CN112801414A - Assembly type building component scheduling optimization method and system - Google Patents

Assembly type building component scheduling optimization method and system Download PDF

Info

Publication number
CN112801414A
CN112801414A CN202110229789.8A CN202110229789A CN112801414A CN 112801414 A CN112801414 A CN 112801414A CN 202110229789 A CN202110229789 A CN 202110229789A CN 112801414 A CN112801414 A CN 112801414A
Authority
CN
China
Prior art keywords
production line
component
production
type
scheduling
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202110229789.8A
Other languages
Chinese (zh)
Other versions
CN112801414B (en
Inventor
李学俊
梁梦莲
琚川徽
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Green Industry Innovation Research Institute of Anhui University
Original Assignee
Green Industry Innovation Research Institute of Anhui University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Green Industry Innovation Research Institute of Anhui University filed Critical Green Industry Innovation Research Institute of Anhui University
Priority to CN202110229789.8A priority Critical patent/CN112801414B/en
Publication of CN112801414A publication Critical patent/CN112801414A/en
Application granted granted Critical
Publication of CN112801414B publication Critical patent/CN112801414B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/12—Computing arrangements based on biological models using genetic models
    • G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0633—Workflow analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G06Q10/103—Workflow collaboration or project management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/08—Construction

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Physics & Mathematics (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Theoretical Computer Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Marketing (AREA)
  • Tourism & Hospitality (AREA)
  • General Business, Economics & Management (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Evolutionary Biology (AREA)
  • Data Mining & Analysis (AREA)
  • Game Theory and Decision Science (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Development Economics (AREA)
  • Biomedical Technology (AREA)
  • Evolutionary Computation (AREA)
  • Genetics & Genomics (AREA)
  • Artificial Intelligence (AREA)
  • Educational Administration (AREA)
  • Computational Linguistics (AREA)
  • Primary Health Care (AREA)
  • Physiology (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • General Factory Administration (AREA)

Abstract

The invention discloses a production scheduling optimization method and system for an assembly type building component, which are used for solving the number of components to be divided of each component type in each production line based on linear programming on the premise of balancing the production time of each production line to obtain a component set of each production line; aiming at the shortest delivery time, solving the component production sequence of the component set of each production line based on a greedy-genetic algorithm to obtain the optimal component production sequence with the shortest production time of each production line, and realizing the optimization of component production sequence; with the optimal cost of the mold as a target, solving the minimum number of mold sleeves of each mold type in the component set of each production line based on nonlinear programming to obtain the number of mold sleeves on each production line, and realizing the optimization of component scheduling; the scheduling optimization method aims at the shortest delivery time and the optimal mold cost, and improves the productivity of the production line.

Description

Assembly type building component scheduling optimization method and system
Technical Field
The invention relates to the technical field of assembly type building component scheduling, in particular to an assembly type building component scheduling optimization method and system.
Background
The assembly type building is the green building mode with the most development prospect in China at present, the prefabricated part is the core of the assembly type building, and the production level of the prefabricated part determines the development of the assembly type building to a great extent. At present, the number of types of components is continuously increased in China, and the requirements of the components are continuously expanded. However, due to the low standardization of the components, the low degree of digital informatization and the low utilization rate of production resources, the production of the components is subject to bottlenecks, and the expected production level is difficult to achieve. Aiming at the problems, the method starts from a workshop production scheduling link, optimizes the production scheduling process and improves the production efficiency.
Scheduling may be simply understood as making a production plan in advance. Through research, a plurality of APS (advanced Planning and scheduling) software are available on the market, and the software is focused on globally managing and controlling production workshop resources, digitally analyzing production and manufacturing information and monitoring workshop production conditions in real time. Aps (advanced Planning and scheduling) software is numerous, but is not popularized and used in prefabricated member enterprises because of not being completely matched with the requirements of enterprises and not being strong in software flexibility. In contrast, many researchers have adopted algorithmic approaches to solve problems in scheduling, such as: the scheduling method based on the genetic algorithm solves the problem that the scheduling plan cannot be changed in time by manpower, and improves the scheduling accuracy; the balanced scheduling method based on weighted round robin scheduling realizes balanced load of the production line and improves the utilization rate of equipment; and analyzing the order by a certain strategy, adding a functional module, perfecting the scheduling process and the like.
Through investigation, a production workshop still has more scheduling pain points, so that a scheduling software with strong pertinence and high flexibility is built for enterprises, and the method has great significance.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides a scheduling optimization method and system for an assembly type building component, which aim to achieve the purposes of shortest delivery time and optimal mold cost and improve the productivity of a production line.
The invention provides an assembly type building component scheduling optimization method, which comprises the following steps:
on the premise of balancing the production time of each production line, solving the number of the components to be divided of each component type in each production line based on linear programming to obtain a component set of each production line;
aiming at the shortest delivery time, solving the component production sequence of the component set of each production line based on a greedy-genetic algorithm to obtain the optimal component production sequence with the shortest production time of each production line, and realizing the optimization of component production sequence;
and with the optimal mold cost as a target, solving the minimum mold sleeve number of each mold type in the component set of each production line based on nonlinear programming to obtain the mold sleeve number on each production line, and realizing the optimization of component scheduling.
Further, on the premise of balancing the production time of each production line, the number of components to be divided of each component type in each production line is solved based on linear programming, and before the component set of each production line is obtained, the optimal production line set is screened out with the minimum production line number as the target, and the specific screening process is as follows:
s011: initializing a selected production line set as an empty set, analyzing all component types contained in a component set to be scheduled in an order, and randomly selecting a certain component type from the component sets as a current component type;
s012: determining an optional production line set according to the current component type, judging whether a production line capable of producing the component type exists in the selected production line set, if so, entering step S013, and if not, entering step S014;
s013: when the current component type screening is finished, keeping the selected production line set unchanged, and entering step S015;
s014: determining an optional production line set of the current component type, adding a production line with high production efficiency for producing the current component type in the optional production line set into the selected production line set, and entering step S015;
s015: and continuously traversing the remaining component types in the component set to be scheduled, and repeating the steps S012 to S014 until all the component types are traversed.
Further, on the premise of balancing the production time of each production line, the number of the components to be divided of each component type in each production line is solved based on linear programming, and a component set of each production line is obtained, wherein the method comprises the following steps:
s101: determining a production line set and types of components which can be produced on each production line in the production line set;
s102: determining the production time of each component type produced by each production line in the production line set;
s103: determining the number of components of each component type in the order;
s104: linear programming is adopted for the production line to solve the number of the components to be distributed for each component type of each production line.
Further, the expression of the linear program is as follows:
Figure BDA0002958648340000031
where i represents the number of lines in the plant, j represents the component type in the order, min z represents the minimum of solving the objective function z, maxtDenotes maximum production time, mintDenotes minimum production time, CjTotal number of members, X, representing type j of memberijNumber of components, T, representing type j of components to be separated in line iijRepresenting the production time of the production line i for producing the component type j;
further, aiming at the shortest delivery time, solving the component production sequence of the component set of each production line based on a greedy-genetic algorithm to obtain the optimal component production scheduling sequence with the shortest production time of each production line, and realizing the optimization of component production scheduling, the method comprises the following steps:
s201: determining a production line set, solving each production line component set based on linear programming, and randomly selecting one production line in the production line set;
s202: determining a set of components assigned to the selected production line based on the selected production line;
s203: initializing a group of component sequences of the determined component set based on a random algorithm to serve as parent sequences;
s204: generating a plurality of descendant sequences from the parent sequence according to a certain rule;
s205: respectively calculating the production time of the parent sequence and the production time of all the offspring sequences, if the production time of all the offspring sequences is more than or equal to the production time of the parent sequence, executing the step S206, and if the production time of the offspring sequences is less than that of the parent sequence, executing the step S207;
s206: outputting the parent sequence as an optimal component scheduling sequence;
s207: respectively taking the child sequences with the production time less than that of the parent sequences as new parent sequences, and executing the steps S204 to S206;
s208: and continuing to select the next production line from the production line set in the step S201, and repeating the steps S202 to S207 until all the production lines in the production line set are traversed to finish, so as to obtain the optimal component production sequence of each production line.
Further, at step S204: generating a plurality of descendant sequences from the parent sequence according to a certain rule, and generating the rule as follows: the offspring sequences are exchanged by two random building blocks in the parent sequence.
Further, with the goal of optimal mold cost, solving the minimum number of mold sleeves of each mold type in the component set of each production line based on nonlinear programming to obtain the number of mold sleeves on each production line, and realizing optimization of component scheduling, the method comprises the following steps:
s301: determining a production line set and determining the price of each mould type;
s302: determining a production line set with selectable models of all molds and the maximum station time of all production lines in the selectable production line set;
s303: determining the number of components required to be produced by each mould type;
s304: and solving the minimum number of the die sets of each die type on each production line in the production line set based on nonlinear programming.
Further, the expression of the non-linear programming is as follows:
Figure BDA0002958648340000041
where min z represents the minimum value for solving the objective function z, DHB00iIndicates the mold type, PiIndicating the mold model DHB00iPrice of (X)iIndicating the mold model DHB00iNumber of die sets, TDHB00iIndicating the mold model DHB00iProduction time of the corresponding component type in the corresponding production line, MSTiIndicating the mold model DHB00iMaximum station time of the corresponding component type in the corresponding production line, CiIndicating the mold model DHB00iThe number of the components of the corresponding component type to be produced on the corresponding production line, M represents the production time, and N represents the upper limit of the number of the die sets.
A system for scheduling production optimization for prefabricated building components, comprising: the distribution module, the component scheduling order calculation module and the mold set number calculation module;
the distribution module is used for solving the number of the components to be distributed of each component type in each production line based on linear programming on the premise of balancing the production time of each production line to obtain a component set of each production line;
the component scheduling sequence calculation module is used for solving a component production sequence of the component set of each production line based on a greedy-genetic algorithm by taking the shortest delivery time as a target to obtain the optimal component scheduling sequence of each production line with the shortest production time, so as to realize component scheduling optimization;
the mold sleeve number calculation module is used for solving the minimum mold sleeve number of each mold type in the component set of each production line based on nonlinear programming by taking the optimal mold cost as a target to obtain the mold sleeve number on each production line, so that the optimization of component scheduling is realized.
A computer readable storage medium having stored thereon a number of acquisition and classification procedures for being invoked by a processor and performing the method of set-up building element schedule optimization of claim 1.
The method and the system for optimizing the scheduling of the assembly type building components have the advantages that: according to the scheduling optimization method and system for the assembly type building components, provided by the structure, different parameters are selected according to different optimization targets to make a scheduling plan, a user is allowed to define parameter values, and the flexibility of a scheduling system is enhanced; the problem that the emergency order cannot be inserted is solved, the production time of each order is fundamentally shortened, and sufficient time is reserved to accept the insertion of the emergency order; the production line cost is reduced, and a reasonable production line screening rule is adopted to screen the minimum number of production lines under the condition of meeting the user requirements; maximizing the production capacity of the production line on the premise of minimizing the production time of the production line; the mold cost is reduced, and the minimum mold sleeve number of each mold model is solved based on linear programming and nonlinear programming.
Drawings
FIG. 1 is a flow chart of the steps of the present invention;
FIG. 2 is a schematic diagram of a component scheduling optimization objective.
Detailed Description
The present invention is described in detail below with reference to specific embodiments, and in the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed as broadly as the present invention is capable of modification in various respects, all without departing from the spirit and scope of the present invention.
As shown in fig. 1 and 2, the method for optimizing the scheduling of the prefabricated building components is mainly used for registering and managing information of components which need to be scheduled daily by enterprises, and specifying the number of the components which need to be scheduled daily; the component scheduling problem of enterprises is solved by taking the shortest delivery time and the best mold cost as the optimization target.
A production scheduling optimization method for an assembly type building component comprises the following steps S100 to S300:
s100: on the premise of balancing the production time of each production line, solving the number of components to be distributed of each component type in each production line based on linear programming to obtain a component set of each production line, and specifically comprising the following steps of S101 to S104:
s101: determining a production line set and types of components which can be produced on each production line in the production line set;
s102: determining the production time of each component type on each production line in the production line set;
s103: determining the number of components of each component type in the order;
s104: linear programming is adopted for the production line to solve the number of the components to be distributed for each component type of each production line.
Wherein the linear program is expressed as follows:
Figure BDA0002958648340000061
Figure BDA0002958648340000071
where i represents the number of lines in the plant, j represents the component type in the order, min z represents the minimum of solving the objective function z, maxtDenotes maximum production time, mintDenotes minimum production time, CjTotal number of members, X, representing type j of memberijNumber of components, T, representing type j of components to be separated in line iijIndicating the production time for production line i to produce component type j.
The linear programming expression represents: on the premise of balancing the production time of each production line, the number of components to be produced by each component type of each production line is determined, the production time of each production line is limited between the maximum value and the minimum value, and the difference between the maximum value and the minimum value is minimized so as to achieve the purpose of balancing the production time of the production lines.
S200: aiming at the shortest delivery time, solving the component production sequence of the component set of each production line based on a greedy-genetic algorithm to obtain the optimal component production sequence with the shortest production time of each production line, and realizing the optimization of component production sequence;
in order to receive the emergency order of the enterprise in time, considering starting from shortening the production time of each order, according to the steps S100 to S200, the shortest delivery time is taken as the target, all production lines of a workshop are oriented, components are allocated to the production lines based on linear programming, the component production sequence is solved according to the component set allocated to each production line based on the greedy-genetic algorithm, and the optimal component production sequence is obtained, wherein the optimal component production sequence is the component production sequence which enables the production time of the production line to be shortest.
S300: with the optimal mold cost as a target, solving the minimum number of mold sleeves of each mold type in the component set of each production line based on nonlinear programming to obtain the number of mold sleeves on each production line, and implementing optimization of component scheduling, specifically, the method may include steps S301 to S304:
s301: determining a production line set and determining the price of each mould type;
s302: determining a production line set with selectable models of all molds and the maximum station time of all production lines in the selectable production line set;
s303: determining the number of components required to be produced by each mould type;
s304: and solving the minimum number of the die sets of each die type on each production line in the production line set based on nonlinear programming.
The expression of the non-linear programming is as follows:
Figure BDA0002958648340000081
where min z represents the minimum value for solving the objective function z, DHB00iIndicates the mold type, PiIndicating the mold model DHB00iPrice of (X)iIndicating the mold model DHB00iNumber of die sets, TDHB00iIndicating the mold model DHB00iProduction time of the corresponding component type in the corresponding production line, MSTiIndicating the mold model DHB00iMaximum station time of the corresponding component type in the corresponding production line, CiIndicating the mold model DHB00iThe number of the components to be produced on the corresponding production line according to the corresponding component type, M represents the production time, N represents the moldThe upper limit of the number of sets.
The nonlinear programming expression represents: and solving the minimum number of mould sleeves of each mould model by adopting nonlinear programming aiming at each production line by taking the minimum mould cost as an objective function.
Therefore, steps S100 and S300 are based on the premise of balancing the production time of each production line, solving the number of components to be distributed for each component type of each production line based on linear programming to balance the production time of the production line, specifically distributing the components to the production lines according to the number of the distributed components, and solving the minimum number of mold sleeves for each mold type of each production line based on nonlinear programming to reduce the mold cost.
Therefore, according to steps S100 to S300, the optimization of component scheduling aiming at the shortest lead time, the largest production capacity of the production line, or the optimal mold cost can be achieved.
In step S200: aiming at the shortest delivery time, solving the component production sequence of the component set of each production line based on a greedy-genetic algorithm to obtain the optimal component production scheduling sequence with the shortest production time of each production line, and realizing the optimization of component production scheduling, the method specifically comprises the following steps of S201 to S208:
s201: determining a production line set, solving each production line component set based on linear programming, and randomly selecting one production line in the production line set;
s202: determining a set of components assigned to the selected production line based on the selected production line;
s203: initializing a group of component sequences of the determined component set based on a random algorithm to serve as parent sequences;
s204: generating a plurality of descendant sequences from the parent sequence according to a certain rule;
the rules are generated as follows: the offspring sequence is obtained by exchanging two random building blocks in the parent sequence, namely: the first and second building blocks are swapped to form a progeny sequence, the first and third building blocks are swapped to form a progeny sequence … …, the second and third building blocks are swapped, and the second and fourth building blocks are swapped … ….
For example, a component set on the current production line includes component a, component B, and component C, and the sequence of components of ABC may be used as a parent sequence, and a child sequence of the sequence of components of ACB, BAC, and CBA may be generated according to the above rules.
S205: respectively calculating the production time of the parent sequence and the production time of all the offspring sequences, if the production time of all the offspring sequences is more than or equal to the production time of the parent sequence, executing the step S206, and if the production time of the offspring sequences is less than that of the parent sequence, executing the step S207;
s206: outputting the parent sequence as an optimal component scheduling sequence;
s207: respectively taking the child sequences with the production time less than that of the parent sequences as new parent sequences, and executing the steps S204 to S206;
s208: and continuing to select the next production line from the production line set in the step S201, and repeating the steps S202 to S207 until all the production lines in the production line set are traversed to finish, so as to obtain the optimal component production sequence of each production line.
Through steps S201 to S208, the optimal component scheduling order on each production line is obtained on the premise that the lead time is shortest, and component scheduling optimization is achieved.
In step S100: on the premise of balancing the production time of each production line, solving the number of components to be divided of each component type in each production line based on linear programming, and screening out a better production line set by taking the minimum number of production lines as a target before obtaining the component set of each production line, wherein the specific screening process is as follows:
s011: initializing a selected production line set as an empty set, analyzing all component types contained in a component set to be scheduled in an order, and randomly selecting a certain component type from the component sets as a current component type;
for example, the selected production line set { }, the component set to be scheduled in the order includes two component types, namely, a laminated slab and a stair.
S012: determining an optional production line set according to the current component type, judging whether a production line capable of producing the component type exists in the selected production line set, if so, entering step S013, and if not, entering step S014;
for example: when the component type is the superimposed sheet, suppose that the selectable production line set of the superimposed sheet is {1#, 2# }, and the efficiency of producing the superimposed sheet by the 1# production line is higher, the specific screening judgment process is as follows:
if no production line in the selected production line set can produce the laminated slab, determining that the production line set which can be selected for the laminated slab is {1#, 2# }, and if the production efficiency on the 1# production line is higher, determining that the production line set which can be selected for the laminated slab is {1# }, and finishing screening; if the selected production line set comprises production lines capable of producing the laminated plates, the screening is immediately finished.
S013: when the current component type screening is finished, keeping the selected production line set unchanged, and entering step S015;
s014: determining an optional production line set of the current component type, adding a production line with high production efficiency for producing the current component type in the optional production line set into the selected production line set, and entering step S015;
s015: and continuously traversing the remaining component types in the component set to be scheduled, and repeating the steps S012 to S014 until all the component types are traversed.
Therefore, by steps S011 to S015, line screening aimed at minimizing the number of lines is realized.
The following specific scheduling mode of the component is aimed at the shortest delivery time, the minimum production line quantity or the optimal mould cost:
in the present embodiment, with the shortest lead time as the optimization target, a method for optimizing the schedule of prefabricated building elements includes steps S11 to S12:
s11: on the premise of balancing the production time of each production line, solving the number of the components to be divided of each component type in each production line based on linear programming to obtain a component set of each production line;
please refer to step S100 for the detailed step of step S11.
S12: and aiming at the shortest delivery time, solving the component production sequence of the component set of each production line based on a greedy-genetic algorithm to obtain the optimal component production sequence with the shortest production time of each production line, and realizing the optimization of component production sequence.
Please refer to step S200 for the detailed step of step S12.
In the present embodiment, the maximum capacity of the production line is taken as the optimization target, and the specific component scheduling process refers to the scheduling optimization method with the shortest lead time (steps S11 to S12), because the production line capacity can reach the maximum in principle with the shortest lead time.
In the present embodiment, with the goal of minimizing the number of production lines, a method for optimizing the production schedule of prefabricated building elements includes steps S21 to S23:
s21: based on the aim of minimum production line number, screening a better production line set;
step S21 specifically includes steps S011 to S015, and realizes the production line screening with the goal of minimizing the number of production lines.
S22: on the premise of balancing the production time of each production line, solving the number of the components to be divided of each component type in each production line based on linear programming to obtain a component set of each production line;
please refer to step S100 for the detailed step of step S22.
S23: and aiming at the shortest delivery time, solving the component production sequence of the component set of each production line based on a greedy-genetic algorithm to obtain the optimal component production sequence with the shortest production time of each production line, and realizing the optimization of component production sequence.
Please refer to step S200 for the detailed step of step S23.
In order to reduce the production line cost and reduce the production line quantity to reduce the water cost, the labor cost and the like, according to the user requirements, through the steps S21 to S23, a reasonable production line screening rule is adopted to screen out a better production line set, components are allocated to the production lines in a linear programming mode, an optimal component scheduling sequence is solved for the component set allocated to each production line based on a greedy-genetic algorithm, and the optimal component scheduling sequence, namely the component production sequence, enables the production time of the production line to be shortest.
(IV) in the present embodiment, with the optimization goal of the mold cost optimization, a method for optimizing the schedule of prefabricated building elements comprises the steps S31 to S32:
s31: on the premise of balancing the production time of each production line, solving the number of the components to be divided of each component type in each production line based on linear programming to obtain a component set of each production line;
please refer to step S100 for the detailed step of step S31.
S32: and solving the minimum number of the mold sleeves of each mold type in the component set of each production line based on nonlinear programming to obtain the number of the mold sleeves on each production line with the optimal mold cost as the target, thereby realizing the optimization of component scheduling.
Please refer to step S300 for the detailed step of step S32.
At present, the universality of the mold among projects is poor, the life cycle of the mold only runs through the beginning to the end of a certain project, and the cost difference between business and business is large, so that the reduction of the mold cost becomes one of the concerns of enterprises. Therefore, steps S31 to S32 are based on balancing the production time of each production line, solving the number of components to be distributed for each component type of each production line based on linear programming to balance the production time of the production line, specifically distributing the components to the production line according to the number of the distributed components, and solving the minimum number of mold sets for each mold type of each production line based on nonlinear programming to reduce the mold cost.
A system for scheduling production optimization for prefabricated building components, comprising: the distribution module, the component scheduling order calculation module and the mold set number calculation module;
the distribution module is used for solving the number of the components to be distributed of each component type in each production line based on linear programming on the premise of balancing the production time of each production line to obtain a component set of each production line;
the component scheduling sequence calculation module is used for solving a component production sequence of the component set of each production line based on a greedy-genetic algorithm by taking the shortest delivery time as a target to obtain the optimal component scheduling sequence of each production line with the shortest production time, so as to realize component scheduling optimization;
the mold sleeve number calculation module is used for solving the minimum mold sleeve number of each mold type in the component set of each production line based on nonlinear programming by taking the optimal mold cost as a target to obtain the mold sleeve number on each production line, so that the optimization of component scheduling is realized.
A computer readable storage medium having stored thereon a number of acquisition and classification procedures for being invoked by a processor and performing the method of set-up building element schedule optimization of claim 1.
In this embodiment, (1) by clicking the interface, the following parameters are set, and the user is allowed to define the parameter values, so as to implement the optimization of component scheduling with the shortest delivery time as the optimization target, and the settable parameters include: the number of moulds in the mould table, a component placing algorithm, a component sequence algorithm, a production line and a production scheduling number; (2) setting the following parameters through clicking an interface, allowing a user to define the parameter values, and realizing the optimization of component scheduling with the maximum production capacity of the production line as an optimization target, wherein the settable parameters comprise: the number of moulds in the mould table, the working time and the production line; (3) through clicking the interface, set up following parameter, allow the user-defined parameter value to realize with the minimum component scheduling optimization of optimizing the target of production line quantity, can set up the parameter and have: the number of moulds in the mould table, a component placing algorithm, a component order algorithm and a production scheduling number; (4) through clicking the interface, set up following parameter, allow the user-defined parameter value to realize with the optimal component scheduling optimization of optimizing the goal of mould cost, can set up the parameter and have: the number of the moulds in the mould table, the working time, the production line and the mould list number. From the multi-target multi-constraint angle, a user self-defines parameter values and generates various scheduling results by one key, so that the flexibility and diversity of the scheduling system are enhanced.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.

Claims (10)

1. A method for optimizing the scheduling of prefabricated building elements, comprising:
on the premise of balancing the production time of each production line, solving the number of the components to be divided of each component type in each production line based on linear programming to obtain a component set of each production line;
aiming at the shortest delivery time, solving the component production sequence of the component set of each production line based on a greedy-genetic algorithm to obtain the optimal component production sequence with the shortest production time of each production line, and realizing the optimization of component production sequence;
and with the optimal mold cost as a target, solving the minimum mold sleeve number of each mold type in the component set of each production line based on nonlinear programming to obtain the mold sleeve number on each production line, and realizing the optimization of component scheduling.
2. The assembly type building component scheduling optimization method according to claim 1, wherein before the number of components to be classified of each component type in each production line is solved based on linear programming on the premise of balancing the production time of each production line, and a component set of each production line is obtained, a preferred production line set is screened out with the aim of minimizing the number of production lines, and the specific screening process is as follows:
s011: initializing a selected production line set as an empty set, analyzing all component types contained in a component set to be scheduled in an order, and randomly selecting a certain component type from the component sets as a current component type;
s012: determining an optional production line set according to the current component type, judging whether a production line capable of producing the component type exists in the selected production line set, if so, entering step S013, and if not, entering step S014;
s013: when the current component type screening is finished, keeping the selected production line set unchanged, and entering step S015;
s014: determining an optional production line set of the current component type, adding a production line with high production efficiency for producing the current component type in the optional production line set into the selected production line set, and entering step S015;
s015: and continuously traversing the remaining component types in the component set to be scheduled, and repeating the steps S012 to S014 until all the component types are traversed.
3. The assembly type building component scheduling optimization method according to claim 1, wherein the step of solving the number of the components corresponding to each component type in each production line based on linear programming to obtain the component set of each production line on the premise of balancing the production time of each production line comprises the following steps:
s101: determining a production line set and types of components which can be produced on each production line in the production line set;
s102: determining the production time of each component type produced by each production line in the production line set;
s103: determining the number of components of each component type in the order;
s104: linear programming is adopted for the production line to solve the number of the components to be distributed for each component type of each production line.
4. A method of scheduling optimisation of an assembled building element according to claim 3 wherein the linear program is expressed as follows:
Figure FDA0002958648330000021
where i represents the number of lines in the plant, j represents the component type in the order, min z represents the minimum of solving the objective function z, maxtDenotes maximum production time, mintDenotes minimum production time, CjTotal number of members, X, representing type j of memberijNumber of components, T, representing type j of components to be separated in line iijIndicating the production time for production line i to produce component type j.
5. The assembly type building component scheduling optimization method according to any one of claims 1 to 4, wherein the optimization of component scheduling is realized by solving the component production sequence of the component set of each production line based on a greedy-genetic algorithm with the goal of shortest delivery time to obtain the optimal component scheduling sequence with the shortest production time of each production line, and the method comprises the following steps:
s201: determining a production line set, solving each production line component set based on linear programming, and randomly selecting one production line in the production line set;
s202: determining a set of components assigned to the selected production line based on the selected production line;
s203: initializing a group of component sequences of the determined component set based on a random algorithm to serve as parent sequences;
s204: generating a plurality of descendant sequences from the parent sequence according to a certain rule;
s205: respectively calculating the production time of the parent sequence and the production time of all the offspring sequences, if the production time of all the offspring sequences is more than or equal to the production time of the parent sequence, executing the step S206, and if the production time of the offspring sequences is less than that of the parent sequence, executing the step S207;
s206: outputting the parent sequence as an optimal component scheduling sequence;
s207: respectively taking the child sequences with the production time less than that of the parent sequences as new parent sequences, and executing the steps S204 to S206;
s208: and continuing to select the next production line from the production line set in the step S201, and repeating the steps S202 to S207 until all the production lines in the production line set are traversed to finish, so as to obtain the optimal component production sequence of each production line.
6. The assembly type building element scheduling optimization method according to claim 5, wherein in step S204: generating a plurality of descendant sequences from the parent sequence according to a certain rule, and generating the rule as follows: the offspring sequences are exchanged by two random building blocks in the parent sequence.
7. The assembly type building component scheduling optimization method according to any one of claims 1 to 4, wherein the method for achieving component scheduling optimization by solving the minimum number of mold sets of each mold type in the component set of each production line based on nonlinear programming with the goal of mold cost optimization comprises the following steps:
s301: determining a production line set and determining the price of each mould type;
s302: determining a production line set with selectable models of all molds and the maximum station time of all production lines in the selectable production line set;
s303: determining the number of components required to be produced by each mould type;
s304: and solving the minimum number of the die sets of each die type on each production line in the production line set based on nonlinear programming.
8. A method of scheduling optimisation of an assembled building element according to claim 7 wherein the non-linear program is expressed as follows:
Figure FDA0002958648330000041
where min z represents the minimum value for solving the objective function z, DHB00iIndicates the mold type, PiIndicating the mold model DHB00iPrice of (X)iIndicating the mold model DHB00iNumber of die sets, TDHB00iIndicating the mold model DHB00iProduction time of the corresponding component type in the corresponding production line, MSTiIndicating the mold model DHB00iMaximum station time of the corresponding component type in the corresponding production line, CiIndicating the mold model DHB00iThe number of the components of the corresponding component type to be produced on the corresponding production line, M represents the production time, and N represents the upper limit of the number of the die sets.
9. A system for optimizing the scheduling of prefabricated building components, comprising: the distribution module, the component scheduling order calculation module and the mold set number calculation module;
the distribution module is used for solving the number of the components to be distributed in each component type of each production line based on linear programming on the premise of balancing the production time of each production line to obtain a component set of each production line;
the component scheduling sequence calculation module is used for solving a component production sequence of the component set of each production line based on a greedy-genetic algorithm by taking the shortest delivery time as a target to obtain the optimal component scheduling sequence of each production line with the shortest production time, so as to realize component scheduling optimization;
the mold sleeve number calculation module is used for solving the minimum mold sleeve number of each mold type in the component set of each production line based on nonlinear programming by taking the optimal mold cost as a target to obtain the mold sleeve number on each production line, so that the optimization of component scheduling is realized.
10. A computer-readable storage medium having stored thereon a number of acquisition and classification procedures for being invoked by a processor and performing the method of optimizing the schedule of prefabricated building components of claim 1.
CN202110229789.8A 2021-03-02 2021-03-02 Assembly type building component scheduling optimization method and system Active CN112801414B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110229789.8A CN112801414B (en) 2021-03-02 2021-03-02 Assembly type building component scheduling optimization method and system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110229789.8A CN112801414B (en) 2021-03-02 2021-03-02 Assembly type building component scheduling optimization method and system

Publications (2)

Publication Number Publication Date
CN112801414A true CN112801414A (en) 2021-05-14
CN112801414B CN112801414B (en) 2023-03-10

Family

ID=75816280

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110229789.8A Active CN112801414B (en) 2021-03-02 2021-03-02 Assembly type building component scheduling optimization method and system

Country Status (1)

Country Link
CN (1) CN112801414B (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113421019A (en) * 2021-07-13 2021-09-21 安徽大学绿色产业创新研究院 Method for optimizing scheduling of internal transportation cost of fabricated building
CN113433915A (en) * 2021-07-08 2021-09-24 南京航空航天大学苏州研究院 Automatic scheduling algorithm for workshop sheet metal machining
CN113723325A (en) * 2021-09-03 2021-11-30 安徽大学绿色产业创新研究院 Tool defect detection system for prefabricated parts
CN115600774A (en) * 2022-12-14 2023-01-13 安徽大学绿色产业创新研究院（Cn） Multi-target production scheduling optimization method for assembly type building component production line

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180357584A1 (en) * 2017-06-12 2018-12-13 Hefei University Of Technology Method and system for collaborative scheduling of production and transportation in supply chains based on improved particle swarm optimization
CN110378528A (en) * 2019-07-17 2019-10-25 南京大学 Workshop scheduled production method and system based on genetic algorithm
CN111208796A (en) * 2020-04-21 2020-05-29 天津开发区精诺瀚海数据科技有限公司 Workshop production operation scheduling method based on clustering niche genetic algorithm

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180357584A1 (en) * 2017-06-12 2018-12-13 Hefei University Of Technology Method and system for collaborative scheduling of production and transportation in supply chains based on improved particle swarm optimization
CN110378528A (en) * 2019-07-17 2019-10-25 南京大学 Workshop scheduled production method and system based on genetic algorithm
CN111208796A (en) * 2020-04-21 2020-05-29 天津开发区精诺瀚海数据科技有限公司 Workshop production operation scheduling method based on clustering niche genetic algorithm

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
ZONGYUE WANG，AND ETC: "A Linear Genetic Programming with Reusable Gene", 《2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION WORKSHOPS》 *
任工昌等: "装配生产线建模方法及资源优化研究", 《陕西科技大学学报》 *

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113433915A (en) * 2021-07-08 2021-09-24 南京航空航天大学苏州研究院 Automatic scheduling algorithm for workshop sheet metal machining
CN113421019A (en) * 2021-07-13 2021-09-21 安徽大学绿色产业创新研究院 Method for optimizing scheduling of internal transportation cost of fabricated building
CN113723325A (en) * 2021-09-03 2021-11-30 安徽大学绿色产业创新研究院 Tool defect detection system for prefabricated parts
CN113723325B (en) * 2021-09-03 2023-08-22 安徽大学绿色产业创新研究院 Frock defect detecting system of prefabricated component of assembled
CN115600774A (en) * 2022-12-14 2023-01-13 安徽大学绿色产业创新研究院（Cn） Multi-target production scheduling optimization method for assembly type building component production line
CN115600774B (en) * 2022-12-14 2023-03-10 安徽大学绿色产业创新研究院 Multi-target production scheduling optimization method for assembly type building component production line

Also Published As

Publication number Publication date
CN112801414B (en) 2023-03-10

Similar Documents

Publication Publication Date Title
CN112801414B (en) Assembly type building component scheduling optimization method and system
CN109636011B (en) Multi-shift planning and scheduling method based on improved variable neighborhood genetic algorithm
CN115600774B (en) Multi-target production scheduling optimization method for assembly type building component production line
CN105629927A (en) Hybrid genetic algorithm-based MES (Manufacturing Execution System) production planning and scheduling method
CN101834786B (en) Queue scheduling method and device
CN111047272B (en) Project scheduling method and device for multi-language collaborative development
CN109886468A (en) Charging station planing method based on improved self-adapted genetic algorithm
CN111401616A (en) Double-layer scheduling method for precast concrete component in supply chain environment
CN115271130B (en) Dynamic scheduling method and system for maintenance order of ship main power equipment
CN116663861B (en) Scheduling optimization method combining production robustness of assembly type component and resource balance
CN118194733B (en) Intelligent typesetting double-objective optimization method for assembled building component mold
CN114511272A (en) Solving algorithm for optimizing unmanned aerial vehicle distribution network for city instant distribution
CN109784570A (en) Wisdom workshop flexible production dispatching method based on information physical emerging system
CN111026534B (en) Workflow execution optimization method based on multiple group genetic algorithms in cloud computing environment
CN111553610B (en) Scheduling method and system based on learning-forgetting effect
CN115983733B (en) Electric power market clear data processing method and device based on water level control
CN103714226A (en) Automatic generating method and automatic generating device for optimized orderly-power-consumption scheme
Hwang et al. CSO and PSO to solve optimal contract capacity for high tension customers
CN103150685B (en) A kind of intelligence Maintenance Schedule Optimization workout system
CN111199311B (en) Residential area charging facility power optimization method
CN108133281A (en) An Optimization Method for Location-Selection is paid in the electricity charge based on improved nearest neighbor classifier propagation algorithm
CN108985604B (en) Construction period compression method for construction planning
CN117035703B (en) Cloud manufacturing-oriented inter-enterprise collaborative scheduling optimization method, system and equipment
CN110659034A (en) Combined optimization deployment method, system and storage medium of cloud-edge hybrid computing service
CN115685920B (en) Casting mixed flow shop scheduling method and system based on improved cuckoo algorithm

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant