non-dimensionalized matrix B,representation b ij And reference matrix->Minimum value after difference +.>Representation b ij And reference matrix->Maximum value after difference +_>Representation b ij To->Hamming distance of (a).
Thereby obtaining an association coefficient matrix epsilon:
wherein eta i ＝(η i1 ,η i2 ,η i3 ) The index value is the association vector of each index value and the optimal value of the ith item.
And calculating the item priority of each item according to the association coefficient matrix and the index weight corresponding to the index value.
Wherein the index weight comprises a demand index, a delivery time index and an emergency degree index.
In the present embodiment, the degree of association γ between each item index value and the optimum value i I.e. project priority gamma i The method comprises the following steps: gamma ray i ＝η i W is an index weight, where the index weight includes a demand index, a delivery time index, and an urgency index, and the specific value of the index weight is determined according to expert experience corresponding to the demand index, the delivery time index, and the urgency index, in this embodiment w= (0.25,0.35,0.4) T . The Fitness formula Fitness (X h ) Wherein a is i Take the value of gamma i
In addition, the calculated gamma i The larger the value, the higher the priority of the expression item i.
It should be noted that the demand index, the delivery time index, and the urgency index are determined according to factors affecting the priority of the item, and in this embodiment, the factors affecting the priority of the item are determined to include the number of demands of the item, the delivery date of the item, and the urgency of the order. Their respective weight setting rules are as follows:
(1) According to the quantity of the demands in the orders, configuring a demand index for each order; the higher the demand, the smaller the index value; the demand index is determined by an arithmetic average method. Demand index = number of items/total number of items.
(2) According to the delivery time, configuring a delivery time index for each order, wherein the later the delivery time is, the smaller the weight value is; lead time index value = standard period/lead time.
(3) And (3) configuring emergency weights for each order according to the emergency degree of the order, and assigning values by adopting expert experience values, wherein the higher the emergency degree is, the larger the index value is.
According to the scheduling scheme provided by the embodiment of the invention, the priority of each item is obtained through the gray correlation coefficient analysis algorithm, so that the items can be scheduled according to the priority of the items, and all the items can be guaranteed to be delivered on time.
Further, on the basis of the foregoing embodiment, in step S102, the construction period objective function according to the total construction period of the plurality of items includes:
the initial task start time and the final task completion time of the plurality of items are obtained.
A time difference between the initial task start time and the final task completion time is calculated.
And carrying out weighted summation calculation according to the project priority and the time difference value to obtain the total construction period of all projects.
And constructing a construction period objective function by taking the minimum total construction period as a target. That is, the construction period objective function isWherein (1)>For the final process completion time of item i, t i0 A is the initial process start time of item i, a i Is the priority weight of item i.
In step S102, the obtaining a predefined constraint condition includes:
and obtaining process information and project resource requirement information in each project according to project information of the projects.
And determining serial constraints among the working procedures according to the working procedure information. Namely t ij -t ih ≥d ij ,Wherein d ij For the working period of the jth working procedure in the ith item, P ij A set of all immediately preceding steps, t, of the jth step in the ith item ij The completion time of the jth process in the ith item, h being all immediately preceding processes in the ith item, t ih The completion time of all immediately preceding steps in the ith item.
And determining a shared resource constraint according to project resource demand information and the available resources, wherein serial constraint among the working procedures and the shared resource constraint are constraint conditions. That is to say,wherein T is ij A represents the jth process of item i being executed at time t t R is the set of ongoing processes at time t ijk For the use amount of the kth resource in the jth procedure in the ith project every day, R k Daily maximum supply of kth shared resources.
In addition, there are constraints on the start time of the process, the process period, the resources, and the like, and in this embodiment, the overall work period objective function and the constraint conditions are:
t 00 ＝0 (3)
t ij ≥0, d ij ≥0,r ijk ≥0 (5)
wherein, the formula (1) is a construction period objective function, which is used for representing that the weighted total construction period of m projects is shortest;
the formula (2) represents the serial constraint relation of the process, and represents that the post process can be started only after the pre process is completed;
the starting time of the virtual task of the project is 0, namely project resources and time are not occupied;
equation (4) is a shared resource constraint, i.e., it indicates that the total amount of demand for resource k by all items performed at time t cannot exceed its supply.
The formula (5) represents that the task starting time, the task construction period and the resources are all nonnegative numbers;
equation (6) shows that the sum of the priority weight coefficients of the items is 1.
The production scheduling device provided by the invention is described below, and the production scheduling device described below and the item production scheduling method described above can be correspondingly referred to each other.
FIG. 3 is a schematic view of a discharging device according to the present invention; as shown in fig. 3, a scheduling device includes:
the item information obtaining module 301 is configured to obtain item priorities and available resources of a plurality of items.
The objective function and constraint condition acquisition module 302 is configured to acquire a pre-constructed construction period objective function and a pre-defined constraint condition; wherein the project period objective function is a particle fitness function constructed according to the total project period of the projects, the project period objective function expresses that the weighted total project period of the projects is minimized, the total project period is determined based on the project priority, and the constraint condition is determined according to project information of the projects and the available resources.
And the optimal resource allocation scheme determining module 303 is configured to obtain an optimal resource allocation scheme according to the construction period objective function and the constraint condition by using a predefined scheduling solution algorithm, where the predefined scheduling solution algorithm includes a particle swarm algorithm.
And the scheduling plan generating module 304 is configured to generate a scheduling plan according to the optimal resource allocation scheme.
In the project scheduling device provided by the embodiment of the invention, the minimum total construction period of a plurality of projects is used as a construction period objective function, available resources and project information are used as constraint conditions, an optimal resource allocation scheme is solved by utilizing a particle swarm algorithm, and a scheduling plan is obtained according to the optimal resource allocation scheme. Under the condition of limited productivity, the invention provides more reasonable and intelligent planning pre-arrangement capability, improves the on-time delivery rate of products, shortens the production process time of the products, establishes reasonable resource allocation for a plurality of commonly implemented projects, ensures the shortest project period of the plurality of projects and achieves the aim of optimal quality.
Optionally, the optimal resource allocation scheme determining module 303 includes:
the resource initialization module is used for initializing available resources and generating initial particles, an initial planned procedure set and an initial to-be-planned procedure set, wherein the initial planned procedure set and the initial to-be-planned procedure set form a resource initial allocation scheme;
and the to-be-planned procedure determining module is used for determining the to-be-planned procedure from the initial to-be-planned procedure set according to the project priority.
The resource allocation adjustment module is used for placing the determined working procedure to be planned into an initial planned working procedure set under the condition that the resource demand corresponding to the determined working procedure to be planned is not greater than the resource residual quantity, obtaining a new working procedure set to be planned and a new planned working procedure set, and calculating the planning time of the planned working procedure according to the new planned working procedure set; the new set of work procedures to be planned and the new set of planned work procedures constitute an adjusted resource allocation scheme.
And the optimal resource allocation scheme determining module is used for repeatedly triggering the to-be-planned procedure determining module and the resource allocation adjusting module to execute until a preset condition is reached, and determining an optimal resource allocation scheme from all the adjusted resource allocation schemes according to the planning time.
Optionally, the optimal resource allocation scheme determining module includes:
and the first triggering execution module is used for repeatedly triggering the execution of the to-be-planned procedure determining module and the resource allocation adjusting module until the new to-be-planned procedure set is empty under the condition that the new to-be-planned procedure set is not empty.
And the second triggering execution module is used for judging whether the quantity of the initial particles meets the requirement of the particle population scale or not under the condition that the new working procedure set to be planned is empty, repeatedly triggering the resource initialization module, the working procedure determining module to be planned and the resource allocation adjustment module to execute under the condition that the quantity of the initial particles does not meet the requirement of the particle population scale until the quantity of the initial particles meets the requirement of the particle population scale, so as to obtain a plurality of adjusted resource allocation schemes, and determining an optimal resource allocation scheme according to the planning time corresponding to the plurality of adjusted resource allocation schemes.
Optionally, the item information obtaining module 301 includes:
the index value matrix acquisition module is used for acquiring index value matrixes of a plurality of projects, wherein the index value matrixes comprise a plurality of index values of each project.
And the matrix conversion module is used for carrying out dimensionless conversion on the index value matrix to obtain a converted matrix.
And the association calculation module is used for carrying out association coefficient calculation on the elements in the converted matrix to obtain an association coefficient matrix.
And the priority calculating module is used for calculating the item priority of each item according to the association coefficient matrix and the index weight corresponding to the index value.
Optionally, the matrix conversion module includes:
the index extremum determining module is used for acquiring index values corresponding to the j-th index of all the items from the index value matrix and determining the maximum index value and the minimum index value from the acquired index values.
The difference calculating module is used for calculating a first difference value between the jth index value and the minimum index value of the ith item and a second difference value between the maximum index value and the minimum index value of the ith item respectively.
The dimensionless determining module is used for determining the ratio between the first difference value and the second difference value as the dimensionless value of the jth index value of the ith item, wherein i and j are natural numbers.
Optionally, the objective function and constraint acquisition module 302 includes: the objective function acquisition module is used for:
the initial task start time and the final task completion time of the plurality of items are obtained.
A time difference between the initial task start time and the final task completion time is calculated.
And carrying out weighted summation calculation according to the project priority and the time difference value to obtain the total construction period of all projects.
And constructing a construction period objective function by taking the minimum total construction period as a target.
Optionally, the objective function and constraint acquisition module 302 includes: constraint condition acquisition module for:
and obtaining process information and project resource requirement information in each project according to project information of the projects.
And determining serial constraints among the working procedures according to the working procedure information.
And determining a shared resource constraint according to the project resource demand information and the available resources, wherein the serial constraint among the working procedures and the shared resource constraint jointly form the constraint condition.
Fig. 4 illustrates a physical schematic diagram of an electronic device, as shown in fig. 4, which may include: processor 410 (processor), communication interface 420 (Communications Interface), memory 430 (memory) and communication bus 440, wherein processor 410, communication interface 420, and memory 430 communicate with each other via communication bus 440. The processor 410 may invoke logic instructions in the memory 430 to perform an item scheduling method comprising:
Item priorities of a plurality of items and available resources are obtained.
Acquiring a pre-constructed construction period objective function and pre-defined constraint conditions; wherein the project period objective function is a particle fitness function constructed according to the total project period of the projects, the project period objective function expresses that the weighted total project period of the projects is minimized, the total project period is determined based on the project priority, and the constraint condition is determined according to project information of the projects and the available resources.
And obtaining an optimal resource allocation scheme by utilizing a predefined scheduling solving algorithm according to the construction period objective function and the constraint condition, wherein the predefined scheduling solving algorithm comprises a particle swarm algorithm.
And generating a scheduling plan according to the optimal resource allocation scheme.
Further, the logic instructions in the memory 430 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform a method of project scheduling provided by the methods described above, the method comprising:
item priorities of a plurality of items and available resources are obtained.
Acquiring a pre-constructed construction period objective function and pre-defined constraint conditions; wherein the project period objective function is a particle fitness function constructed according to the total project period of the projects, the project period objective function expresses that the weighted total project period of the projects is minimized, the total project period is determined based on the project priority, and the constraint condition is determined according to project information of the projects and the available resources.
And obtaining an optimal resource allocation scheme by utilizing a predefined scheduling solving algorithm according to the construction period objective function and the constraint condition, wherein the predefined scheduling solving algorithm comprises a particle swarm algorithm.
And generating a scheduling plan according to the optimal resource allocation scheme.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the above-provided project scheduling methods, the method comprising:
item priorities of a plurality of items and available resources are obtained.
Acquiring a pre-constructed construction period objective function and pre-defined constraint conditions; wherein the project period objective function is a particle fitness function constructed according to the total project period of the projects, the project period objective function expresses that the weighted total project period of the projects is minimized, the total project period is determined based on the project priority, and the constraint condition is determined according to project information of the projects and the available resources.
And obtaining an optimal resource allocation scheme by utilizing a predefined scheduling solving algorithm according to the construction period objective function and the constraint condition, wherein the predefined scheduling solving algorithm comprises a particle swarm algorithm.
And generating a scheduling plan according to the optimal resource allocation scheme.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A method of scheduling items, comprising:
acquiring project priorities of a plurality of projects and available resources;
acquiring a pre-constructed construction period objective function and pre-defined constraint conditions; wherein the project period objective function is a particle fitness function constructed according to the total project period of the plurality of projects, the project period objective function expresses that the weighted total project period of the plurality of projects is minimized, the total project period is determined based on the project priority, and the constraint condition is determined according to project information of the plurality of projects and the available resources;
according to the construction period objective function and the constraint condition, an optimal resource allocation scheme is obtained by utilizing a predefined scheduling solving algorithm, wherein the predefined scheduling solving algorithm comprises a particle swarm algorithm;
and generating a scheduling plan according to the optimal resource allocation scheme.
2. The project scheduling method according to claim 1, wherein the obtaining an optimal resource allocation scheme according to the construction period objective function and the constraint condition by using a predefined scheduling solution algorithm includes:
a resource initializing step: initializing available resources to generate initial particles, an initial planned procedure set and an initial to-be-planned procedure set, wherein the initial planned procedure set and the initial to-be-planned procedure set form a resource initial allocation scheme;
Determining a procedure to be planned: determining a procedure to be planned from the initial procedure set to be planned according to the project priority;
a resource allocation adjustment step: under the condition that the resource demand corresponding to the determined to-be-planned working procedure is not greater than the resource residual quantity, the determined to-be-planned working procedure is put into an initial planned working procedure set to obtain a new to-be-planned working procedure set and a new planned working procedure set, and the planning time of the planned working procedure is calculated according to the new planned working procedure set; the new working procedure set to be planned and the new planned working procedure set form an adjusted resource allocation scheme;
determining an optimal resource allocation scheme: and repeating the step of determining the procedure to be planned to the step of adjusting the resource allocation until a preset condition is reached, and determining an optimal resource allocation scheme from all the adjusted resource allocation schemes according to the planning time.
3. The item scheduling method according to claim 2, wherein the optimal resource allocation scheme determining step includes:
repeating the step of determining the working procedure to be planned until the resource allocation is adjusted under the condition that the new working procedure set to be planned is not empty, until the new working procedure set to be planned is empty;
And under the condition that the new working procedure set to be planned is empty, judging whether the quantity of the initial particles meets the requirement of the particle population scale, and under the condition that the quantity of the initial particles does not meet the requirement of the particle population scale, repeating the resource initializing step to the resource allocation adjusting step until the quantity of the initial particles meets the requirement of the particle population scale, so as to obtain a plurality of adjusted resource allocation schemes, and determining an optimal resource allocation scheme according to the planning time corresponding to the plurality of adjusted resource allocation schemes.
4. The item scheduling method of claim 1, wherein the obtaining the item priorities of the plurality of items comprises:
acquiring an index value matrix of a plurality of items, wherein the index value matrix comprises a plurality of index values of each item;
performing dimensionless conversion on the index value matrix to obtain a converted matrix;
performing association coefficient calculation on elements in the converted matrix to obtain an association coefficient matrix;
and calculating the item priority of each item according to the association coefficient matrix and the index weight corresponding to the index value.
5. The method for project scheduling according to claim 4, wherein said dimensionless transforming the index value matrix to obtain a transformed matrix comprises:
Acquiring index values corresponding to the j-th index of all the items from the index value matrix, and determining a maximum index value and a minimum index value from the acquired index values;
respectively calculating a first difference value between the jth index value and the minimum index value of the ith item and a second difference value between the maximum index value and the minimum index value;
and determining the ratio between the first difference value and the second difference value as the dimensionless index value of the jth item, wherein i and j are natural numbers.
6. The project scheduling method of any one of claims 1-5, wherein the obtaining a pre-constructed project objective function comprises:
acquiring initial task starting time and final task finishing time of a plurality of projects;
calculating a time difference between the initial task start time and the final task completion time;
carrying out weighted summation calculation according to the project priority and the time difference value to obtain the total construction period of all projects;
and constructing a construction period objective function by taking the minimum total construction period as a target.
7. The project scheduling method of any one of claims 1-5, wherein the obtaining a predefined constraint includes:
acquiring process information and project resource demand information in each project according to project information of a plurality of projects;
Determining serial constraints among the working procedures according to the working procedure information;
and determining a shared resource constraint according to the project resource demand information and the available resources, wherein the serial constraint among the working procedures and the shared resource constraint jointly form the constraint condition.
8. An item scheduling apparatus, comprising:
the project information acquisition module is used for acquiring project priorities and available resources of a plurality of projects;
the objective function and constraint condition acquisition module is used for acquiring a pre-constructed construction period objective function and a pre-defined constraint condition; wherein the project period objective function is a particle fitness function constructed according to the total project period of the plurality of projects, the project period objective function expresses that the weighted total project period of the plurality of projects is minimized, the total project period is determined based on the project priority, and the constraint condition is determined according to project information of the plurality of projects and the available resources;
the optimal resource allocation scheme determining module is used for obtaining an optimal resource allocation scheme by utilizing a predefined scheduling solution algorithm according to the construction period objective function and the constraint condition, wherein the predefined scheduling solution algorithm comprises a particle swarm algorithm;
And the scheduling plan generating module is used for generating a scheduling plan according to the optimal resource allocation scheme.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the item scheduling method of any one of claims 1 to 7 when the program is executed by the processor.
10. A non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the project scheduling method of any one of claims 1 to 7.
CN202311108897.5A 2023-08-30 2023-08-30 Project scheduling method and device Pending CN117132232A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117745721A (en) * 2024-02-19 2024-03-22 江苏中天互联科技有限公司 Scheduling plan optimization method based on identification analysis and related equipment

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117745721A (en) * 2024-02-19 2024-03-22 江苏中天互联科技有限公司 Scheduling plan optimization method based on identification analysis and related equipment
CN117745721B (en) * 2024-02-19 2024-05-07 江苏中天互联科技有限公司 Scheduling plan optimization method based on identification analysis and related equipment

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