CN109358581A - The two different wide steel smelting-continuous casting process batches plan optimization methods of stream - Google Patents
The two different wide steel smelting-continuous casting process batches plan optimization methods of stream Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 66
- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 46
- 239000010959 steel Substances 0.000 title claims abstract description 46
- 230000008569 process Effects 0.000 title claims abstract description 33
- 238000009749 continuous casting Methods 0.000 title claims abstract description 26
- 238000005457 optimization Methods 0.000 title claims abstract description 25
- 238000002922 simulated annealing Methods 0.000 claims abstract description 32
- 238000004519 manufacturing process Methods 0.000 claims abstract description 24
- 230000008859 change Effects 0.000 claims abstract description 14
- 238000005266 casting Methods 0.000 claims description 20
- 239000000463 material Substances 0.000 claims description 13
- 230000007717 exclusion Effects 0.000 claims description 9
- 238000005098 hot rolling Methods 0.000 claims description 9
- 238000010079 rubber tapping Methods 0.000 claims description 7
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- 238000013461 design Methods 0.000 description 6
- 238000013178 mathematical model Methods 0.000 description 4
- 238000000137 annealing Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000007670 refining Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
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- 238000011161 development Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
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- 238000009628 steelmaking Methods 0.000 description 1
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The present invention provides one kind the two different wide steel smelting-continuous casting process batches plan optimization methods of stream, comprising the following steps: S1, the heat-for establishing Steelmaking-Continuous Casting Production Scheduling pour time batch plan model；S2, it is optimized using change neighborhood combination simulated annealing model described in step S1.The shortcomings that different wide steel smelting-continuous casting group furnace group of two stream of the present invention pours batch plan optimization method, and convenient and simple, calculating speed is fast, and multi items can not be solved by efficiently solving previous methods, more specifications, the slab input of small lot.
Description
Technical field
The present invention relates to production fields, and in particular to it is a kind of based on simulated annealing with become neighborhood search combine about two
Flow different wide steel smelting-continuous casting process batches plan optimization method.
Background technique
With the development of steel industry, iron and steel enterprise's order increasingly present multi items, small lot, customize the characteristics of.
In the case that the contract or slab negligible amounts and specification of input are numerous, existing batch plan optimization method is all
It is that two stream crystallizer width values in same heat are set as identical numerical value, in slab negligible amounts, width tomography between heat,
Calculating resulting remaining material rate or middle packet number leads to higher cost, makes a profit less, satisfactory effect can not often be discharged.
Summary of the invention
According to existing batch plan optimization method set forth above, lead to higher cost, makes a profit less, can not often be discharged
Satisfactory technical problem, and provide one kind the two different wide steel smelting-continuous casting process batches plan optimization methods of stream.Master of the present invention
Time batch plan model is poured using the heat-of Steelmaking-Continuous Casting Production Scheduling, devise the change neighborhood for solving the class model
(Variable Neighborhood Search, VNS) combines simulated annealing (Simulated Annealing, SA) algorithm, from
And play and efficiently solve previous methods and can not solve multi items, the shortcomings that more specifications, the slab input of small lot.
The technological means that the present invention uses is as follows:
A kind of different wide steel smelting-continuous casting process batches plan optimization method of two stream, comprising the following steps:
S1, the heat-for establishing Steelmaking-Continuous Casting Production Scheduling pour time batch plan model；S2, simulation is combined using change neighborhood
Annealing algorithm model described in step S1 optimizes.
Further, in step S1, half charging plan is firstly generated, and then generates the middle packet plan with steel grade, in
Between wrap plan, charging plan is determined with this, after determining charging plan, consider grade transition and hot rolling material constraint pours time meter
It draws, detailed process is as follows:
S11, data processing；
By work order according to unit, path, thickness are refined, tapping mark is divided into different group furnaceman's list mutually exclusive sets, is gathering
It is interior to arrange work order according to allowing to produce width descending, to make steel a group furnace；
S12, half heat process of group；
S121, first work order set for taking work order mutually exclusive sets carry out next step S122 for each work order；
S122, judge whether the work order set is empty, be that sky then deletes the work order set, then carries out step S121, otherwise
Carry out next step S123；
S123, a work order in work order set is taken, carries out next step S124；
S124, judge whether heat set is empty, be that sky then establishes one and half heat set, and generates a half new furnace
It is secondary；According to a group furnace rule, heat set is traversed, can judgement be added to the work order when first half heat, if can, by the work order
Be added to current heat, and deleted from work order set, if cannot if create half heat, half heat is added in work order, by this half
Heat set is added in heat, and the work order is deleted from work order set, then goes to step S125；
S125, judge whether work order mutually exclusive sets is sky, then go to step S13 for sky, otherwise go to step S121；
S13, the pre- intermediate packet procedures of group；
S131, first half heat for taking heat set carry out step S132 for first half heat；
S132, judge whether pre- tundish set is empty, be that sky then establishes a pre- tundish set, and generates one newly
Pre- tundish；According to pre- tundish rule is organized, pre- tundish set is traversed, can judgement be added to half heat in currently pre-
Between wrap, if can, which is added to current pre- tundish, and half heat is deleted from half heat set, if cannot if it is new
Pre- tundish is built, half heat is added to the pre- tundish, and delete half heat from heat set；Go to step S133；
S133, judge whether half heat set is sky, be idle running step S14, otherwise go to step S131；
S14, intermediate packet procedures are organized；
S141, according to unit, refine path, thickness, pre- tundish is divided into different groups and pours mutual exclusion set by tapping mark,
And pre- tundish is arranged according to half heat quantity descending in gathering；
S142, judge whether tundish set is sky, then establish a tundish set for sky, take in pre- tundish set
The pre- tundish of the first two judges whether half heat quantity is equal, equal, is combined into tundish, and be put into tundish set,
If half heat quantity is unequal, the big tundish of quantity is clipped into half heat of gap, and interception is partially placed into pre- tundish
Set, remaining two pre- tundish are combined, and are formed tundish, are put into tundish set, go to step S143；
S143, judge whether pre- tundish set is empty, be that sky is then deleted, and takes next pre- tundish collection in mutually exclusive sets
It closes, if group tundish mutually exclusive sets is sky, goes to step S15, otherwise go to step S142；
S15, heat is determined；
S151, traversal tundish set, take tundish in order, go to step S152；
S152, the tundish being traversed, taken in same tundish, half heat that time corresponding position is flowed in left and right constitutes heat, if
The heat (batch) number attribute of fixed half heat；
S153, judge whether tundish set traverses completion, completion goes to step S16, otherwise goes to step S151；
S16, consider grade transition, determine casting plan；
S161, rule is poured according to pouring group repeatedly, will pour and do not organize out pouring for Optimum Economic furnace number in time set and time be divided into difference
Mutual exclusion pour set repeatedly, go to step S162；
S162, one of them is taken to pour set repeatedly, traversal is poured time, judge that can two be poured secondary width and be connected, thus by two
A pour time is merged into one and is poured repeatedly；If can merge, time merging is poured by two, one cannot be then removed and pour and time judged, directly
It is completed to time combination is poured；Go to step S163；
S163, judge that mutual exclusion pours whether set traverses completion repeatedly, complete then to enter Optimization Steps, otherwise go to step
S162。
Further, after generating initial solution according to the specific steps in step S1, then in step s 2, change neighborhood knot is used
Simulated annealing is closed to optimize；By taking charging plan as an example, the neighbour structure that is defined as follows: N1- exchanges slab；The operation is logical
The slab for exchanging different heats is crossed, constrains if the operation meets and improves objective function, receive the exchange；N2- power board
Base, the operation receive the friendship if the operation meets constraint and improves objective function by exchanging the slab of different heats
It changes；The neighbour structure and charging plan of casting plan are similarly；Receive neighborhood change since model constraint is extremely more, and using greedy mode
It changes, if falling into locally optimal solution, to solve this problem, when falling into local optimum, new explanation is obtained using simulated annealing, then
Iteration carries out change neighborhood search, to obtain acceptable solution.
The algorithm steps of use are as follows:
S21, the initial solution that the above process generates is set as S0, the parameter of simulated annealing is set；
S22, to solution S0Using internal layer simulated annealing, new solution S ' is obtained；
S221, judge whether i < m is true, m is heat sum, if then going to step S222, otherwise goes to step S22；
S222, on the basis of current solution, any heat that exchanges obtains new solution S '；The target function value of new explanation S is calculated,
And objective function difference DELTA E=S '-S0；Decide whether to receive new explanation, if Δ E < 0 or e-ΔE/TGreater than random chance p,
Then retain solution S '；i++；
S223, cooling enable T=T Δ t, go to step S23；
S23, to solution S0Change neighborhood search (VNS) is carried out, if initial parameter k=1；Go to step S231；
S231, k is judged whether less than 4, if then using neighbour structure NkIt scans for, until falling into locally optimal solution S*,
If S*Better than S0Then enable S0=S*, k=0；Otherwise k++；If >=4 k, go to step S24；
S24, solution S ' is obtained to solution S ' carry out step 2*；Judge whether the solution is better than S*, it is to receive and be assigned to S*；
S25, judge that T whether less than 40, is to export solution, otherwise goes to step S23.
Further, have performance indicator: the steel grade difference of group to the production work order in each heat is as small as possible；Group arrives
The production work order cocurrent flow width difference of each heat is as small as possible；Group arrives steel grade rank difference between the adjacent heat of identical tundish
It is different as small as possible；Group is as small as possible to width difference between the adjacent heat of identical tundish.
Compared with prior art, the different wide steel smelting-continuous casting process batches plan optimization method of two stream of the present invention,
Two processes are broadly divided into, initial solution is constructed using heuritic approach, then using change neighborhood combination simulated annealing to first
Beginning solution optimizes.Initial solution preocess can be divided into group furnace process and group pours process, using enterprise practical production case to model and
The validity of algorithm has carried out confirmatory experiment, the results showed that steel smelting-continuous casting batch plan model and VNS combination SA algorithm are solved and be somebody's turn to do
Class problem is effectively that this method is convenient and simple, and calculating speed is fast.
It plays a decisive role in batch plan optimization algorithm to result of the processing of width to optimization algorithm, for small lot
Change release, scene work out plan and often separately consider the stream width of conticaster two, tied according to how many pairs two of slab quantity streams
Brilliant device width is configured, so that the slab of different in width is combined under the premise of meeting production constraint, so that same
Width of plate slab gap corresponding with two streams is larger in heat, but can reasonable arrangement produce, reduction tundish quantity.
Therefore, it pours that be able to solve contracted quantity small using the different wide group furnace group of two streams, but is badly in need of the case where arranging production.The present invention
In the case where describing the steel smelting-continuous casting Batch Planning of the steel mill, considers the two different width of stream, charging plan is decomposed into half furnace
Secondary plan, in the group between Bao Shizai from macroscopically determine corresponding other half heat of half heat, form heat, heat determine
In the case of reconfigure and pour time.To solve because slab is various in style, tundish caused by batch is smaller is large number of, can not
The problem of merging.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to do simply to introduce, it should be apparent that, the accompanying drawings in the following description is this hair
Bright some embodiments for those of ordinary skill in the art without any creative labor, can be with
It obtains other drawings based on these drawings.
Fig. 1 is step S1 flow chart of the present invention.
Fig. 2 is step S2 flow chart of the present invention.
Specific embodiment
In order to enable those skilled in the art to better understand the solution of the present invention, below in conjunction in the embodiment of the present invention
Attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
The model that the present invention protects all should belong in member's every other embodiment obtained without making creative work
It encloses.
It should be noted that description and claims of this specification and term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so as to the embodiment of the present invention described herein can in addition to illustrating herein or
Sequence other than those of description is implemented.In addition, term " includes " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, for example, the process, method, system, product or equipment for containing a series of steps or units are not necessarily limited to
Step or unit those of is clearly listed, but may include be not clearly listed or for these process, methods, product
Or other step or units that equipment is intrinsic.
The present invention provides the two different wide steel smelting-continuous casting process batches plan optimization methods of stream of one kind, comprising the following steps:
S1, the heat-for establishing Steelmaking-Continuous Casting Production Scheduling pour time batch plan model；
Half charging plan is firstly generated, and then generates the middle packet plan with steel grade, tundish plan determines furnace with this
Secondary plan considers the casting plan of grade transition and hot rolling material constraint, detailed process is as follows after determining charging plan:
S11, data processing；
By work order according to unit, path, thickness are refined, tapping mark is divided into different group furnaceman's list mutually exclusive sets, is gathering
It is interior to arrange work order according to allowing to produce width descending, to make steel a group furnace；
S12, half heat process of group；
S121, first work order set for taking work order mutually exclusive sets carry out next step S122 for each work order；
S122, judge whether the work order set is empty, be that sky then deletes the work order set, then carries out step S121, otherwise
Carry out next step S123；
S123, a work order in work order set is taken, carries out next step S124；
S124, judge whether heat set is empty, be that sky then establishes one and half heat set, and generates a half new furnace
It is secondary；According to a group furnace rule, heat set is traversed, can judgement be added to the work order when first half heat, if can, by the work order
Be added to current heat, and deleted from work order set, if cannot if create half heat, half heat is added in work order, by this half
Heat set is added in heat, and the work order is deleted from work order set, then goes to step S125；
S125, judge whether work order mutually exclusive sets is sky, then go to step S13 for sky, otherwise go to step S121；
S13, the pre- intermediate packet procedures of group；
S131, first half heat for taking heat set carry out step S132 for first half heat；
S132, judge whether pre- tundish set is empty, be that sky then establishes a pre- tundish set, and generates one newly
Pre- tundish；According to pre- tundish rule is organized, pre- tundish set is traversed, can judgement be added to half heat in currently pre-
Between wrap, if can, which is added to current pre- tundish, and half heat is deleted from half heat set, if cannot if it is new
Pre- tundish is built, half heat is added to the pre- tundish, and delete half heat from heat set；Go to step S133；
S133, judge whether half heat set is sky, be idle running step S14, otherwise go to step S131；
S14, intermediate packet procedures are organized；
S141, according to unit, refine path, thickness, pre- tundish is divided into different groups and pours mutual exclusion set by tapping mark,
And pre- tundish is arranged according to half heat quantity descending in gathering；
S142, judge whether tundish set is sky, then establish a tundish set for sky, take in pre- tundish set
The pre- tundish of the first two judges whether half heat quantity is equal, equal, is combined into tundish, and be put into tundish set,
If half heat quantity is unequal, the big tundish of quantity is clipped into half heat of gap, and interception is partially placed into pre- tundish
Set, remaining two pre- tundish are combined, and are formed tundish, are put into tundish set, go to step S143；
S143, judge whether pre- tundish set is empty, be that sky is then deleted, and takes next pre- tundish collection in mutually exclusive sets
It closes, if group tundish mutually exclusive sets is sky, goes to step S15, otherwise go to step S142；
S15, heat is determined；
S151, traversal tundish set, take tundish in order, go to step S152；
S152, the tundish being traversed, taken in same tundish, half heat that time corresponding position is flowed in left and right constitutes heat, if
The heat (batch) number attribute of fixed half heat；
S153, judge whether tundish set traverses completion, completion goes to step S16, otherwise goes to step S151；
S16, consider grade transition, determine casting plan；
S161, rule is poured according to pouring group repeatedly, will pour and do not organize out pouring for Optimum Economic furnace number in time set and time be divided into difference
Mutual exclusion pour set repeatedly, go to step S162；
S162, one of them is taken to pour set repeatedly, traversal is poured time, judge that can two be poured secondary width and be connected, thus by two
A pour time is merged into one and is poured repeatedly；If can merge, time merging is poured by two, one cannot be then removed and pour and time judged, directly
It is completed to time combination is poured；Go to step S163；
S163, judge that mutual exclusion pours whether set traverses completion repeatedly, complete then to enter Optimization Steps, otherwise go to step
S162。
S2, simulated annealing (Simulated is combined using change neighborhood (Variable Neighborhood Search, VNS)
Annealing, SA) algorithm model described in step S1 optimizes.
After generating initial solution according to the specific steps in step S1, then in step s 2, change neighborhood (Variable is used
Neighborhood Search, VNS) combine simulated annealing (Simulated Annealing, SA) algorithm to optimize；With furnace
For secondary plan, the neighbour structure that is defined as follows: N1- exchanges slab；The operation is by exchanging the slab of different heats, if be somebody's turn to do
Operation, which meets, to be constrained and improves objective function, then receives the exchange；N2- exchanges slab, and the operation is by exchanging different heats
Slab constrains if the operation meets and improves objective function, receives the exchange.
The neighbour structure and charging plan of casting plan are similarly；Receive since model constraint is extremely more, and using greedy mode
Neighborhood transformation, if falling into locally optimal solution, to solve this problem, when falling into local optimum, using simulated annealing
(Simulated Annealing, SA) algorithm obtains new explanation, then iteration carries out change neighborhood search, to obtain acceptable solution；
The algorithm steps of use are as follows:
S21, the initial solution that the above process generates is set as S0, the parameter of simulated annealing is set；
S22, to solution S0Using internal layer simulated annealing (SA), new solution S ' is obtained.
S221, judge whether i < m is true, m is heat sum, if then going to step S222, otherwise goes to step S22；
S222, on the basis of current solution, any heat that exchanges obtains new solution S '；The target function value of new explanation S is calculated,
And objective function difference DELTA E=S '-S0；Decide whether to receive new explanation, if Δ E < 0 or e-ΔE/TGreater than random chance p,
Then retain solution S '；i++；
S223, cooling enable T=T Δ t, go to step S23；
S23, to solution S0Change neighborhood search (VNS) is carried out, if initial parameter k=1；Go to step S231；
S231, k is judged whether less than 4, if then using neighbour structure NkIt scans for, until falling into locally optimal solution S*,
If S*Better than S0Then enable S0=S*, k=0；Otherwise k++；If >=4 k, go to step S24；
S24, solution S ' is obtained to solution S ' carry out step 2*；Judge whether the solution is better than S*, it is to receive and be assigned to S*；
S25, judge that T whether less than 40, is to export solution, otherwise goes to step S23.
With performance indicator: the steel grade difference of group to the production work order in each heat is as small as possible；Group arrives each heat
Production work order cocurrent flow width difference it is as small as possible；It organizes to steel grade grade difference between the adjacent heat of identical tundish as far as possible
It is small；Group is as small as possible to width difference between the adjacent heat of identical tundish.
The different wide steel smelting-continuous casting process batches plan optimization method of two stream of the present invention, in conjunction with being ordered in actual production
Single contract is mostly small lot, the background of customization, fully take into account continuous casting of two strands in parallel machine two flow crystallizer can different wide situation, establish
Group furnace-the group for meeting steel-making continuous casting process constraint pours batch plan model, devises heuritic approach and solves the problems, such as this, and benefit
With variable neighborhood search algorithm optimum results.Simulating, verifying has been carried out for one day actual production data of certain steel mill.It is tied from emulation
Seen in fruit, in tundish left and right stream width there are width linking between inconsistent and heat is smooth, compare practical same day scheduling as a result,
Remaining material rate reduces 5.5%, and remaining material gross weight reduces 980t.Heat quantity reduces by 4 furnaces, and tundish quantity reduces 3.It is substantially better than hand
Work operation brings considerable economic benefit for enterprise.Compared with artificial planning, reduce the planning time, improves
The quality of plan.
The different wide steel smelting-continuous casting process batches plan optimization method of two stream of the present invention, be divided into group furnace process and
Group pours process, since problem can be divided into heat problem and pour time problem, and need to consider the different width of two streams, therefore, firstly generate half furnace
Secondary plan, and then the middle packet plan with steel grade is generated, tundish plan determines charging plan with this, is determining heat meter
After drawing, the casting plan of grade transition and hot rolling material constraint is considered, be a kind of for the different wide steel smelting-continuous casting process batch of two streams
Measure plan optimization method.
Embodiment 1
In embodiment, used letter character and its meaning are as shown in the table:
Decision variable
For the ease of pouring the foundation and solution that problem carries out mathematical model to production work order group furnace group, firstly for the problem
Performance indicator converted, then for the key element of the modelings such as the target of the problem, constraint condition and decision variable
It is described.
Performance indicator is respectively as follows:
The steel grade difference of group to the production work order in each heat is as small as possible.
The production work order cocurrent flow width difference of group to each heat is as small as possible.
Group is as small as possible to steel grade grade difference between the adjacent heat of identical tundish.
Group is as small as possible to width difference between the adjacent heat of identical tundish.
Wherein, constraint condition are as follows:
All work orders are by scheduling, i.e., each work order is by group in a certain charging plan.
All heats ensure that heat is all arranged in a certain casting plan by scheduling.
Group furnace rule is to be less than the maximum standard of furnace weight with work order weight summation in furnace, is greater than minimum sandards, and work order
Unit, thickness, refining path, necessary identical, the similar width of tapping mark, are less than tune wide scope, root with furnace insied width difference
According to data prediction, the work order in different sets does not allow in same heat.
Group pours rule to be less than Optimum Economic furnace number with furnace number in pouring time, and with unit, the thickness, essence of heat in pouring time
Refining path must be identical, allows for mixing if heat steel grade difference and pour, the work according to data prediction, in different sets
It is single not allow to pour in secondary same.
Heat weight is not less than the most port weight of unit, no more than maximum furnace weight.
Pouring secondary maximum casting sequence should be the minimum value for pouring the corresponding maximum casting sequence of all heat steel grades in secondary.
Adjacent width of plate slab gap, which is less than, in same heat adjusts the wide maximum value allowed.
Same time interior adjacent heat linking width of plate slab gap of pouring is less than the maximum value for adjusting width to allow.
It pours time interior hot rolling material slab weight and is less than the hot rolling material maximum weight for allowing to produce.
For convenience of the foundation and solution of mathematical model, data prediction need to be carried out, mainly includes following two points:
(1) work order is classified.Work order collection I is classified according to unit and steel grade and refining path, is arranged in identical machine
The work order of group production and identical steel grade is divided into same category, is divided into K class, i.e.,
I=G1∪G2∪...∪GK。
(2) mutual exclusion rule collection.Due to having unit in group furnace rule, with steel grade requirement, work order group furnace mutually exclusive sets is established accordingly
Close, by can not work order of the group in same heat enumerated in set come, i.e.,
S1=(i, j) | i ∈ Gk1, j ∈ Gk2, k1≠k2}
Group, which is poured, same specification in rule, can even pour steel grade just can continuous casting requirement similarly can obtain group and pour mutually exclusive sets, i.e.,
S2=(i, j) | i ∈ Gk3, j ∈ Gk4, k3≠k4}
Based on the above analysis, designs group furnace-group as follows and pours mathematical model:
Wherein, formula (1) is objective function, and first item is to minimize to pour sub-quantity, and Section 2 is that adjacent slab is wide in heat
Gap punishment is spent, Section 3 is to pour time interior adjacent heat width penalty value.All work orders of constraint formula (2) expression are by scheduling, i.e.,
Each work order is by group in a certain charging plan.Formula (3) indicates that all heats by scheduling, that is, ensure that heat is all arranged at
In a certain casting plan.Formula (4) is group furnace rule, and according to data prediction, the work order in different sets does not allow same
In one heat.Formula (5) is that group pours rule, and according to data prediction, the work order in different sets does not allow to pour time same
In.Formula (6) indicates heat weight, and weight is related with the unit that slab is assigned, and furnace is not less than the most port weight of unit again, less
In maximum furnace weight.Formula (7) indicates maximum casting sequence, the maximum casting sequence poured time should be pour time in all heat steel grades it is corresponding
Maximum casting sequence minimum value.Formula (8) indicates that adjacent width of plate slab gap is less than the wide permission of tune most in same heat
Big value.Formula (9) indicates that same time interior adjacent heat linking width of plate slab gap of pouring is less than the wide maximum value allowed of tune.Formula (10)
Indicate that pouring time interior hot rolling material slab weight is less than the hot rolling material maximum weight for allowing to produce.
Since mathematical model solves complexity, validity is not high, can not solve the problems, such as extensive actual production, and virtual heat
Interior slab and conticaster or so crystallizer corresponding relationship are difficult to mathematical symbolism, thus use didactic method to problem into
Row solves.
Simulated annealing and change neighborhood search combination algorithm.
The present embodiment proposes that three stage group furnace groups pour strategy: data prediction, is based on the building of group furnace cast design initial solution
Simulated annealing and the group furnace cast design optimization process for becoming neighborhood search.Wherein, group furnace cast design initial solution constructs includes: again
Production half furnace of work order group, half furnace, which are merged into, partly to be poured, partly pours that group is combined into tundish, tundish splits four part of heat.Based on simulation
Annealing and the group furnace cast design optimization process for becoming neighborhood search include: the building of variable neighborhood search algorithm neighborhood, simulated annealing
It searches for local optimum and obtains perturbed solution two parts.Group furnace cast design meets tundish minimum number, adjacent in same tundish
Width gap is as small as possible between heat, steel grade grade difference is as small as possible, in furnace the adjacent width of plate slab gap of cocurrent flow it is as small as possible,
Remaining material rate multiple performance indicators as few etc. as possible, and these performance indicators is made all to reach more excellent solution as far as possible.And under meeting
Requirement of the procedure to hot rolling material in tundish meets production technology constraint.
Simulation result and analysis.
The different wide heat proposed-casting plan establishment multiple target mould is flowed to solve the problems, such as to pour time interior left and right herein in order to verify
Type and VNS combination SA algorithm solve the effect of the problem, carry out emulation experiment using the real data of certain steel production enterprise.It takes
1 day contract daily planning data includes A1, and A2, totally 732 blocks of slabs, 3 unit standard stoves are respectively 150t to A9 unit again,
250t, 150t, the interior left and right stream of furnace is each to allow to adjust width once, and tune wide scope is 150mm.Parameter setting is as follows:SA algorithm fractional t1=100, T2=60, t=0.8.Using model solution obtain the same day heat and
Casting plan.Since data volume is larger, partial results are only listed.
Table 1 is part casting plan, and table 2 indicates that 106 pour second part plan on grouping furnaces.
1 casting plan of table (part)
Table 2 106 pours time charging plan (part)
Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Pipe present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: its according to
So be possible to modify the technical solutions described in the foregoing embodiments, or to some or all of the technical features into
Row equivalent replacement；And these are modified or replaceed, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme.
Claims (4)
1. the two different wide steel smelting-continuous casting process batches plan optimization method of stream of one kind, it is characterised in that the following steps are included:
S1, the heat-for establishing Steelmaking-Continuous Casting Production Scheduling pour time batch plan model；
S2, it is optimized using change neighborhood combination simulated annealing model described in step S1.
2. the different wide steel smelting-continuous casting group furnace group of two stream according to claim 1 pours batch plan optimization method, feature exists
In,
In step S1, half charging plan is firstly generated, and then generates the middle packet plan with steel grade, tundish plan, with this
It determines charging plan, after determining charging plan, considers the casting plan of grade transition and hot rolling material constraint, detailed process is such as
Under:
S11, data processing；
By work order according to unit, path, thickness are refined, tapping mark is divided into different group furnaceman's list mutually exclusive sets, will in set
Work order is according to allowing to produce the arrangement of width descending, to make steel a group furnace；
S12, half heat process of group；
S121, first work order set for taking work order mutually exclusive sets carry out next step S122 for each work order；
S122, judge whether the work order set is sky, then delete the work order set for sky, then carry out step S121, otherwise carry out
Next step S123；
S123, a work order in work order set is taken, carries out next step S124；
S124, judge whether heat set is empty, be that sky then establishes one and half heat set, and generates a half new heat；
According to a group furnace rule, heat set is traversed, can judgement be added to the work order when first half heat, if can, which is added
Deleted to current heat, and from work order set, if cannot if create half heat, half heat is added in work order, by half furnace
Secondary addition heat set, and the work order is deleted from work order set, then go to step S125；
S125, judge whether work order mutually exclusive sets is sky, then go to step S13 for sky, otherwise go to step S121；
S13, the pre- intermediate packet procedures of group；
S131, first half heat for taking heat set carry out step S132 for first half heat；
S132, judge pre- tundish set whether be it is empty, then establish a pre- tundish set for sky, and generate one it is new pre-
Tundish；According to pre- tundish rule is organized, pre- tundish set is traversed, can judgement be added to half heat current pre- centre
Packet, if can, which is added to current pre- tundish, and half heat is deleted from half heat set, if cannot if create
Half heat is added to the pre- tundish, and deletes half heat from heat set by pre- tundish；Go to step S133；
S133, judge whether half heat set is sky, be idle running step S14, otherwise go to step S131；
S14, intermediate packet procedures are organized；
S141, according to unit, refine path, thickness, pre- tundish is divided into different groups and pours mutual exclusion set by tapping mark, and will
Pre- tundish is arranged according to half heat quantity descending in gathering；
S142, judge whether tundish set is sky, then establish a tundish set for sky, take preceding two in pre- tundish set
A pre- tundish judges whether half heat quantity is equal, equal, is combined into tundish, and be put into tundish set, if half
Heat quantity is unequal, then the big tundish of quantity is clipped half heat of gap, and interception is partially placed into pre- tundish set,
Remaining two pre- tundish are combined, tundish is formed, is put into tundish set, goes to step S143；
S143, judge whether pre- tundish set is sky, then deleted for sky, and take next pre- tundish set in mutually exclusive sets, if
Group tundish mutually exclusive sets is sky, then goes to step S15, otherwise go to step S142；
S15, heat is determined；
S151, traversal tundish set, take tundish in order, go to step S152；
S152, the tundish is traversed, taken in same tundish, half heat that time corresponding position is flowed in left and right constitutes heat, setting half
The heat (batch) number attribute of heat；
S153, judge whether tundish set traverses completion, completion goes to step S16, otherwise goes to step S151；
S16, consider grade transition, determine casting plan；
S161, pour rule according to pouring group repeatedly, by pour do not organized out in time set Optimum Economic furnace number pour time be divided into it is different mutual
Reprimand pours set repeatedly, goes to step S162；
S162, one of them is taken to pour set repeatedly, traversal is poured time, judge that can two be poured secondary width and be connected, so that two be poured
It is secondary to merge into one and pour repeatedly；If can merge, time merging is poured by two, one cannot be then removed and pour and time judged, until pouring
Secondary combination is completed；Go to step S163；
S163, judge that mutual exclusion pours whether set traverses completion repeatedly, complete then to enter Optimization Steps, otherwise go to step S162.
3. the different wide steel smelting-continuous casting process batches plan optimization method of two stream according to claim 2, which is characterized in that
After generating initial solution according to the specific steps in step S1, then in step s 2, calculated using neighborhood combination simulated annealing is become
Method optimizes；
By taking charging plan as an example, the neighbour structure that is defined as follows: N1- exchanges slab；
The operation receives the friendship if the operation meets constraint and improves objective function by exchanging the slab of different heats
It changes；
N2- exchanges slab, which is constrained if the operation meets by the slab of the different heats of exchange and improve target letter
Number, then receive the exchange；
The neighbour structure and charging plan of casting plan are similarly；
Receive neighborhood transformation since model constraint is extremely more, and using greedy mode, if falling into locally optimal solution, is asked to solve this
Topic obtains new explanation using simulated annealing, then iteration carries out change neighborhood search when falling into local optimum, so that obtaining can
The solution of receiving；
The algorithm steps of use are as follows:
S21, the initial solution that the above process generates is set as S0, the parameter of simulated annealing is set；
S22, to solution S0Using internal layer simulated annealing, new solution S ' is obtained；
S221, judge whether i < m is true, m is heat sum, if then going to step S222, otherwise goes to step S22；
S222, on the basis of current solution, any heat that exchanges obtains new solution S '；The target function value of new explanation S is calculated, and
Objective function difference DELTA E=S '-S0；Decide whether to receive new explanation, if Δ E < 0 or e-ΔE/ T is greater than random chance p, then protects
Stay solution S '；i++；
S223, cooling enable T=T Δ t, go to step S23；
S23, to solution S0Change neighborhood search (VNS) is carried out, if initial parameter k=1；Go to step S231；
S231, k is judged whether less than 4, if then using neighbour structure NkIt scans for, until falling into locally optimal solution S*If
S*Better than S0Then enable S0=S*, k=0；Otherwise k++；If k >=4, go to step S24；
S24, solution S ' is obtained to solution S ' carry out step 2*；Judge whether the solution is better than S*, it is to receive and be assigned to S*；
S25, judge that T whether less than 40, is to export solution, otherwise goes to step S23.
4. the different wide steel smelting-continuous casting process batches plan optimization method of two stream according to claim 2 or 3, feature exist
In,
With performance indicator: the steel grade difference of group to the production work order in each heat is as small as possible；Group arrives the life of each heat
It is as small as possible to produce work order cocurrent flow width difference；Group is as small as possible to steel grade grade difference between the adjacent heat of identical tundish；
Group is as small as possible to width difference between the adjacent heat of identical tundish.
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