CN109213094A - A kind of Optimization Scheduling based on multiplexing inter-plant steel smelting-continuous casting production steel billet process - Google Patents
A kind of Optimization Scheduling based on multiplexing inter-plant steel smelting-continuous casting production steel billet process Download PDFInfo
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- CN109213094A CN109213094A CN201810825272.3A CN201810825272A CN109213094A CN 109213094 A CN109213094 A CN 109213094A CN 201810825272 A CN201810825272 A CN 201810825272A CN 109213094 A CN109213094 A CN 109213094A
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- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 143
- 239000010959 steel Substances 0.000 title claims abstract description 143
- 238000000034 method Methods 0.000 title claims abstract description 50
- 238000005457 optimization Methods 0.000 title claims abstract description 40
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 32
- 238000009749 continuous casting Methods 0.000 title claims abstract description 23
- 241000255581 Drosophila <fruit fly, genus> Species 0.000 claims abstract description 40
- 238000009628 steelmaking Methods 0.000 claims abstract description 5
- 238000012545 processing Methods 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000003754 machining Methods 0.000 claims description 3
- 238000013507 mapping Methods 0.000 claims description 3
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 claims description 3
- 238000005272 metallurgy Methods 0.000 abstract description 2
- 239000002699 waste material Substances 0.000 abstract description 2
- 238000003723 Smelting Methods 0.000 description 4
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 238000010923 batch production Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000007670 refining Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 description 1
- 239000010931 gold Substances 0.000 description 1
- 229910052737 gold Inorganic materials 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
- 238000011160 research Methods 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32252—Scheduling production, machining, job shop
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The present invention relates to a kind of Optimization Schedulings based on multiplexing inter-plant steel smelting-continuous casting production steel billet process, belong to metallurgy manufacture production process intelligent optimization dispatching technique field.The present invention is by determining that different steel billets optimize target in the scheduling model and optimization aim of multiple steel mills one continuous casting steel billet process of steel-making, and using the Optimization Scheduling of mixing drosophila optimization algorithm；Wherein, scheduling model is established according to process time of the different steel billets on different steel mill's machines, and the target of optimization is minimizes Maximal Makespan.The present invention can find the production decision of each factory in a relatively short period of time, avoid the waste of each factory resources, minimize the Maximal Makespan C of each factorymax(π) improves the production efficiency of factory so as to reduce the production cost of factory.
Description
Technical field
The present invention relates to a kind of Optimization Schedulings based on multiplexing inter-plant steel smelting-continuous casting production steel billet process, belong to smelting
Gold manufacture production process intelligent optimization dispatching technique field.
Background technique
Increasingly fierce with market competition with advances in technology, steel and iron industry is towards efficient, inexpensive and steady production
Direction develop.It is modernization steel production pipe that production scheduling plays key player in the efficient stable production process of steel mill
The core function of reason system.A continuous casting section is made steel to occupy an important position in steel manufacture process.The mesh of bloom production scheduling
Mark is exactly to make full use of existing device resource by designing reasonable production scheduling plan, reduces the process waiting time and disappears
Except the operation conflict of production process, to realize that conticaster most Dalian pours to obtain maximum economic benefit.
It mainly includes smelting, second metallurgy refining and continuous casting three process that steel mill, which makes steel a continuous casting steel billet process,.It is raw
Producing steel grade mainly has conventional steel and variety steel, therefore needs when producing different steel grades using different refining equipments, so that
Steel mill has a plurality of process route.In addition, corresponding tundish institute is fertile most when different conticasters produces different steel grades
Big heat number is not also identical, therefore special steel plant makes steel a continuous casting steel billet process with equipment is more, mode is more, more than route
Feature causes scheduling process restriction condition numerous.NP is belonged to for the scheduling problem of multiple steel mill's steel-smelting continuous casting production processes
Problem solves difficulty and is exponentially increased with the increase of problem scale, therefore all has very in theoretical research and practical application
High researching value.
Steel billet is processed based on batch production mode.The steel billet requirements for the production process of different size is different, and each
The working ability that steel mill makes steel machine is different, so that different steel mills make steel the processing in each stage during a continuous casting steel billet
Time is different.Thus, steel billet processing sequence can cause large effect to the total complete time of batch production steel billet.It is reasonable to add
Work sequence and allocation plan can allow the resource of different steel mills to be realized rationally and utilize.Finally, shorten its total production time, into
And the maximization of multiple steel steel-smelting continuous casting production steel billet benefits may be implemented.
The present invention establishes order models in the actual production process that multiple steel mills make steel a continuous casting steel billet according to steel billet,
And design a kind of mixing drosophila optimization algorithm.The algorithm can obtain multiple steel mills within a short period of time and make steel a continuous casting steel
The scheduling scheme of base, and acquire the approximate optimal solution of the scheduling problem.To make steel a continuous casting steel billet for multiple steel mills and mention
It is instructed for actual scheme, reduces production cost and finally improve the economic benefit of multiple steel mills.
Summary of the invention
The purpose of the present invention is making steel a continuous casting steel billet process scheduling problem for multiple steel mills, a kind of mixing is proposed
The Optimization Scheduling of drosophila optimization algorithm, to realize the reasonable utilization of multiple steel mills steel-making resources, save its production cost into
And improve productivity effect.
The technical scheme is that a kind of Optimized Operation side based on multiplexing inter-plant steel smelting-continuous casting production steel billet process
Method is made steel the scheduling model and optimization aim of a continuous casting steel billet process in multiple steel mills by the different steel billets of determination, and is adopted
Target is optimized with the Optimization Scheduling of mixing drosophila optimization algorithm；Wherein, scheduling model is according to different steel billets not
It is established with the process time on steel mill's machine, the target of optimization is minimizes Maximal Makespan Cmax(π)
K=1,2, F, i=1,2, nk, j=1,2, m
In formula, F indicates F steel-making factory, and k indicates some specific factory, and n indicates the steel billet for needing to complete the process
Sum, nkIndicate the steel billet for needing to be completely processed in factory k sum, i expression is completely processed steel billet position in the ranking, j
Indicate that a certain machine in factory, m indicate number of machines total in each factory；π=π (1), π (2), π (n) } it indicates
It is completely processed steel billet always to sort, π (n) is the steel billet for needing to complete the process in nth position in total sequence, is completely processed steel
Base always sort π generated after factory's allocation rule be completely processed in each factory steel billet sequence πk, πk(i) it indicates in factory k
In be completely processed in steel billet sequence and be completely processed steel billet, π on i-th of positionk={ πk(1),πk(2),···,πk(nk)}
Indicate the sequence that steel billet is completely processed in factory k；Expression is completely processed steel billet π in factory kk(i) in machine j
On start process the moment,Expression is completely processed steel billet π in factory kk(i) process time on machine j is simultaneously
And it is greater than 0,Expression is completely processed steel billet π in factory kk(i) process time on machine j,Table
Show that factory k is all on machine m and is completely processed steel billet πk(nk) total machining the time；
The Optimization Scheduling of the mixing drosophila optimization algorithm specifically:
Step1, initialization: population scale popsize, maximum number of iterations maxgen, drosophila group position range are set
The single flight range FR ∈ [- 5,5] of LR ∈ [0,5] and drosophila, random initializtion drosophila position (xa,ya)
xa=rand (LR)
ya=rand (LR)
Step2, smell and visual search: drosophila individual is the update of algorithm using the process of smell and vision search of food
Process assigns the distance FR ∈ [- 5,5] of drosophila individual single flight, then the location update formula of drosophila individual i is as follows:
xi=xa+rand(FR)
yi=ya+rand(FR)
Since mixing drosophila optimization algorithm is to be based on continuous real number field, and steel billet to be processed is assigned to different steel mills processing
Scheduling process belong to discrete optimization, therefore established between drosophila position and steel billet to be processed sequence one by one using LOV rule
Mapping relations, and then realize the conversion from real coding to steel billet to be processed sequence discrete codes, by drosophila in continuous real number
The transformation of domain position finds optimal sequencing by constantly searching for update, in turn to change the steel billet sequence being completely processed
Minimizes Maximal Makespan Cmax(π)；
Step3, the local search based on Insert: carrying out Insert to the optimal drosophila individual in population, if part
It searches for obtained individual then to be replaced better than current individual, and is remained into population；Otherwise, retain current individual not
Become；
Step4, termination condition: termination condition is set as maximum number of iterations max gen, then exports " optimum individual "；It is no
Step Step2 is then gone to, is iterated, until meeting termination condition.
The beneficial effects of the present invention are: the present invention proposes a kind of to make steel a continuous casting steel billet process based on multiple steel mills
Scheduling model and optimization aim, and updated by the iteration of mixing drosophila optimization algorithm and the steel billet sequence being completely processed is carried out
Optimization, finally, can find the production decision of each factory in a relatively short period of time, avoid the waste of each factory resources, minimum
Change the Maximal Makespan C of each factorymax(π) improves the production efficiency of factory so as to reduce the production cost of factory.
Detailed description of the invention
Fig. 1 is whole design flow chart of the invention；
Fig. 2 is total algorithm flow chart of the invention；
Fig. 3 is that the basic field " Insert " of the invention changes schematic diagram；
Specific embodiment
Embodiment 1: as shown in Figure 1-3, a kind of Optimized Operation side based on multiplexing inter-plant steel smelting-continuous casting production steel billet process
Method is made steel the scheduling model and optimization aim of a continuous casting steel billet process in multiple steel mills by the different steel billets of determination, and is adopted
Target is optimized with the Optimization Scheduling of mixing drosophila optimization algorithm；Wherein, scheduling model is according to different steel billets not
It is established with the process time on steel mill's machine, the target of optimization is minimizes Maximal Makespan Cmax(π)
K=1,2, F, i=1,2, nk, j=1,2, m
In formula, F indicates F steel-making factory, and k indicates some specific factory, and n indicates the steel billet for needing to complete the process
Sum, nkIndicate the steel billet for needing to be completely processed in factory k sum, i expression is completely processed steel billet position in the ranking, j
Indicate that a certain machine in factory, m indicate number of machines total in each factory；π=π (1), π (2), π (n) } it indicates
It is completely processed steel billet always to sort, π (n) is the steel billet for needing to complete the process in nth position in total sequence, is completely processed steel
Base always sort π generated after factory's allocation rule be completely processed in each factory steel billet sequence πk, πk(i) it indicates in factory k
In be completely processed in steel billet sequence and be completely processed steel billet, π on i-th of positionk={ πk(1),πk(2),···,πk(nk)}
Indicate the sequence that steel billet is completely processed in factory k；Expression is completely processed steel billet π in factory kk(i) in machine j
On start process the moment,Expression is completely processed steel billet π in factory kk(i) process time on machine j is simultaneously
And it is greater than 0,Expression is completely processed steel billet π in factory kk(i) process time on machine j,Table
Show that factory k is all on machine m and is completely processed steel billet πk(nk) total machining the time；
The Optimization Scheduling of the mixing drosophila optimization algorithm specifically:
Step1, initialization: population scale popsize, maximum number of iterations maxgen, drosophila group position range are set
The single flight range FR ∈ [- 5,5] of LR ∈ [0,5] and drosophila, random initializtion drosophila position (xa,ya)
xa=rand (LR)
ya=rand (LR)
Step2, smell and visual search: drosophila individual is the update of algorithm using the process of smell and vision search of food
Process assigns the distance FR ∈ [- 5,5] of drosophila individual single flight, then the location update formula of drosophila individual i is as follows:
xi=xa+rand(FR)
yi=ya+rand(FR)
Since mixing drosophila optimization algorithm is to be based on continuous real number field, and steel billet to be processed is assigned to different steel mills processing
Scheduling process belong to discrete optimization, therefore established between drosophila position and steel billet to be processed sequence one by one using LOV rule
Mapping relations, and then realize the conversion from real coding to steel billet to be processed sequence discrete codes, by drosophila in continuous real number
The transformation of domain position finds optimal sequencing by constantly searching for update, in turn to change the steel billet sequence being completely processed
Minimizes Maximal Makespan Cmax(π)；
Step3, the local search based on Insert: carrying out Insert to the optimal drosophila individual in population, if part
It searches for obtained individual then to be replaced better than current individual, and is remained into population；Otherwise, retain current individual not
Become；
Step4, termination condition: termination condition is set as maximum number of iterations max gen, then exports " optimum individual "；It is no
Step Step2 is then gone to, is iterated, until meeting termination condition.
Above in conjunction with attached drawing, the embodiment of the present invention is explained in detail, but the present invention is not limited to above-mentioned
Embodiment within the knowledge of a person skilled in the art can also be before not departing from present inventive concept
Put that various changes can be made.
Claims (1)
1. a kind of Optimization Scheduling based on multiplexing inter-plant steel smelting-continuous casting production steel billet process, it is characterised in that: pass through determination
Different steel billets make steel the scheduling model and optimization aim of a continuous casting steel billet process in multiple steel mills, and excellent using mixing drosophila
The Optimization Scheduling for changing algorithm optimizes target；Wherein, scheduling model is according to different steel billets on different steel mill's machines
Process time establish, the target of optimization is minimizes Maximal Makespan Cmax(π)
K=1,2 ... F, i=1,2 ..., nk, j=1,2 ..., m
In formula, F indicates F steel-making factory, and k indicates some specific factory, and n indicates that the steel billet for needing to complete the process is total
Number, nkIndicate the steel billet for needing to be completely processed in factory k sum, i expression is completely processed steel billet position in the ranking, j table
Show that a certain machine in factory, m indicate number of machines total in each factory；π=π (1), π (2) ..., π (n) } indicate to be processed
It completes steel billet always to sort, π (n) is the steel billet for needing to complete the process in nth position in total sequence, is completely processed steel billet and always arranges
Sequence π is generated after factory's allocation rule is completely processed steel billet sequence π in each factoryk, πk(i) indicate to be added in factory k
Work is completed to be completely processed steel billet, π on i-th of position in steel billet sequencek={ πk(1),πk(2),…,πk(nk) indicate factory k
In be completely processed the sequence of steel billet；Expression is completely processed steel billet π in factory kk(i) beginning on machine j
The moment is processed,Expression is completely processed steel billet π in factory kk(i) process time on machine j and be greater than 0,Expression is completely processed steel billet π in factory kk(i) process time on machine j,Indicate that factory k exists
It is all on machine m to be completely processed steel billet πk(nk) total machining the time；
The Optimization Scheduling of the mixing drosophila optimization algorithm specifically:
Step1, initialization: setting population scale popsize, maximum number of iterations maxgen, drosophila group position range L R ∈
[0,5] and the single flight range FR ∈ [- 5,5] of drosophila, random initializtion drosophila position (xa,ya)
xa=rand (LR)
ya=rand (LR)
Step2, smell and visual search: drosophila individual is the updated of algorithm using the process of smell and vision search of food
Journey assigns the distance FR ∈ [- 5,5] of drosophila individual single flight, then the location update formula of drosophila individual i is as follows:
xi=xa+rand(FR)
yi=ya+rand(FR)
Since mixing drosophila optimization algorithm is to be based on continuous real number field, and steel billet to be processed is assigned to the tune of different steel mills processing
It spends journey and belongs to discrete optimization, therefore the mapping one by one between drosophila position and steel billet to be processed sequence is established using LOV rule
Relationship, and then realize the conversion from real coding to steel billet to be processed sequence discrete codes, by drosophila in continuous real number field position
The transformation set finds optimal sequencing by constantly searching for update, and then minimum to change the steel billet sequence being completely processed
Change Maximal Makespan Cmax(π)；
Step3, the local search based on Insert: Insert is carried out to the optimal drosophila individual in population, if local search
Obtained individual is then replaced better than current individual, and is remained into population；Otherwise, it is constant to retain current individual；
Step4, termination condition: termination condition is set as maximum number of iterations maxgen, then exports " optimum individual "；Otherwise it goes to
Step Step2, iterates, until meeting termination condition.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115345032A (en) * | 2022-10-17 | 2022-11-15 | 宁波钢铁有限公司 | Steelmaking-continuous casting tundish plan optimization method and device and electronic equipment |
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| CN107831740A (en) * | 2017-10-17 | 2018-03-23 | 昆明理工大学 | A kind of Optimization Scheduling during the distributed manufacturing applied to notebook part |
| CN108063452A (en) * | 2017-12-04 | 2018-05-22 | 广东电网有限责任公司电力科学研究院 | The optimal isolated island division methods of power distribution network based on adaptive chaos drosophila optimization algorithm |
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|---|---|---|---|---|
| US20120089970A1 (en) * | 2010-10-12 | 2012-04-12 | Cha Byung-Chang | Apparatus and method for controlling loop schedule of a parallel program |
| CN103941684A (en) * | 2014-04-10 | 2014-07-23 | 昆明理工大学 | Dispatching optimization method for electroless copper plating process of multiple layers of circuit boards |
| CN107094112A (en) * | 2017-03-31 | 2017-08-25 | 西南交通大学 | Bandwidth constraint multicast routing optimization method based on drosophila optimized algorithm |
| CN107831740A (en) * | 2017-10-17 | 2018-03-23 | 昆明理工大学 | A kind of Optimization Scheduling during the distributed manufacturing applied to notebook part |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115345032A (en) * | 2022-10-17 | 2022-11-15 | 宁波钢铁有限公司 | Steelmaking-continuous casting tundish plan optimization method and device and electronic equipment |
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