CN106611237A - Improved method for solving material purchasing problem in manufacturing industry by using evolutionary programming algorithm - Google Patents
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Abstract
The invention provides an improved method for solving the material purchasing problem in a manufacturing industry by using an evolutionary programming algorithm. The method provided by the invention mainly solves a purchasing problem that the lowest total purchasing cost is lowest on the premise of satisfying constraint conditions, such as the purchasing amount, the ordering period and the fund, when n type goods and materials as shown in the specification are purchased from providers as shown in the specification. By means of the method provided by the invention, the provider reliability is used as the reference standard for making a choice of an initial solution provider; the method is simple and effective; some providers having relatively reliability are abandoned; therefore, the calculation amount of the algorithm is reduced; the searching efficiency of the algorithm is increased; the individual variation quantity is calculated through a Levy flight algorithm; and thus, the calculation result of the algorithm is relatively precise.
Description
Technical field
The present invention relates to business administration field, more particularly to algorithm manufacturing industry material procurement is solved the problems, such as.
Background technology
As world market integration and the arriving of information age, professional production can play its huge effect, look forward to
The proportion of industry buying is also greatly increased, and the importance of buying is increasingly recognized by people.In the world, in industrial undertaking
During product is constituted, the raw material and parts cost of buying is different with industry difference, substantially in 30%-90%, average water
Put down more than 60%.From for world wide, for a typical enterprise, purchase cost (including raw material, parts) will
Account for 60%.And in the industrial undertaking of China, the purchase cost of various goods and materials will account for the 70% of enterprise marketing cost.Obviously buying
Cost is the main body in business administration and core, and buying is the part of " most worthy " in business administration.In addition, according to state
The relevant data that economic and commercial committee of family issues for 1999, if large and medium-sized state-owned enterprise reduces every year purchase cost 2%-3%, can increase
Plus the RMB of benefit more than 500 hundred million, equivalent to state owned industrial enterprise realized profit summation in 1997.Therefore, buying receives society
The suitable attention of meeting all circles, promotes buying research to become one of hot issue of today's society.
Therefore, a kind of efficient intelligent optimization method is studied outstanding to solve material procurement question meaning.
Evolutional programming is a kind of randomized optimization process, be its objective is intelligent by the behavior that reaches of evolving.Evolutional programming is calculated
Method proceeds by search from one group of individuality for randomly generating, and individuality is got over towards in search space by operations such as variation, selections
Carry out the region evolution the closer to global optimum.Evolutionary Programming Algorithm is a kind of maturation with robustness and broad applicability
Global optimization method, with self-organizing, self-optimizing, self study characteristic, can not be limited by problem property, effectively process
The insoluble challenge of traditional optimized algorithm.But, due to excessively selecting, mutation operation destruction is effectively individual and variation is calculated
Son chooses the reason such as improper, and it is low, scarce to initial parameter sensitivity etc. that Evolutionary Programming Algorithm presence is easy to Premature Convergence, search efficiency
Point.
The content of the invention
For the above-mentioned deficiency of prior art, the present invention proposes a kind of improved Evolutionary Programming Algorithm and solves manufacturing industry thing
Material purchasing problem.
The purpose of the present invention is to overcome problems of the prior art：Evolutionary Programming Algorithm exist search efficiency it is low, meter
The shortcomings of calculation precision is not high enough.
The technical scheme that adopted for achieving the above object of the present invention is：A kind of improved Evolutionary Programming Algorithm solves manufacture
Industry material procurement problem.
The step of algorithm, is as follows：
Step 1：Determine procurement criteria：It is determined that purchasing the amount of purchase of each material, usually, procurement criteria is one big
General amount.
Step 2：Select alternative supplier：From supplier select meet amount of purchase constraint and limited fund condition it is alternative
Supplier.
Step 3：Select initial scheme：Procurement scheme collection X, reliability are constituted by the supplier for selecting reliability higher
Relatively low supplier directly gives up.
Step 4：Calculate average fitness and standard deviation：According to target function computing formula, time windows constraints condition, fitness
Function calculates the fitness value average fitness of each schemeAnd standard deviation.
Step 5：Whether obtain being satisfied with procurement scheme：If obtaining, terminate calculating, the i.e. corresponding buying side of output least cost
Case, otherwise goes to step 6.
Step 6：Calculate new procurement scheme amount of variability：The generation of the scheme collection Y of one new procurement scheme composition is by Lay
Tie up flight algorithm to determine.
Step 7：Calculate new fitness value：The adaptation of each scheme in new departure collection Y is calculated by fitness function formula
Angle value.
Step 8：Judge whether individual with the presence of fitness identical in set Φ=X ∪ Y, if nothing, go to step 9, if having,
It is individual to replace repetition fitness value then to produce new individuality.
Step 9：Produce new individual collection：In set Φ=X ∪ Y, individual adaptation degree competitive strategy is taken, select to adapt to
The larger L-N of degree function0Individual scheme constitutes new round procurement scheme collection Z.N0It is new individual in every generation evolutionary process such as
Number.
Step 10：Scheme in X is replaced with into new departure, X=Z+Z ', repeat step 4 arrives step 10.
The invention has the beneficial effects as follows：
1. the reference standard of the choice to initial scheme supplier is used as using supplier's reliability, it is simple effective.
2. the supplier relatively low by giving up some reliabilities, the less amount of calculation of algorithm, improves the search of algorithm
Efficiency.
3. individual variation amount is calculated by using Lay dimension flight algorithm, make algorithm result of calculation more accurate.
Description of the drawings
Fig. 1 calculates manufacturing industry material procurement problem flow chart of determining for a kind of improved Evolve-ment law solution planning
Specific embodiment
In order that the objects, technical solutions and advantages of the present invention become more apparent, enter below with reference to algorithm flow chart
Row in detail, illustrate.
First, the description of material procurement problem
It is provided with n class goods and materials { M1, M2..., MnRespectively from supplier S={ S1..., SnPlace's buying, every kind of goods and materials have m
Individual buying index, such as price and freight.When being purchased, every kind of goods and materials all select an index as referring mainly to
Mark, other indexs are used as reference index.The supplier of different goods and materials how is selected, a procurement scheme X=will be below formulated
{X1, X2..., Xn, Xi={ x1, x2..., xn, Xi∈Si, Si={ Si1, Si2..., Sik, i=1,2 ..., n, k be i-th
Group Supplier Number, on the premise of the constraintss such as amount of purchase, ordering period and fund are met, makes total purchase cost minimum.
Set up plan model as follows：
Object function：
Wherein qi=f (x1, x2..., xm) be the i-th class goods and materials amount of purchase, qixijRepresent the i-th class goods and materials with regard to index j
Cost, xijRepresent j-th buying desired value, C (Xi) represent the i-th class goods and materials purchase cost, C (x*) it is optimum procurement scheme
x*Cost, i.e. optimal cost.
Constraints：
1) amount of purchase constraint：Buyer and supplier allow each index the interval of a floating, i.e.,：xij∈
[T1(j), T2(j)], i=1,2 ..., n；J=1,2 ..., m
T1(j), T2J () is respectively the lower limit and the upper limit of index.
2) limited fund：Need to meet per the procurement payment of class goods and materials：
qi=f (x1, x2..., xm) it is k homogeneous equation, cost function c (qi) reflect purchase cost and amount of purchase it
Between restriction relation,L is purchase cost.
3) time windows constraints：
Wherein, tiFor the volume ordering period of the i-th class goods and materials, t (σ) is the standard deviation of all kinds of materials order phases.Meet algorithm
Fitness function：
fi=C (x*)t(σ), i=1,2 ..., N
2nd, specific implementation step
Step 1：Determine procurement criteria：It is determined that purchasing the amount of purchase of each materialUsually, procurement criteria is one
General amount.
Step 2：Select alternative supplier：From supplier S1, S2..., SnMiddle selection meets amount of purchase constraint with fund about
The alternative supplier of beam condition.
Step 3：Select initial scheme：Procurement scheme collection X, reliability are constituted by the supplier for selecting reliability higher
Relatively low supplier directly gives up.The reliability of supplier is portrayed with criterion difference, and reliability is bigger, then the supplier is
The probability of optimum procurement scheme is bigger.Supplier's reliability is portrayed by material standard deviation.It is specific as follows：
If meeting σi＜ ε, ε are the deviation of regulation, then the supplier i is constituted into a procurement scheme { x1, x2...,
xn, if such as σi＞ ε then give up the supplier.So on, the supplier for meeting deviation range is constituted into initial scheme collection X,
If L=is | X |.
Step 4：Calculate average fitness and standard deviation：According to target function computing formula, time windows constraints condition, fitness
Function calculates the fitness value f of each scheme1, f2..., fL, average fitnessAnd standard deviation.
Step 5：Whether obtain being satisfied with procurement scheme：If obtaining, terminate calculating, the i.e. corresponding buying side of output least cost
Case, otherwise goes to step 6.It is satisfied with procurement scheme to be described as：When certain result of calculation once meets customer requirement, or calculate reach to
Fixed enough evolutionary generations, or the error for connecing is when reaching given precision, scheme now is referred to as satisfied procurement scheme.
As long as buyer is satisfied with to the evaluation result of scheme, scheme now is the solution of algorithm.
Step 6：Calculate new procurement scheme：The generation of the scheme collection Y of L new procurement scheme composition is calculated by Lay dimension flight
Method is determining.It is specific as follows：
The computing formula of individual variation amount：
x′i(j)=xi(j)+α·S
Parameter S is the step-length of random walk, and computing formula is as follows：
Wherein, β is the parameter between [1,2], typically takes β=1.5, u and v Normal Distributions are as follows：
Wherein,
Step 7：Calculate new fitness value：The adaptation of each scheme in new departure collection Y is calculated by fitness function formula
Angle value, fL+1, fL+2..., f2L。
Step 8：Judge whether individual with the presence of fitness identical in set Φ=X ∪ Y, if nothing, go to step 9, if having,
It is individual to replace repetition fitness value then to produce new individuality, produces new individual computing formula：
Step 9：Produce new individual collection：In set Φ=X ∪ Y, individual adaptation degree competitive strategy is taken, select to adapt to
The larger L-N of degree function0Individual scheme constitutes new round procurement scheme collection Z.N0It is new individual in every generation evolutionary process such as
Number, produces new individual and integrates as Z '.New individual collection producing method is：
Step 10：Scheme in X is replaced with into new departure, X=Z+Z ', repeat step 4 arrives step 10.
Claims (6)
1. a kind of improved Evolutionary Programming Algorithm solves the problems, such as manufacturing industry material procurement, the present invention relates to business administration field, tool
It is related to solve the problems, such as manufacturing industry material procurement with algorithm body, it is characterized in that, comprises the steps：
Step 1：Determine procurement criteria：It is determined that purchasing the amount of purchase of each material, usually, procurement criteria is one general
Amount
Step 2：Select alternative supplier：Select to meet amount of purchase constraint and the alternative supply of limited fund condition from supplier
Business
Step 3：Select initial scheme：Constitute procurement scheme collection X by selecting the higher supplier of reliability, reliability compared with
Low supplier directly gives up
Step 4：Calculate average fitness and standard deviation：According to target function computing formula, time windows constraints condition, fitness function
Calculate the fitness value average fitness of each schemeAnd standard deviation
Step 5：Whether obtain being satisfied with procurement scheme：If obtaining, terminate calculating, output least cost is corresponding procurement scheme,
Otherwise go to step 6
Step 6：Calculate new procurement scheme amount of variability：The generation of the scheme collection Y of one new procurement scheme composition is flown by Lay dimension
Line algorithm is determining
Step 7：Calculate new fitness value：The fitness value of each scheme in new departure collection Y is calculated by fitness function formula
Step 8：Judge setIn it is whether individual with the presence of fitness identical, if nothing, go to step 9, if having,
It is individual to replace repetition fitness value to produce new individuality
Step 9：Produce new individual collection：In setIn, individual adaptation degree competitive strategy is taken, select fitness
Function is largerIndividual scheme constitutes new round procurement scheme collection Z,It is new in every generation evolutionary process such as
Body number
Step 10：Scheme in X is replaced with into new departure,Repeat step 4 arrives step 10.
2. manufacturing industry material procurement is solved the problems, such as according to a kind of improved Evolutionary Programming Algorithm described in claim 1, it is special
Levying is, particular content is as follows in the above step 3：
Step 3：Select initial scheme：Constitute procurement scheme collection X by selecting the higher supplier of reliability, reliability compared with
Low supplier directly gives up, and the reliability of supplier is portrayed with criterion difference, and reliability is bigger, then the supplier is for most
The probability of excellent procurement scheme is bigger, and supplier's reliability is portrayed by material standard deviation, specific as follows：
If meeting,For the deviation of regulation, then the supplier i is constituted into a procurement scheme
If such asThen the supplier is given up, so on, the supplier for meeting deviation range is constituted into initial scheme collection X, if
L=|X|。
3. manufacturing industry material procurement is solved the problems, such as according to a kind of improved Evolutionary Programming Algorithm described in claim 1, it is special
Levying is, particular content is as follows in the above step 5：
Step 5：Whether obtain being satisfied with procurement scheme：If obtaining, terminate calculating, output least cost is corresponding procurement scheme,
6 are otherwise gone to step, procurement scheme is satisfied with and is described as:When certain result of calculation once meets customer requirement, or calculate reach it is given
Enough evolutionary generations, or the error for connecing is when reaching given precision, and scheme now is referred to as satisfied procurement scheme, only
Buyer is wanted to be satisfied with the evaluation result of scheme, scheme now is the solution of algorithm.
4. manufacturing industry material procurement is solved the problems, such as according to a kind of improved Evolutionary Programming Algorithm described in claim 1, it is special
Levying is, concrete calculating process is as follows in the above step 6：
Step 6：Calculate new procurement scheme：The generation of the scheme collection Y of L new procurement scheme composition ties up flight algorithm by Lay
It is specific as follows to determine：
The computing formula of individual variation amount：
Parameter S is the step-length of random walk, and computing formula is as follows：
Wherein,It is the parameter between [1,2], typically takesU and v Normal Distributions, it is as follows：
Wherein,
。
5. manufacturing industry material procurement is solved the problems, such as according to a kind of improved Evolutionary Programming Algorithm described in claim 1, it is special
Levying is, concrete calculating process is as follows in the above step 8：
Step 8：Judge setIn it is whether individual with the presence of fitness identical, if nothing, go to step 9, if having,
It is individual to replace repetition fitness value then to produce new individuality, produces new individual computing formula：
。
6. manufacturing industry material procurement is solved the problems, such as according to a kind of improved Evolutionary Programming Algorithm described in claim 1, it is special
Levying is, concrete calculating process is as follows in the above step 9：
Step 9：Produce new individual collection：In setIn, individual adaptation degree competitive strategy is taken, select to adapt to
Degree function is largerIndividual scheme constitutes new round procurement scheme collection Z,It is such as new in every generation evolutionary process
Number of individuals, producing new individual collection is, new individual collection producing method is：
。
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112308404A (en) * | 2020-10-29 | 2021-02-02 | 广东电网有限责任公司 | Project risk management method and device, electronic equipment and storage medium |
| CN113420947A (en) * | 2021-04-08 | 2021-09-21 | 国网物资有限公司 | Evaluation method and device for electrician equipment suppliers based on Internet of things |
-
2016
- 2016-06-24 CN CN201610478758.5A patent/CN106611237A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112308404A (en) * | 2020-10-29 | 2021-02-02 | 广东电网有限责任公司 | Project risk management method and device, electronic equipment and storage medium |
| CN112308404B (en) * | 2020-10-29 | 2023-02-17 | 广东电网有限责任公司 | Project risk management method and device, electronic equipment and storage medium |
| CN113420947A (en) * | 2021-04-08 | 2021-09-21 | 国网物资有限公司 | Evaluation method and device for electrician equipment suppliers based on Internet of things |
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Application publication date: 20170503 |