CN108985486A - A kind of optimization method and device of Closed Loop Supply Chain system cost - Google Patents
A kind of optimization method and device of Closed Loop Supply Chain system cost Download PDFInfo
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Abstract
The present embodiments relate to logistics technology, disclose a kind of optimization method of Closed Loop Supply Chain system cost, comprising: establish to minimize Closed Loop Supply Chain system cost as the mathematical model of target；Mathematical model is solved using searching algorithm；Optimal addressing and the optimum macro of the optimal addressing of manufactory and optimum macro, the optimal addressing and optimum macro and logistics center that remanufacture factory in Closed Loop Supply Chain system are determined according to the solving result of acquisition.By establishing to minimize Closed Loop Supply Chain system cost as the mathematical model of target, and obtained solving result is solved for mathematical model, the optimal addressing of the manufactory in Closed Loop Supply Chain system and optimal addressing and the optimum macro of optimum macro, the optimal addressing and optimum macro and logistics center that remanufacture factory are defined, the minimum of Closed Loop Supply Chain system cost is realized.Therefore, have the management and decision of science in terms of Facilities Construction and transportation cost, and save cost.
Description
Technical field
The present embodiments relate to logistics technology, in particular to a kind of optimization method of Closed Loop Supply Chain system cost
And device.
Background technique
In recent years, due to the enhancing of people's environmental consciousness, sustainable development has become the theme of current social development, tradition
The limitation for supplying chain pattern is increasingly obvious, has constrained the development of society.Closed Loop Supply Chain as a kind of realization it is economical with
The mode of harmonious development has attracted the extensive concern of academia and industry.
General supply chain refers to the forward direction net from the purchasing of raw materials, intermediate products and production, final sales to customer
Network structure, and Closed Loop Supply Chain then refers to including preceding to supply chain and using the product of its end customer as starting point, by returning goods,
Logistics, cash flow and the information flow directly recycle, repair, remanufacturing, recycling recycling or waste treatment and formed close
Loop system.
At least there are the following problems in the prior art for inventor's discovery: existing relevant to Closed Loop Supply Chain location problem
Most of researchs usually require that the demand of each customer site can only be distributed or be collected by a logistics center, and each manufacture
Factory remanufactures factory and also usually requires that and only transports product, the in addition design of closed-loop system in practical applications by logistics center
It is mainly designed by rule of thumb by staff, lacks the management and decision of science, caused in terms of Facilities Construction and transportation cost
Sizable waste.
Summary of the invention
A kind of optimization method and device for being designed to provide Closed Loop Supply Chain system cost of embodiment of the present invention, makes
It obtains by establishing to minimize Closed Loop Supply Chain system cost as the mathematical model of target, and obtained for mathematical model solution
Solving result defines the optimal addressing of the manufactory in Closed Loop Supply Chain system and optimum macro, remanufactures factory most
It is preferred that optimal addressing and the optimum macro of location and optimum macro and logistics center, realize Closed Loop Supply Chain system cost
It minimizes, has the management and decision of science in terms of Facilities Construction and transportation cost, and save cost.
In order to solve the above technical problems, embodiments of the present invention provide a kind of optimization of Closed Loop Supply Chain system cost
Method, comprising the following steps: establish to minimize Closed Loop Supply Chain system cost as the mathematical model of target；Using searching algorithm
Solve mathematical model；The optimal addressing of manufactory and best rule in Closed Loop Supply Chain system are determined according to the solving result of acquisition
Mould, the optimal addressing for remanufacturing factory and the optimal addressing of optimum macro and logistics center and optimum macro；Wherein, mathematical modulo
Type include: indicate Closed Loop Supply Chain system cost and manufactory addressing and Scale Decision-making variable, remanufacture the addressing of factory with
And Scale Decision-making variable and logistics center addressing and Scale Decision-making variable relation objective function.
Embodiments of the present invention additionally provide a kind of optimization device of Closed Loop Supply Chain system cost, comprising: model is built
Formwork erection block, for establishing to minimize Closed Loop Supply Chain system cost as the mathematical model of target；Model solution module, for adopting
Mathematical model is solved with searching algorithm；Determining module determines that Closed Loop Supply Chain system manufactures for the solving result according to acquisition
The optimal addressing of factory and optimum macro, the optimal addressing and optimum macro and logistics center that remanufacture factory optimal addressing with
And optimum macro；Wherein, mathematical model includes: addressing and the Scale Decision-making for indicating Closed Loop Supply Chain system cost and manufactory
The target of variable, the addressing for remanufacturing factory and the addressing of Scale Decision-making variable and logistics center and Scale Decision-making variable relation
Function.
Embodiment of the present invention is to minimize Closed Loop Supply Chain system cost in terms of existing technologies, by establishing
The mathematical model of target, and obtained solving result is solved for mathematical model, it defines and is manufactured in Closed Loop Supply Chain system
The optimal addressing of factory and optimum macro, the optimal addressing and optimum macro and logistics center that remanufacture factory optimal addressing with
And optimum macro, realize the minimum of Closed Loop Supply Chain system cost.Therefore, have in terms of Facilities Construction and transportation cost
The management and decision of standby science, and save cost.
In addition, mathematical model further include: bound for objective function.By the way that constraint condition is arranged in mathematical model,
The premise that objective function is set up is determined, thus by being more in line with practical feelings to mathematics model solution solving result obtained
Condition.
In addition, Closed Loop Supply Chain system cost includes: fixed cost and operation cost.
In addition, fixed cost includes: to establish the fixed cost of manufactory, establish the fixed cost for remanufacturing factory and establish object
The fixed cost of flow center；Operation cost includes: manufactory and logistics center in the positive transmission direction of Closed Loop Supply Chain system
Between production cost and transportation cost, Closed Loop Supply Chain system reverse transmission direction on logistics center and remanufacture between factory
Reproduction cost and transportation cost, Closed Loop Supply Chain system positive transmission direction on processing between logistics center and customer
Processing cost in the reverse transmission direction of cost and transportation cost and Closed Loop Supply Chain system between customer and logistics center
And transportation cost.When determining Closed Loop Supply Chain system cost, not only allows for manufactory, remanufactures factory and logistics center consolidates
Determine cost, it is also contemplated that the operation cost in reverse transmission direction and positive transmission direction in Closed Loop Supply Chain system, to whole
The determination of a Closed Loop Supply Chain system cost is more comprehensive, therefore the mathematical model established is more in line with actual conditions.
In addition, searching algorithm includes TABU search heuritic approach.When being solved to the mathematical model having built up,
It is solved using TABU search heuritic approach, the solving result very close to optimal solution, and solving speed can be obtained
Faster compared to existing solver.
In addition, solving mathematical model using searching algorithm, comprising: the initial value of setting current iteration number and the current overall situation
Optimal solution does not change the initial value of number；The initial solution of mathematical model is obtained, and using initial solution as current solution, wherein when
Preceding solution is current globally optimal solution；Judgement search whether plain algorithm meets termination condition, if so, using current globally optimal solution as
Otherwise solving result carries out neighborhood search to current solution, obtains neighborhood solution；After obtaining neighborhood solution, whether neighborhood solution is judged
Greater than current globally optimal solution, if so, current globally optimal solution is replaced with neighborhood solution, otherwise, by current globally optimal solution
Do not change number and adds one；Judge whether the number that globally optimal solution does not change is more than or equal to preset threshold, if so, obtaining again
The initial solution of mathematical model is obtained, and using the initial solution as current solution, while globally optimal solution not changed to number setting
It is zero, otherwise, current iteration number is added one, and rejudge whether searching algorithm meets termination condition.
In addition, obtaining the initial solution of mathematical model, comprising: the addressing of manufactory and Scale Decision-making variable remanufacture factory
Addressing and Scale Decision-making variable and logistics center addressing and Scale Decision-making variable, the unknown change as mathematical model
Amount obtains the initial solution of mathematical model by initializing known variables.
In addition, using initial solution as currently solving after, comprising: calculate and currently solve the numerical value of corresponding objective function,
And empty introduce taboo list.
In addition, carrying out neighborhood search to current solution, comprising: generate the initial neighborhood solution currently solved, and at the beginning of calculating each
The numerical value of the corresponding objective function of beginning neighborhood solution；The numerical value of each corresponding objective function of initial neighborhood solution is ranked up,
And sequentially select, determine initial neighborhood solution corresponding to the numerical value of the smallest objective function, and by the number of the smallest objective function
The neighborhood solution that the corresponding initial neighborhood solution of value is obtained as neighborhood search.
Detailed description of the invention
One or more embodiments are illustrated by the picture in corresponding attached drawing, these exemplary theorys
The bright restriction not constituted to embodiment, the element in attached drawing with same reference numbers label are expressed as similar element, remove
Non- to have special statement, composition does not limit the figure in attached drawing.
Fig. 1 is the flow chart of the optimization method of Closed Loop Supply Chain system cost in the application first embodiment；
Fig. 2 is the flow chart of the optimization method of Closed Loop Supply Chain system cost in the application second embodiment；
Fig. 3 is the block diagram of the optimization device of Closed Loop Supply Chain system cost in the application 3rd embodiment；
Fig. 4 is the block diagram of the optimization device of Closed Loop Supply Chain system cost in the application fourth embodiment.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with attached drawing to the present invention
Each embodiment be explained in detail.However, it will be understood by those skilled in the art that in each embodiment party of the present invention
In formula, in order to make the reader understand this application better, many technical details are proposed.But even if without these technical details
And various changes and modifications based on the following respective embodiments, the application technical solution claimed also may be implemented.
The first embodiment of the present invention is related to a kind of optimization methods of Closed Loop Supply Chain system cost.Detailed process is as schemed
Shown in 1, comprising the following steps:
Step 101, it establishes to minimize Closed Loop Supply Chain system cost as the mathematical model of target.
Specifically, in the present embodiment, mathematical model include: the addressing of Closed Loop Supply Chain system cost and manufactory with
And Scale Decision-making variable, the addressing of the addressing and Scale Decision-making variable and logistics center that remanufacture factory and Scale Decision-making variable
The objective function of relationship.Meanwhile mathematical model further include: bound for objective function.
It should be noted that the Closed Loop Supply Chain system cost in present embodiment includes fixed cost and operation cost.
Wherein, fixed cost includes: to establish the fixed cost of manufactory, establish the fixed cost for remanufacturing factory and establish logistics center
Fixed cost.Operation cost includes: the life in the positive transmission direction of Closed Loop Supply Chain system between manufactory and logistics center
Produce cost and transportation cost, Closed Loop Supply Chain system reverse transmission direction on logistics center and remanufacture the reproduction between factory
Cost and transportation cost, Closed Loop Supply Chain system positive transmission direction on processing cost and fortune between logistics center and customer
Processing cost in the reverse transmission direction of defeated cost and Closed Loop Supply Chain system between customer and logistics center and transport at
This.
In the specific implementation, objective function is indicated with formula (1):
Wherein, TC indicates the cost of Closed Loop Supply Chain system, αs,aIndicate addressing and the Scale Decision-making variable of manufactory,
βs,bExpression remanufactures addressing and the Scale Decision-making variable of factory, γl,cIndicate addressing and the Scale Decision-making variable of logistics center.
Wherein,Indicate fixed cost, its remainder in formula (1)
Indicate operation cost.The fixed cost of manufactory is established in expression,It indicates to establish and remanufactures factory
Fixed cost,The fixed cost of logistics center is established in expression.
Indicate fortune
Seek in cost in the positive transmission direction of Closed Loop Supply Chain system production cost between manufactory and logistics center and transport at
This,
Indicate Closed Loop Supply Chain system in operation cost
Logistics center and the reproduction cost and transportation cost between factory are remanufactured in the reverse transmission direction of system,
It indicates in operation cost
Processing cost and transportation cost in the positive transmission direction of Closed Loop Supply Chain system between logistics center and customer,
It indicates to close in operation cost
Processing cost and transportation cost in the reverse transmission direction of ring supply chain system between customer and logistics center.
Wherein, the meaning of each symbol is respectively as follows: d in formula (1)w,k,pIndicate demand number of the customer to product p at scene w
Amount, sw,k,pIndicate return of goods quantity of the customer k to product p, g at scene ws,lIndicate to transport a truck product from place s to place
L cost, gl,sIndicate to transport a truck product from place l to place s cost, gl,kIndicate from place l transport a truck product to
Place k cost, gk,lIt indicates from place k one truck product of transport to place l cost,Indicating that s opens up scale in place is a's
The fixed cost of manufactory,It indicates to open up the fixed cost for remanufacturing factory that scale is b, f in the place sl,cIt indicates in the place l
The fixed cost for the logistics center that scale is c is opened up,In the place s and manufactory that scale is a manufacture the unit of product p at
This,The unit cost for remanufacturing factory and remanufacturing product p that expression is b in the place s and scale,In the place l and scale
For c logistics center in feedforward network to the processed in units cost of requirement product p,In the place l and scale is the logistics of c
Center is in inverse network to the processed in units cost of returned work p, rs,pIndicate that product p returns in manufactory/remanufacture factory s
Yield, hpIndicate the unit stockholding cost of product p in each period, epTruck capacity needed for indicating unit product p, ts,l
It indicates from place s to the haulage time of place l, tl,sIt indicates from place l to the haulage time of place s, tl,kIndicate from place l to
The haulage time of place k, tk,lIt indicates from place k to the haulage time of place l, probwIndicate the probability of scene；
It should be noted that αs,aIt is no equal to 1 if opening up the manufactory that scale is a at the s of place for 0-1 variable
Then it is equal to 0, βs,bFor 0-1 variable, factory is remanufactured for b if opening up scale at the s of place, is equal to 1, is otherwise equal to 0,
γl,cIt is equal to 1, θ if opening up the manufactory that scale is c at the l of place for 0-1 variablew,l,k,pIt indicates at scene w, cares for
The quantity that demand of the objective k to product p is dispensed by logistics center l accounts for the ratio of product p demand total quantity, λw,k,l,pIt indicates
Under scene w, customer k to the ratio that the return of goods of product p are that the quantity collected by logistics center l accounts for product p return of goods total quantity,
μw,s,l,pIt indicates at scene w, the product p of manufactory s production is the quantity dispensed by logistics center l, vw,l,s,pIndicate on the scene
Under scape w, the quantity of manufactory s is sent in the product p of logistics center l.
It is noted that mathematical model further includes bound for objective function, by setting constraint condition, so that logical
It crosses and actual conditions is more in line with to mathematics model solution optimal solution obtained.
In the specific implementation, including: for the constraint condition of objective function (1) setting
Wherein, the meaning of formula (2) each symbol into formula (15) are as follows:The manufacture that expression is a in the place s and scale
Factory to the manufacturing capacity of product p,The factory that remanufactures for indicating that in the place s and scale is b remanufactures ability to product p,Indicate logistics center that in the place l and scale is c in feedforward network to requirement product processing capacity,It indicates in l
The logistics center that point and scale are c is in inverse network to returned work processing capacity, vpIndicate the unit volume of product p.
It should be noted that constraint condition (2) indicates that a manufactory can only be opened up in the candidate locations of a manufactory,
Constraint condition (3) indicates that the candidate locations that factory is remanufactured at one can only open up one and remanufacture factory, and constraint condition (4) indicates
One logistics center's candidate locations can only open up a logistics center, and constraint condition (5) guarantee one, which remanufactures factory, to build
The place of manufactory is chosen as at one, constraint condition (6) guarantees that the product demand quantity of each customer is distributed each
The sum of ratio of logistics center is 1, and constraint condition (7) guarantees ratio of the return of goods quantity distribution in each logistics center of each customer
The sum of rate is 1, and constraint condition (8) guarantees that the product quantity that outputs and inputs of each logistics center keeps equal in forward direction supply chain
Weighing apparatus, constraint condition (9) guarantee that the product quantity that outputs and inputs of each logistics center is kept in balance in reverse supply chain, constrain
Condition (10) and (11) guarantee the product total volume for being transported to logistics center no more than processing capacity, and constraint condition (12) guarantees
The production capacity restrictive condition of manufactory, constraint condition (13) guarantee to remanufacture the production capacity restrictive condition of factory, constraint condition (14) and
(15) domain of decision variable is defined.
It should be noted that check cost is not considered in present embodiment in founding mathematical models, and checking is pair
Return of goods product checked, therefore can only be occurred in the reverse transmission direction of Closed Loop Supply Chain system.Therefore in the mathematics of foundation
It is contemplated that being checked respectively in manufactory, logistics center and customer location on the basis of model, to establish with inspection
The mathematical model of cost.
In the specific implementation, when manufactory is checked, the objective function of the mathematical model with check cost are as follows:
Wherein,Indicate the unit check cost of each product at manufacturer s.Such case indicate, manufactory into
Row checks, after inspection, product section r can be recycleds,pIt is remanufactured, rest part is processed.
When logistics center is checked, the objective function of the mathematical model with check cost are as follows:
Constraint condition (9) becomes:
Wherein,Indicate logistics center l to the unit check cost of product p.Such case indicates that all return of goods produce
Product are checked in logistics center, and only recyclable product, which is just transported to, remanufactures factory and produced.
When being checked in customer location, the objective function of the mathematical model with check cost are as follows:
Constraint condition (9) becomes:
Constraint condition (11) becomes:
Wherein,Indicate the unit check cost of the product p at customer k.Such case indicates that all returned works exist
Customer site is checked.Therefore, only accounting is rk,pPartial product is transported to by logistics center remanufactures factory's progress
It remanufactures.
It should be noted that the mathematical model with check cost is further contemplated on the basis of mathematical model
It checks the difference in place and establishes.It is similar to the general idea of founding mathematical models in the application that it establishes mode, and is building
When vertical mathematical model, other related factors of Closed Loop Supply Chain system cost can also be considered simultaneously, it is therefore, no longer superfluous herein
It states.And the present embodiment is then primarily directed to the foundation of mathematical model and solution.
Step 102, mathematical model is solved using searching algorithm.
Specifically, in the present embodiment, with three decision variable αs,a、βs,bAnd γl,cAs in mathematical model not
Know variable, (the α of one group of determination is solved by searching algorithms,a, βs,b, γl,c) make Closed Loop Supply Chain system in objective function
Cost reaches minimum.(the α of the determinations,a, βs,b, γl,c) it can serve as one group of best solution.
It is solved it is noted that other algorithms can be used, to obtain solving result, and is determined according to solving result
Suitable solution, for example, genetic algorithm and ant group algorithm etc..The specific shape of present embodiment not limit search algorithm
Formula obtains solving result as long as can solve by algorithm, in protection scope all in this application.
Step 103, the optimal addressing of manufactory and most is determined in Closed Loop Supply Chain system according to the solving result of acquisition
Good scale, the optimal addressing for remanufacturing factory and the optimal addressing of optimum macro and logistics center and optimum macro.
Specifically, obtained solving result will be solved by searching algorithm, define in Closed Loop Supply Chain system
Manufactory, the optimal location and optimum macro for remanufacturing factory and logistics center, realize Closed Loop Supply Chain system cost most
Smallization.
Compared with prior art, present embodiment, by establishing to minimize Closed Loop Supply Chain system cost as target
Mathematical model, and obtained solving result is solved for mathematical model, define the manufactory in Closed Loop Supply Chain system
Optimal addressing and optimum macro, the optimal addressing of the optimal addressing and optimum macro and logistics center that remanufacture factory and most
Good scale realizes the minimum of Closed Loop Supply Chain system cost.Therefore, has section in terms of Facilities Construction and transportation cost
Management and decision, while realizing the purpose for saving cost.
Second embodiment of the present invention is related to a kind of optimization method of Closed Loop Supply Chain system cost.The present embodiment is
It is further improved on the basis of one embodiment, specific improvements are as follows: to the side for solving mathematical model using searching algorithm
Formula has been described in detail.The process of the optimization method of Closed Loop Supply Chain system cost in the present embodiment is as shown in Figure 2.Specifically
Say, in the present embodiment, including step 201, to step 213, the step 101 wherein in step 201 and first embodiment is big
Cause identical, step 213 is roughly the same with the step 103 in first embodiment, and details are not described herein again, mainly introduces below different
Place, the not technical detail of detailed description in the present embodiment, reference can be made to Closed Loop Supply Chain system provided by first embodiment
The optimization method for cost of uniting, details are not described herein again.
After step 201, step 202 is executed.
In step 202, the initial value and current globally optimal solution that current iteration number is arranged do not change the first of number
Initial value.
It should be noted that current iteration number is indicated with letter n, current optimal solution does not change number letter m table
Show.Therefore, when searching algorithm starts to solve mathematical model, current iteration frequency n=1, current globally optimal solution are set first
Number m=0 is not changed.
In step 203, the initial solution of mathematical model is obtained, and using initial solution as current solution, and currently solution is to work as
Preceding globally optimal solution.
It should be noted that in present embodiment, by the addressing of manufactory and Scale Decision-making variable αs,a, remanufacture factory
Addressing and Scale Decision-making variable βs,bAddressing and Scale Decision-making variable γ with logistics centerl,c, as mathematical model
Core known variables.Wherein, with αs,aFor, it indicates two decisions, and s is the place of the manufactory of decision, and a is the system of decision
Make the scale of factory, and αs,aComprising a variety of situations, these different situations are used | S | | A | a dimension indicates, when solution
Can be first by this | S | | A | the numerical value of dimension is converted into αs,aNumerical value, to acquire αs,aInitial solution.
For example, | S | | A | the numerical value of dimension is i/ (S | -1), therefore the integer part of i/ (S | -1), a table can be indicated with s
Show the complementing part of i/ (S | -1).If the integer part of i-th dimension is equal to 1, α is just sets,a=1, i.e., one is established at the s of place
A scale is the manufactory of a, otherwise, α is arrangeds,a=0,.Equally, for βs,bAnd γl,cThe mode and solution of the initial solution of acquisition
αs,aMode it is identical, details are not described herein again.
It is noted that using initial solution as current solution after, can be acquired by solver currently solve it is corresponding
The numerical value of objective function, while introduce taboo list is emptied, such as setting αs,aIntroduce taboo listβ is sets,bIntroduce taboo listγ l is set,cIntroduce taboo listAnd the length that each introduce taboo list is arranged is L.
In step 204, judge whether searching algorithm meets termination condition, if satisfied, thening follow the steps 205, otherwise hold
Row step 212.
Specifically, the termination of algorithm is realized in algorithm by setting maximum number of iterations N, wherein N can be 200,
When current iteration frequency n is equal to N, illustrate that searching algorithm meets termination condition, if current iteration frequency n is not equal to N, illustrates to search
Rope algorithm does not meet termination condition.
In step 205, neighborhood search is carried out to current solution, obtains neighborhood solution.
It should be noted that the concrete mode for carrying out neighborhood search is, mobile search is carried out since current solution, looks for and works as
Satisfactory solution near preceding solution to generate the initial neighborhood solution currently solved, and calculates each initially by solver
The numerical value of the corresponding objective function of neighborhood solution.By the numerical value of each corresponding objective function of initial neighborhood solution be ranked up and according to
Sequence selection, determines initial neighborhood solution corresponding to the numerical value of the smallest objective function, the neighborhood solution obtained as neighborhood search.
It should be noted that determine neighborhood solution not in introduce taboo list, then using neighborhood solution as new current solution, simultaneously
Update introduce taboo list；Or neighborhood search solution is in introduce taboo list, but neighborhood solution meets aspiration criterion, then using neighborhood solution as new
Current solution, while updating introduce taboo list；Or neighborhood solution in introduce taboo list and is unsatisfactory for aspiration criterion, but neighborhood solution satisfaction is relaxed
Criterion then using neighborhood solution as new current solution, while updating introduce taboo list.
It is noted that the element in introduce taboo list is continually changing, imitation during carrying out neighborhood search
Man memory function, the solution that algorithm was once searched for can exist in introduce taboo list, and are stored in taboo column after a period of time
Solution in table can release, and this holding time can be indicated with the length L of introduce taboo list.Plain process is being searched every time
In, it was searched for before explanation if element is stored in introduce taboo list, and corresponding target function value is not than being obtained
Global optimum's target function value it is not bad, and be unsatisfactory for relaxed criteria, then this movement is not received, which is to be not involved in
This algorithm search.
In step 206, judge whether neighborhood solution is greater than current globally optimal solution, if so, 207 are thened follow the steps, otherwise,
Execute step 208.
In step 207, current globally optimal solution is replaced with into neighborhood solution.
It should be noted that being needed to reset current full while current globally optimal solution is replaced with neighborhood solution
It is 0 that office's optimal solution, which does not change number,.
In a step 208, current globally optimal solution is not changed into number and adds one.
In step 209, judge that globally optimal solution does not change whether number is more than or equal to preset threshold, if so, holding
Otherwise row step 210 executes step 211.
It should be noted that preset threshold is set as M, wherein M can be 10, that is, judge that current globally optimal solution does not change
Whether the number m of change is more than or equal to M, the precision that the specific value of certain preset threshold M can be solved by user according to algorithm, from
Row is configured, and present embodiment does not limit the specific value of preset threshold.
It should be noted that determining that number that globally optimal solution does not change is more than or equal to preset threshold M, then it will be current
Globally optimal solution does not change number and is set as 0, and regains the initial solution of mathematical model.By regaining initial solution
Mode can widely cover the space entirely solved, rather than be only confined in during carrying out algorithm search
The region of some part, prevents region of search too local, therefore the initial solution by regaining mathematical model, it is ensured that logical
Cross the accuracy of the solving result of algorithm acquisition.
In step 210, the initial solution of mathematical model is regained, and using initial solution as current solution, while will be current
Globally optimal solution does not change number and is set as zero.
It should be noted that regained in step 210 initial solution of mathematical model mode and step 203 in obtain number
The initial solution mode for learning model is similar, but will not solve currently as current globally optimal solution in step 210.
In step 211, current iteration number is added one.
It should be noted that after by the operation of the execution of current iteration number plus one 204 can be re-execute the steps, judgement
Whether new the number of iterations reaches the maximum value N of setting.
In the step 212, using current globally optimal solution as solving result.
It should be noted that then algorithm stopping is searched when searching algorithm meets termination condition, i.e. current iteration frequency n=N
Rope, and using current globally optimal solution as the solving result of mathematical model.
In step 213, determined according to the solving result of acquisition the optimal addressing of manufactory in Closed Loop Supply Chain system with
And optimal addressing and the optimum macro of optimum macro, the optimal addressing and optimum macro and logistics center that remanufacture factory.
Compared with prior art, present embodiment, by establishing to minimize Closed Loop Supply Chain system cost as target
Mathematical model, and obtained solving result is solved for mathematical model, define the manufactory in Closed Loop Supply Chain system
Optimal addressing and optimum macro, the optimal addressing of the optimal addressing and optimum macro and logistics center that remanufacture factory and most
Good scale realizes the minimum of Closed Loop Supply Chain system cost.And mathematical modulo is solved using TABU search heuritic approach
Type, so that the optimal solution for solving the mathematical model obtained is more accurate.
The step of various methods divide above, be intended merely to describe it is clear, when realization can be merged into a step or
Certain steps are split, multiple steps are decomposed into, as long as including identical logical relation, all in the protection scope of this patent
It is interior；To adding inessential modification in algorithm or in process or introducing inessential design, but its algorithm is not changed
Core design with process is all in the protection scope of the patent.
Third embodiment of the invention is related to a kind of optimization device of Closed Loop Supply Chain system cost, and specific structure is as schemed
Shown in 3.
As shown in figure 3, the optimization device of Closed Loop Supply Chain system cost includes: model building module 301, model solution mould
Block 302 and determining module 303.
Wherein, model building module 301, for establishing to minimize Closed Loop Supply Chain system cost as the mathematical modulo of target
Type.
Wherein, mathematical model includes: to indicate that the addressing of Closed Loop Supply Chain system cost and manufactory and Scale Decision-making become
Measure, remanufacture the target letter of the addressing of factory and the addressing of Scale Decision-making variable and logistics center and Scale Decision-making variable relation
Number.
It should be noted that mathematical model further include: bound for objective function.
Closed Loop Supply Chain system cost includes fixed cost and operation cost.Wherein, fixed cost includes: to establish manufactory
Fixed cost, establish and remanufacture the fixed cost of factory and establish the fixed cost of logistics center.Operation cost includes: that closed loop supplies
Answer the production cost and transportation cost, Closed Loop Supply Chain system in the positive transmission direction of catenary system between manufactory and logistics center
Logistics center and the reproduction cost and transportation cost, Closed Loop Supply Chain system between factory are remanufactured in the reverse transmission direction of system
Positive transmission direction on processing cost between logistics center and customer and transportation cost and Closed Loop Supply Chain system it is inverse
Processing cost and transportation cost in transmission direction between customer and logistics center.
Model solution module 302, for solving mathematical model using searching algorithm.
Determining module 303 determines that manufactory is most preferably in Closed Loop Supply Chain system for the solving result according to acquisition
Location and optimum macro, the optimal addressing of the optimal addressing and optimum macro and logistics center that remanufacture factory and best rule
Mould.
It is not difficult to find that present embodiment is Installation practice corresponding with first embodiment, present embodiment can be with
First embodiment is worked in coordination implementation.The relevant technical details mentioned in first embodiment still have in the present embodiment
Effect, in order to reduce repetition, which is not described herein again.Correspondingly, the relevant technical details mentioned in present embodiment are also applicable in
In first embodiment.
Four embodiment of the invention is related to a kind of optimization device of Closed Loop Supply Chain system cost.The embodiment and the
Three embodiments are roughly the same, and specific structure is as shown in Figure 4.Wherein, mainly the improvement is that: the 4th embodiment is to third
Model solution module 302 in embodiment has been described in detail.Shown in Fig. 4, model solution module 302 includes parameter setting
Module 3021, initial solution obtain module 3022, first judgment module 3023, neighborhood search module 3024, the second judgment module
3025 and third judgment module 3026.
Parameter setting module 3021, initial value and current globally optimal solution for current iteration number to be arranged do not change
The initial value of number.
Initial solution obtains module 3022, solves for obtaining the initial solution of mathematical model, and using initial solution as current,
In, current solution is current globally optimal solution.
First judgment module 3023 searches whether plain algorithm meets termination condition for judging, if so, most by the current overall situation
Excellent solution is used as solving result, otherwise, carries out neighborhood search to current solution using neighborhood search module 3024, obtains neighborhood solution.
Neighborhood search module 3024 for generating the initial neighborhood solution currently solved, and calculates each initial neighborhood solution pair
The numerical value for the objective function answered；The numerical value of each corresponding objective function of initial neighborhood solution is ranked up, and is sequentially selected,
Determine initial neighborhood solution corresponding to the numerical value of the smallest objective function, and will be first corresponding to the numerical value of the smallest objective function
The neighborhood solution that beginning neighborhood solution is obtained as neighborhood search.
Second judgment module 3025, for judging whether neighborhood solution is greater than globally optimal solution, if so, most by the current overall situation
Excellent solution replaces with neighborhood solution, otherwise, current globally optimal solution is not changed number and adds one.
Third judgment module 3026, for judging whether the number that globally optimal solution does not change is more than or equal to default threshold
Value if so, regaining the initial solution of mathematical model, and using initial solution as current solution, while globally optimal solution not being had
Change number and be set as zero, otherwise, current iteration number is added one, and rejudge search using first judgment module 3023 and calculate
Whether method meets termination condition.
It is not difficult to find that present embodiment is Installation practice corresponding with second embodiment, present embodiment can be with
Second embodiment is worked in coordination implementation.The relevant technical details mentioned in second embodiment still have in the present embodiment
Effect, in order to reduce repetition, which is not described herein again.Correspondingly, the relevant technical details mentioned in present embodiment are also applicable in
In second embodiment.
It is noted that each module involved in present embodiment is logic module, and in practical applications, one
A logic unit can be a physical unit, be also possible to a part of a physical unit, can also be multiple physics lists
The combination of member is realized.In addition, in order to protrude innovative part of the invention, it will not be with solution institute of the present invention in present embodiment
The technical issues of proposition, the less close unit of relationship introduced, but this does not indicate that there is no other single in present embodiment
Member.
The 5th embodiment of the application is related to a kind of computer readable storage medium, in the computer readable storage medium
It is stored with computer program, which can be realized when being executed by processor involved in any means embodiment of the present invention
Closed Loop Supply Chain system cost optimization method.
It will be understood by those skilled in the art that implementing the method for the above embodiments is that can pass through
Program is completed to instruct relevant hardware, which is stored in a storage medium, including some instructions are used so that one
A equipment (can be single-chip microcontroller, chip etc.) or processor (processor) execute each embodiment the method for the application
All or part of the steps.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only
Memory), random access memory (RAM, Random Access Memory), magnetic or disk etc. are various can store journey
The medium of sequence code.
It will be understood by those skilled in the art that the respective embodiments described above are to realize specific embodiments of the present invention,
And in practical applications, can to it, various changes can be made in the form and details, without departing from the spirit and scope of the present invention.
Claims (10)
1. a kind of optimization method of Closed Loop Supply Chain system cost characterized by comprising
It establishes to minimize Closed Loop Supply Chain system cost as the mathematical model of target；
The mathematical model is solved using searching algorithm；
The optimal addressing of manufactory and optimum macro, again are determined in the Closed Loop Supply Chain system according to the solving result of acquisition
The optimal addressing of the optimal addressing of manufactory and optimum macro and logistics center and optimum macro；
Wherein, the mathematical model includes: to indicate addressing and the rule of the Closed Loop Supply Chain system cost and the manufactory
Mould decision variable, the addressing for remanufacturing factory and the addressing of Scale Decision-making variable and the logistics center and Scale Decision-making
The objective function of variable relation.
2. the optimization method of Closed Loop Supply Chain system cost according to claim 1, which is characterized in that the mathematical model
Further include: the bound for objective function.
3. the optimization method of Closed Loop Supply Chain system cost according to claim 2, which is characterized in that the closed loop supply
Catenary system cost includes: fixed cost and operation cost.
4. the optimization method of Closed Loop Supply Chain system cost according to claim 3, which is characterized in that the fixed cost
Include: the fixed cost for establishing the manufactory, remanufacture the fixed cost of factory described in foundation and establish the logistics center
Fixed cost；
The operation cost includes: in the positive transmission direction of the Closed Loop Supply Chain system in the manufactory and the logistics
Production cost and transportation cost between the heart, the logistics center and institute in the reverse transmission direction of the Closed Loop Supply Chain system
State remanufacture reproduction cost between factory and transportation cost, the Closed Loop Supply Chain system positive transmission direction on the object
Processing cost and transportation cost between flow center and customer and institute in the reverse transmission direction of the Closed Loop Supply Chain system
State the processing cost and transportation cost between customer and the logistics center.
5. the optimization method of Closed Loop Supply Chain system cost according to claim 1, which is characterized in that described search algorithm
Including TABU search heuritic approach.
6. the optimization method of Closed Loop Supply Chain system cost according to claim 5, which is characterized in that described using search
Algorithm solves the mathematical model, comprising:
Initial value and current globally optimal solution that current iteration number is arranged do not change the initial value of number；
The initial solution of the mathematical model is obtained, and using the initial solution as current solution, wherein the current solution is current complete
Office's optimal solution；
Search whether plain algorithm meets termination condition described in judgement, if so, using the current globally optimal solution as the solution
As a result, otherwise, carrying out neighborhood search to the current solution, obtaining neighborhood solution；
After the acquisition neighborhood solution, judge whether the neighborhood solution is greater than the current globally optimal solution, if so, by institute
It states current globally optimal solution and replaces with the neighborhood solution, otherwise, the current globally optimal solution is not changed into number and adds one；
Judge whether the number that the globally optimal solution does not change is more than or equal to preset threshold, if so, regaining the number
The initial solution of model is learned, and using the initial solution as current solution, while current globally optimal solution is not changed into number setting
It is zero, otherwise, the current iteration number is added one, and rejudge whether described search algorithm meets termination condition.
7. the optimization method of Closed Loop Supply Chain system cost according to claim 6, which is characterized in that described in the acquisition
The initial solution of mathematical model, comprising:
The addressing of the manufactory and Scale Decision-making variable, the addressing for remanufacturing factory and Scale Decision-making variable and described
The addressing of logistics center and Scale Decision-making variable, it is described unknown by initializing as the known variables of the mathematical model
Variable obtains the initial solution of the mathematical model.
8. the optimization method of Closed Loop Supply Chain system cost according to claim 7, which is characterized in that it is described will be described
After initial solution is as currently solving, comprising:
The numerical value for currently solving the corresponding objective function is calculated, and empties introduce taboo list.
9. the optimization method of Closed Loop Supply Chain system cost according to claim 8, which is characterized in that described to work as to described
Preceding solution carries out neighborhood search, comprising:
The initial neighborhood solution currently solved is generated, and calculates the corresponding objective function of each described initial neighborhood solution
Numerical value；
The numerical value of the corresponding objective function of each described initial neighborhood solution is ranked up, and is sequentially selected, is determined most
Initial neighborhood solution corresponding to the numerical value of the small objective function, and will be corresponding to the numerical value of the smallest objective function
The neighborhood solution that initial neighborhood solution is obtained as neighborhood search.
10. a kind of optimization device of Closed Loop Supply Chain system cost, comprising:
Model building module, for establishing to minimize Closed Loop Supply Chain system cost as the mathematical model of target；
Model solution module, for solving the mathematical model using searching algorithm；
Determining module, for the solving result according to acquisition determine Closed Loop Supply Chain system manufactory optimal addressing and
Optimum macro, the optimal addressing for remanufacturing factory and the optimal addressing of optimum macro and logistics center and optimum macro；
Wherein, the mathematical model includes: to indicate addressing and the rule of the Closed Loop Supply Chain system cost and the manufactory
Mould decision variable, the addressing for remanufacturing factory and the addressing of Scale Decision-making variable and logistics center and Scale Decision-making variable
The objective function of relationship.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111985674A (en) * | 2020-06-01 | 2020-11-24 | 南京沃普特科技有限公司 | Intelligent supply chain management cloud system containing Internet of things optimization |
| CN114723092A (en) * | 2020-12-22 | 2022-07-08 | 四川合纵药易购医药股份有限公司 | Distribution route planning method for logistics transportation |
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2018
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111985674A (en) * | 2020-06-01 | 2020-11-24 | 南京沃普特科技有限公司 | Intelligent supply chain management cloud system containing Internet of things optimization |
| CN111985674B (en) * | 2020-06-01 | 2024-02-13 | 南京沃普特科技有限公司 | Intelligent supply chain management cloud system containing Internet of things optimization |
| CN114723092A (en) * | 2020-12-22 | 2022-07-08 | 四川合纵药易购医药股份有限公司 | Distribution route planning method for logistics transportation |
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Application publication date: 20181211 |