CN108596375A - A kind of equipment manufacture material requirement Design Method and system - Google Patents
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Abstract
The present invention provides a kind of equipment manufacture material requirement Design Method, according to material requirement data set, determine each material requirement time point, and time point set is clustered, using improved K_Means algorithms to material requirement time point clustering, the required time point tool that suitable merging material requirement is come to centralized purchasing is one kind；Initiated purchase scheme is determined according to material requirement information and material variety, establishes the optimization constraint of procurement scheme；Select satisfactory procurement scheme composition procurement scheme collection；Obtain the fitness of scheme；According to the fitness of each procurement scheme, GWO optimization algorithm optimization purchases scheme collection is utilized；To the procurement scheme collection after optimization into row variation, and is calculated by the fitness of new procurement scheme, replacement is compared with the fitness of initiated purchase scheme for the procurement scheme inspection after variation using optimization constraint；Until obtaining satisfied procurement scheme.The present invention provides data supporting for the buying of resources of production, to lower production cost.
Description
Technical field
The invention belongs to equipment manufacture material fields, and in particular to a kind of equipment manufacture material requirement conceptual design side
Method and system.
Background technology
Equipment manufacture is that the advanced manufacturing industry of Technical facilities in production is provided for national economy and national defense construction, main to produce
The well of mineral resources is adopted and strip mining equipment, the large size such as large electric power plant, water power, nuclear power complete set of equipments and complicated technology
Equipment.The with high content of technology of these products, production technology are complicated, and the production time is long.Under current market environment, in order to meet
The individual demand of client, enterprise generally design and produce product by order.Requirement due to different clients to product is not
Together, so for enterprise, though produce same type product when in internal structure and configuration design etc. if can exist
Difference, and then result in the difference of product processes and consumed resource.When enterprise is simultaneously to the product of different clients customization
When being produced, the demand opportunity and demand of the production schedule of each product to all kinds of resources are different from, it is difficult to according to biography
The procurement strategy of system carrys out at a time centralized purchasing certain resource.Therefore the cooperation between scheduling of production and resource purchasing is asked
Topic will become difficult to solve, and the supply problem of resources of production can further result in enterprise and be difficult to control to the production cost of product again
System.
Invention content
The technical problem to be solved by the present invention is to：A kind of equipment manufacture material requirement Design Method is provided and is
System, provides data supporting, to lower production cost for the buying of resources of production.
The technical solution taken by the invention to solve the above technical problem is：A kind of equipment manufacture material requirement scheme
Design method, it is characterised in that：It includes the following steps：
Step 1, initialization data set：Initialize material requirement data set Mn, material attribute data collection Mps；
Step 2, according to material requirement data set, determine each material requirement time point, and cluster to time point set,
Using improved K_Means algorithms to material requirement time point clustering, suitable merging material requirement is come to the need of centralized purchasing
Seeking time point tool is one kind；
Step 3：Initiated purchase scheme is determined according to material requirement information and material variety, and is gathered according to what step 2 obtained
Class result establishes the optimization constraint of procurement scheme；
Step 4：Procurement scheme collection S is formed by selecting satisfactory procurement scheme；
Step 5：By calculate material procurement payment cost of possession, stock material management cost and production delay cost and
The value of penalty obtains the fitness of scheme；
Step 6：According to the fitness value of each procurement scheme, the buying side obtained using GWO optimization algorithms Optimization Steps 4
Case collection S；
Step 7：To the obtained procurement scheme collection S after optimization into row variation, and constrained using the optimization obtained in step 3
To the procurement scheme inspection in the procurement scheme collection S after variation, the fitness of new procurement scheme is calculated, at the beginning of step 3
The fitness of beginning procurement scheme is compared replacement；
Step 8：When the fitness value of procurement scheme tends towards stability, it is considered that in the iterative process of continuous preset times
In optimal fitness value do not change, judge that fitness tends towards stability, then terminate calculating, export best fitness value
Corresponding procurement scheme, otherwise goes to step 6.
By said program, the step 2 is specially：
(1) number of clusters k is determined；
(2) select k time point as initial cluster center in required time point set at random；
(3) time interval of the quantity required and material price attribute and required time point and initial cluster center of material is used
Calculate similarity, by each required time point cluster to in the cluster of its similarity minimum；
(4) calculate the average value of all required time points in each cluster, and by after the processing of this average value as newly
Cluster centre；
(5) (3), (4) are executed repeatedly, until the number that cluster centre is moved or clustered in a certain range reaches default
Until quantity；
(6) output cluster, and count the included required time point set Tc of each cluster.
By said program, described (3) calculate the similarity of each required time point and cluster centre, specific to calculate such as
Under：
In formula：MqijFor enterprise in i-th of required time point to the demand of material j, MpjFor the price of material j, MQ is
In all required time points to the total demand of material, m is the total quantity of material variety, μ for enterprisehFor h-th of cluster centre, ti
For i-th of buying hour point,For the distance of i-th buying hour point and h-th of cluster centre.
It is as follows that described (4) calculate new cluster centre formula：
In formula：ti (j)To belong to cluster centre μjI-th of required time point, x be divided into cluster centre μjDemand
Time point number, Round (x) function representations take the integer nearest apart from variable x；MqtijFor required time point tiTo material j's
Demand, MpjFor the price of material j；M is material variety quantity.
By said program, the specific formula for calculation of fitness is as follows in the step 5：
Fit (x)=OC (x)+MC (x)+DC (x)+δ (gen) × H (x)
In formula：OC (x) is procurement payment cost of possession, and MC (x) is stock material management cost, and DC (x) is that production is delayed
Cost, δ (gen) H (x) are penalty, and δ (gen) is punishment dynamics, value related to the evolutionary generation of GWO algorithms
Wherein, OC (x) calculation formula are as follows：
In formula：MbtijIndicate procurement scheme in required time point tiTo the purchase quantity of material j, iptiMark is needed in material
Seeking time point tiWhether purchase behavior is had occurred, and f is the fixed cost of single buying, and I is the rate of return on investment of enterprise, tsiFor when
Between point tiThe time interval of the required time point of distance the latest；N is the quantity of buying hour point；M is the quantity of material variety.
MC (x) calculation formula are as follows：
In formula：Ts is earliest material requirement time point to the time interval at material requirement time point the latest, RqijFor material
J is in i-th day quantity in stock, RmjFor the stock control expense of the unit interval of material j；
DC (x) calculation formula are as follows；
DC (x)=dt × dp
In formula：Dt is the production delay time at stop, and dp is the cost of production delay unit interval；
Penalty calculation formula is as follows：
qj(x)=max { 0, pj(x)}
pj(x)=hj(x)
Wherein：H (x) is penalty factor, qj(x) it is violation degree of the procurement scheme to optimization constraint, hj(x) it is buying side
Measures of dispersion of the case between the amount of purchase and enterprise demand amount of jth kind material, r (qj(x)) it is strength of punishment, θ (qj(x)) it is point
Section mapping function, stajIndicate aggregate demand of the enterprise to jth kind material.
By said program, the step 6 specific formula for calculation is as follows：
In GWO optimization process, improved location update formula：
D=| C × Xp(t)-X(t)|
X (t+1)=Xp(t)-A×D
In formula：C=2r1, A=2ar2-a
Wherein：D is the distance between grey wolf individual and prey, Xp(t) be t for when prey position, X (t) be t generations
When grey wolf individual position, X(t+1)For t+1 for when grey wolf individual position, C is constant, be swing the factor, A is convergence factor,
r1、r2For the random number of [0,1], a is grey wolf population as iterations increase from 2 linear decreases to 0, f (α), f (β), f (δ)
The fitness value of the middle fitness grey wolf individual of first three, X1、X2、X3Respectively t+1 for when wolf position, Xp(t+1)For t+1 for when
The position of prey.
By said program, the step 7 specific formula for calculation is as follows：
Optimization constraint calculation formula：
In formula：sckjIndicate that k-th of included required time point of cluster concentrates all time points total to the buying of material j
Measure the constraint that should meet.
A kind of equipment manufacture material requirement Scheme Design System, it is characterised in that：It includes memory and processor, is deposited
There is computer program in reservoir, called for the processor, is set with the equipment manufacture material requirement scheme for completing described
Meter method.
Beneficial effects of the present invention are：The calculating formula of similarity in clustering algorithm has been redesigned, has made cluster result more
Add and meets actual demand；By clustering algorithm, to concentrate implementation procurement strategy to provide the foundation, while reducing GWO optimizations and calculating
The value range of independent variable in method can stop in non-optimal solution region to avoid algorithm, accelerate the solution efficiency of algorithm；For
GWO algorithms addition variation step, effectively reduces the possibility that algorithm is absorbed in locally optimal solution；Utilize intelligent optimization algorithm
It determines the important parameters such as the procurement cycle in centralized purchasing strategy, buying hour point, amount of purchase, can seek to relatively preferably
Procurement scheme, production cost is greatly reduced；The discrete demand characteristic of algorithm combination equipment Manufacturing material is designed, more
Stick on the actual demand for closing enterprise.
Description of the drawings
Fig. 1 is to cluster flow chart at the material requirement time point of this method
Fig. 2 is the GWO procurement strategy optimization method flow charts of this method
Fig. 3 is the general frame figure of this system
Fig. 4 is the operational flow diagram of this system
Specific implementation mode
With reference to specific example and attached drawing, the present invention will be further described.
One, the description of material procurement problem
Initialize enterprise material requirement data set Mn, material attribute data collection Mps.It is obtained from material requirement data set Mn
Required time point set T={ Ti| i=1,2, n } and, in each required time point to the quantity required Mq=of each material
{Mqij| i=1,2, n；J=1,2, h }；Material collection M={ M are obtained from material property set Mpi| i=1,
2, h }, the procurement price Mp={ M of each materialPi| i=1,2, h } and, the unit interval unit of each material
The stock control expense Rm={ Rm of quantityi| i=1,2, h }.Consider enterprise's production cost and meets the feelings of production
Under condition, need to purchase required all kinds of materials within the material requirement period.In order to realize centralized purchasing, need to merge certain several
The material requirement of required time point carries out centralized purchasing, uses K_Means clustering algorithms by all material requirement time herein
Point is divided into k classes, and the material requirement for arranging the material requirement time point to each in clustering later carries out centralized purchasing, and determines
Corresponding buying constraints.Finally formulate procurement scheme Mb={ Mbij| i=1,2, n；J=1,2, h },
In the case where meeting carried goal condition as possible using GWO algorithms come optimization purchases scheme.It is as follows to establish cost model：
Object function：
F (x)=OC (x)+MC (x)+DC (x)
In formula：OC (x) is procurement payment cost of possession, and MC (x) is stock material management cost, and DC (x) is that production is delayed
Cost.
Wherein, OC (x) calculation formula are as follows：
In formula：MbtijIndicate procurement scheme in required time point tiPurchase the quantity of material j, iptiMark is in material requirement
Time point tiWhether purchase behavior is had occurred, and f is the fixed cost of single buying, and I is capital investment return rate, tsiFor time point
tiThe time interval of the required time point of distance the latest.
MC (x) calculation formula are as follows：
In formula：Ts is earliest material requirement time point to the time interval at material requirement time point the latest, RqijFor material
J is in i-th day quantity in stock, RmjFor the stock control expense of the unit interval of material j.
DC (x) calculation formula are as follows；
DC (x)=dt × dp
In formula：Dt is the production delay time at stop, and dp is the cost of production delay unit interval.
Constraints：
Amount of purchase constrains：Each material quantity of procurement scheme buying must satisfy enterprise's production requirement, i.e.,
Two, specific implementation step, as shown in Figure 3 and Figure 4.
The work that the logging data module of system carries out：
Step 1：Initialization data set inputs demand data collection Mn, material attribute data in the data inputting module of system
Collect Mps, and enter and solve module, system built-in algorithm can come initial reguirements time point set T, material collection according to the input data
M, material set of prices Mp, stock material administration fee collection Rm, material requirement quantity collection Mq.T={ Ti|I=1,2, n } and, M
={ Mi| i=1,2, h }, Mp={ Mpi| i=1,2, h }, Rm={ Rmi| i=1,2, h }, Mq=
{Mqij| i=1,2, n；J=1,2, h }
The work that the solution module (K_Means cluster modules) of system carries out：
Step 2：According to material requirement data set material associated property data, T is clustered.Material, which can be merged, to be needed
The time point for carrying out centralized purchasing is asked to gather for one kind, as shown in Figure 1, specific step is：
(1) number of clusters k is determined
(2) cluster centre is selected, selects k time point as initial cluster center in required time point set at random.
Be denoted as V=Vc | c=1,2, k }
(3) similarity (distance) is calculated, with quantity required and material price attribute and required time point and the cluster of material
The time interval at center calculates similarity, is specifically calculated as：
In formula：MqikFor required time point tiTo the demand of material j, MpkFor the price of material k, MQ is enterprise all
Total demand of the required time point to material.
(4) cluster average value is calculated, calculates the average value of all required time points in each cluster, and by this average value
Rounding is carried out as new cluster centre.Specifically it is calculated as：
In formula：ti (j)To belong to cluster centre μjI-th of required time point, x be divided into cluster centre μjDemand
Time point number, round (x) function representations take the integer nearest apart from variable x.
(5) (3), (4) are executed repeatedly, reach requirement until cluster centre is no longer moved or clustered on a large scale number
Until
(6) output cluster, and count the included required time point set Tc={ Tc of each clusteri| i=1,2,
k}
The work that the solution module (GWO optimization modules) of system carries out, as shown in Figure 2：
Step 3：Initiated purchase scheme Mb is determined according to material requirement information and material variety, and is established according to cluster result
Procurement scheme optimization constraint, specific calculating are as follows：
Wherein：X is the required time point quantity for belonging to cluster centre k, sckjFor calculating the institute to belonging to cluster centre k
Constraint of the having time point to the amount of purchase of material j.
Step 4：Initial scheme is selected, procurement scheme collection S is formed by selecting satisfactory procurement scheme
Step 5：By calculate material procurement payment cost of possession, stock material management cost and production delay cost and
Penalty obtains the fitness value of scheme, it is specific calculate it is as follows：
Fit (x)=F (x)+δ (gen) × H (x)
In formula：δ (gen) H (x) is penalty, and δ (gen) is punishment dynamics, related to the evolutionary generation of GWO algorithms, is taken
Value
Penalty calculation formula is as follows：
qj(x)=max { 0, pj(x)}
pj(x)=hj(x)
Step 6：According to the fitness value of each procurement scheme, GWO optimization algorithm optimization purchases schemes, GWO optimizations are utilized
In the process, improved location update formula is as follows：
D=| C × Xp(t)-X(t)|
X (t+1)=Xp(t)-A×D
In formula：C=2r1, A=2ar2-a
Step 7：To new procurement scheme into row variation, and constrained to new buying side using the optimization obtained in step 3
Case is checked that the fitness value for calculating new departure later is compared replacement with the fitness value of former scheme.Variation rule be：
It is checked by cluster centre, the amount of purchase for each required time point that the cluster centre includes is judged, if amount of purchase is less than
The value sc determined in step 3kj/x, then the amount of purchase of the buying hour point is changed to 0, its buying task amount is assigned randomly to
Other buying hour points that the cluster centre includes.
The work that the result output module of system carries out：
Step 8：Judge whether to obtain satisfied procurement scheme：If obtaining, terminates and calculate, export best fitness value institute
Corresponding procurement scheme, fitness evolution curve and all kinds of production costs, otherwise go to step 6.The procurement scheme of the satisfaction
Refer to the procurement scheme that the fitness value of procurement scheme tends towards stability, it is considered that optimal in continuous 20 iterative process
Fitness value does not change, and judges that fitness tends towards stability.
Above example is merely to illustrate the design philosophy and feature of the present invention, and its object is to make technology in the art
Personnel can understand the content of the present invention and implement it accordingly, and protection scope of the present invention is not limited to the above embodiments.So it is all according to
According to equivalent variations or modification made by disclosed principle, mentality of designing, within protection scope of the present invention.
Claims (7)
1. a kind of equipment manufacture material requirement Design Method, it is characterised in that：It includes the following steps：
Step 1, initialization data set：Initialize material requirement data set Mn, material attribute data collection Mps；
Step 2, according to material requirement data set, determine each material requirement time point, and cluster to time point set, utilize
Improved K_Means algorithms are to material requirement time point clustering, when suitable merging material requirement is carried out the demand of centralized purchasing
Between point tool for one kind；
Step 3：Initiated purchase scheme, and the cluster knot obtained according to step 2 are determined according to material requirement information and material variety
Fruit establishes the optimization constraint of procurement scheme；
Step 4：Procurement scheme collection S is formed by selecting satisfactory procurement scheme；
Step 5：By procurement payment cost of possession, stock material management cost and the production delay cost and the punishment that calculate material
The value of function obtains the fitness of scheme；
Step 6：According to the fitness value of each procurement scheme, the procurement scheme collection obtained using GWO optimization algorithms Optimization Steps 4
S；
Step 7：To the obtained procurement scheme collection S after optimization into row variation, and using the optimization constraint obtained in step 3 to becoming
The procurement scheme inspection in procurement scheme collection S after different, calculates the fitness of new procurement scheme, with initially adopting in step 3
The fitness of purchaser's case is compared replacement；
Step 8：Optimal fitness value does not change in the iterative process of continuous preset times, then judges that fitness tends to
Stablize, then terminates calculating, export the procurement scheme corresponding to optimal fitness value, otherwise go to step 6.
2. equipment manufacture material requirement Design Method according to claim 1, it is characterised in that：The step
2 are specially：
(1) number of clusters k is determined；
(2) select c time point as initial cluster center in required time point set at random；
(3) it is counted with the quantity required of material and material price attribute and the time interval of required time point and initial cluster center
Calculate similarity, by each required time point cluster to in the cluster of its similarity minimum；
(4) calculate the average value of all required time points in each cluster, and by after the processing of this average value as new cluster
Center；
(5) (3), (4) are executed repeatedly, until the number that cluster centre is moved or clustered in a certain range reaches preset quantity
Until；
(6) output cluster, and count the included required time point set Tc of each cluster.
3. equipment manufacture material requirement Design Method according to claim 2, it is characterised in that：(3)
The similarity of each required time point and cluster centre is calculated, specific calculating is as follows：
In formula：MqijFor enterprise in i-th of required time point to the demand of material j, MpjFor the price of material j, MQ is enterprise
In all required time points to the total demand of material, m is the total quantity of material variety, μhFor h-th of cluster centre, tiIt is i-th
A buying hour point,For the distance of i-th buying hour point and h-th of cluster centre；
It is as follows that described (4) calculate new cluster centre formula：
In formula：ti (j)To belong to cluster centre μjI-th of required time point, x be divided into cluster centre μjRequired time
Point number, Round (x) function representations take the integer nearest apart from variable x；MqtijFor required time point tiDemand to material j
Amount, MpjFor the price of material j；M is material variety quantity.
4. equipment manufacture material requirement Design Method according to claim 3, it is characterised in that：The step
The specific formula for calculation of fitness is as follows in 5：
Fit (x)=OC (x)+MC (x)+DC (x)+δ (gen) × H (x)
In formula：OC (x) is procurement payment cost of possession, and MC (x) is stock material management cost, and DC (x) is production tardiness cost,
δ (gen) H (x) is penalty, and δ (gen) is punishment dynamics, value related to the evolutionary generation of GWO algorithms
Wherein, OC (x) calculation formula are as follows：
In formula：MbtijIndicate procurement scheme in required time point tiTo the purchase quantity of material j, iptiMark is in material requirement
Between point tiWhether purchase behavior is had occurred, and f is the fixed cost of single buying, and I is the rate of return on investment of enterprise, tsiFor time point
tiThe time interval of the required time point of distance the latest；N is the quantity of procurement events point；M is the quantity of material variety；
MC (x) calculation formula are as follows：
In formula：Ts is earliest material requirement time point to the time interval at material requirement time point the latest, RqijExist for material j
I-th day quantity in stock, RmjFor the stock control expense of the unit interval of material j；
DC (x) calculation formula are as follows；
DC (x)=dt × dp
In formula：Dt is the production delay time at stop, and dp is the cost of production delay unit interval；
Penalty calculation formula is as follows：
qj(x)=max { 0, pj(x)}
pj(x)=hj(x)
Wherein：H (x) is penalty factor, qj(x) it is violation degree of the procurement scheme to optimization constraint, hj(x) it is procurement scheme pair
Measures of dispersion between the amount of purchase and enterprise demand amount of jth kind material, r (qj(x)) it is strength of punishment, θ (qj(x)) it is that segmentation is reflected
Penetrate function, stajIndicate aggregate demand of the enterprise to jth kind material.
5. equipment manufacture material requirement Design Method according to claim 4, it is characterised in that：The step
6 specific formula for calculation are as follows：
In GWO optimization process, improved location update formula：
D=| C × Xp(t)-X(t)|
X (t+1)=Xp(t)-A×D
In formula：C=2r1, A=2ar2-a
Wherein：D is the distance between grey wolf individual and prey, Xp(t) be t for when prey position, X (t) be t for when ash
The position of wolf individual, X(t+1)For t+1 for when grey wolf individual position, C is constant, be swing the factor, A is convergence factor, r1、r2
For the random number of [0,1], a is to be fitted in grey wolf population as iterations increase from 2 linear decreases to 0, f (α), f (β), f (δ)
The fitness value of the response grey wolf individual of first three, X1、X2、X3Respectively t+1 for when wolf position, Xp(t+1)For t+1 for when prey
Position.
6. equipment manufacture material requirement Design Method according to claim 5, it is characterised in that：The step
7 specific formula for calculation are as follows：
Optimization constraint calculation formula：
In formula：sckjIndicate that k-th of included required time point of cluster concentrates all time points to answer the buying total amount of material j
The constraint of satisfaction.
7. a kind of equipment manufacture material requirement Scheme Design System, it is characterised in that：It includes memory and processor, storage
There is computer program in device, called for the processor, to complete the equipment described in any one of claim 1 to 6
Manufacturing industry material requirement Design Method.
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