CN109543881A - Equipment inventory management decision optimization method, system, electronic equipment and storage medium - Google Patents

Equipment inventory management decision optimization method, system, electronic equipment and storage medium Download PDF

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CN109543881A
CN109543881A CN201811236373.3A CN201811236373A CN109543881A CN 109543881 A CN109543881 A CN 109543881A CN 201811236373 A CN201811236373 A CN 201811236373A CN 109543881 A CN109543881 A CN 109543881A
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equipment
cycle
inventory management
scene
management decision
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镇璐
纪莹
董彬
董平
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Yunfeng International Logistics (shanghai) Co Ltd
University of Shanghai for Science and Technology
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Yunfeng International Logistics (shanghai) Co Ltd
University of Shanghai for Science and Technology
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Abstract

The present embodiments relate to logistics fields, disclose a kind of equipment inventory management decision optimization method, it include: that foundation is interior to the related inventory management decision Optimized model of the demand and the deposit refreshing appliance total amount in warehouse of refreshing appliance with each period, inventory management decision Optimized model includes dynamic profit function and several constraints；According to inventory management decision Optimized model, the quantity of each moment purchase new equipment and the quantity of sale refreshing appliance are determined.The present invention is by establishing inventory management decision Optimized model, it calculates the quantity of each moment purchase new equipment and sells the quantity i.e. optimizing decision of system of refreshing appliance, system total revenue is set to reach maximum, the inventory management decision for equipment especially electronic equipment provides support.

Description

Equipment inventory management decision optimization method, system, electronic equipment and storage medium
Technical field
Logistics field of the embodiment of the present invention, in particular to a kind of equipment inventory management decision optimization method, system, electronics are set Standby and storage medium.
Background technique
With economic continuous development, electronic product early has become essential a part in people's life.Due to electricity The sub- product life cycle is shorter, update speed is fast, and each enterprise is that new product is made to seize the market share rapidly, is continuously improved and produces Product diversity and uniqueness etc. attract customer, while also providing a series of guarantee returns policies for it, improve Customer Satisfaction comprehensively Degree.Therefore, developing reverse supply chain has been that each enterprise improves competitiveness and obtains one of the strategic decision of economic interests.
From the point of view of in the research of reverse supply chain both domestic and external, reverse supply chain stock control about electronic product is ground Study carefully document and few, is advised in relation to the focus mostly on recycling manufacture in electronic product, reverse channel selection, Reverse Logistic Network of research Draw etc..Souza etc. has carried out comprehensive analysis to Closed Loop Supply Chain and has described, and also provides guidance for the research of this paper.Huang etc. pairs The problem of management of product of exchanging goods has carried out detailed general introduction, and establishes a kind of multicycle individual event inventory control model, and analysis is ground The stochastic demand distribution of new product and product of exchanging goods, but its relevant issues for not analyzing return of goods product are studied carefully.The analysis such as Brito Time and influence of the uncertain return of goods product of quantity to stock control, and demonstrate in the case where imperfect information, most Effective method not necessarily shows optimal performance.Petersen constructs prediction model and decision support template, comes The stock control of reverse supply chain is improved, which is changed by incremental analysis to carry out prediction to product whole life cycle Into decision support template then quantifies the uncertainty and risk of different Inventory Management Policies by Monte Carlo simulation.Pince Etc. considering an optimal dynamic decision problem, on this problem, it is for the later period that OEM, which needs to be dynamically selected return of goods product, The replacement for fulfiling equipment of exchanging goods still is used for two time selling, and a critically important factor as decision-making foundation is exactly new product With the price of Refresh Product.And Chen etc. is also from cost-benefit angle analysis, it is quasi- to look for the balance policy for replenishing with returning goods, It is preferably minimized total expected cost of entire stock control problem.For how solving model, Huh etc. is distributed in discrete demand In the case of, the blue Meier estimator of Kapp is used in adaptive optimization algorithm, stochastic stock control problem is solved.Calmon It is distributed Deng by the demand of Monte Carlo simulation goods return and replacement equipment, solves inventory control model in conjunction with certainty equivalents method. Ferguson etc. solves the random optimization mould of monocycle and multicycle that article is established by the situation of change of analysis marginal return Type, the model illustrate electronic product industry return of goods product remanufacture, disassembly components or for the optimal of schemes such as reselling Decision, numerical experiment show that the heuritic approach works well.
However, uncertain in the number of devices of each period supplier demand compensation and the refreshing appliance total amount in deposit warehouse In the case of, how each moment determines the quantity of purchase new equipment and sells the quantity of refreshing appliance, so that system total revenue Reach maximum, do not suggest that in existing research in the case where considering above-mentioned two uncertain factor, proposes so that system The maximum solution of total revenue.
Summary of the invention
Be designed to provide a kind of equipment inventory management decision optimization method, system, the electronics of embodiment of the present invention are set Standby and storage medium, can be not true in the number of devices of each period supplier demand compensation and the refreshing appliance total amount in deposit warehouse In the case where fixed, from cost-benefit angle, calculate the quantity of each moment purchase new equipment and sell refreshing appliance Quantity, that is, system optimizing decision makes system total revenue reach maximum.
In order to solve the above technical problems, embodiments of the present invention provide a kind of equipment inventory management decision optimization side Method, comprising: establish interior to the related library the demand b and the deposit refreshing appliance total amount e in warehouse of refreshing appliance with each period Administrative decision Optimized model is deposited, inventory management decision Optimized model includes dynamic profit function and several constraints；According to inventory Administrative decision Optimized model determines the quantity of each moment purchase of equipment and the quantity of sale refreshing appliance；Wherein, dynamic profit Function is related to the profit on sales of refreshing appliance and purchase new equipment cost, the difference for storing refreshing appliance cost in each period, Several constraints include that the quantity purchase constraint of new equipment, the sales volume constraint of refreshing appliance and refreshing appliance store quantity One or more of constraint.
Embodiments of the present invention additionally provide a kind of equipment inventory management decision optimization system, comprising: Optimized model is built Mould module, it is related to the demand b of refreshing appliance and the deposit refreshing appliance total amount e in warehouse in each period for establishing Inventory management decision Optimized model, inventory management decision Optimized model include dynamic profit function and several constraints；It is optimal to determine Plan determining module determines the quantity and sale refreshing appliance of each moment purchase of equipment according to inventory management decision Optimized model Quantity；Wherein, dynamic profit function is related in each period the profit on sales of refreshing appliance and purchase new equipment cost, stores The difference of refreshing appliance cost, several constraints include the sales volume constraint of the quantity purchase constraint of new equipment, refreshing appliance One or more of number constraint is stored with refreshing appliance.
Embodiments of the present invention additionally provide a kind of electronic equipment, comprising: memory and processor, memory storage meter Calculation machine program, processor execute equipment inventory management decision optimization method as above when running program.
Embodiments of the present invention additionally provide a kind of non-volatile memory medium, for storing computer-readable program, Computer-readable program is for executing equipment inventory management decision optimization method as above for computer.
Embodiment of the present invention calculates each moment purchase new equipment by establishing inventory management decision Optimized model Quantity and the quantity, that is, system optimizing decision for selling refreshing appliance make system total revenue reach maximum, are that equipment is especially electric The inventory management decision of sub- equipment provides support.
In addition, the refreshing appliance total amount e of each period t is determined according to minor function in embodiment of the present invention:
eT, s=wT, s+vT, s+aT, s,
Wherein, eT, sFor the refreshing appliance total amount in each cycle t deposit warehouse under s scene, wT, sFor each cycle under s scene T manufacturer repairs exchange goods equipment after be stored in warehouse number of devices, vT, sFor under s scene each cycle t supplier repair and change The number of devices in warehouse, a are stored in after goods equipmentT, sFor the equipment that supplier has repaired deposit warehouse after return of goods equipment under s scene Quantity.To combine the calculation method that practical application request provides the refreshing appliance total amount of determining each cycle.
In addition, in embodiment of the present invention, wT, s、vT, s、aT, sIt calculates according to the following formula:
Wherein, κsMeet the probability of manufacturer's service contract, d for the equipment that each cycle customer t need to exchange goods under s sceneT, s For the number of devices that each cycle customer t need to exchange goods under s scene, αsFor the conjunction of each cycle t manufacturer maintenance of equipment under s scene Lattice rate, βsFor the qualification rate of each cycle t supplier maintenance of equipment under s scene, rT, sFor under s scene each cycle customer t need to move back The number of devices of goods.The calculation formula of above-mentioned each element is further clarified.
In addition, according to inventory management decision Optimized model, determining each moment purchase of equipment in embodiment of the present invention The quantity of quantity and sale refreshing appliance, specifically:
According to the carrying cost of equipment, the equipment total amount that each cycle needs to retain is solved；
The equipment total amount retained is needed according to each cycle, using incremental formula and gradient search algorithm, solves each cycle Optimal Inventory it is horizontal；
According to the constraint of the quantity purchase of the Optimal Inventory of each cycle level, dynamic profit function, new equipment and refreshing appliance Sales volume constraint, determine each moment purchase of equipment quantity and sale refreshing appliance quantity.
In addition, according to the carrying cost of equipment, it is total to solve the equipment that each cycle needs to retain in embodiment of the present invention Amount, specifically:
According to the carrying cost c of each cycle h equipmentH, s, it is determined that the maximum time of retaining device
According to should retaining device maximum timeWith each cycle h to the demand b of refreshing applianceH, sWith deposit storehouse The refreshing appliance total amount e in libraryH, s, determineNet demand in period section
According to net demandSolving the equipment total amount that each cycle t needs to retain is oT, s；
Wherein, period h is greater than period t.
In addition, in embodiment of the present invention further include: design multiple groups experiment determines the reality of inventory management decision Optimized model Test best scene number.
In addition, embodiment of the present invention further include: carry out numerical experiment in conjunction with sales data, analyzed under best scene number The sensitivity that inventory management decision Optimized model changes different parameters；
Wherein, different parameters include at least the maintenance time and equipment guarantee period of the maintenance time of supplier, manufacturer.
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 equipment inventory management decision optimization method flow chart in first embodiment according to the present invention；
Fig. 2 is the dynamic flow schematic diagram at the reverse logistic center in first embodiment according to the present invention；
Fig. 3 is that the quantity of each moment purchase of equipment of determination in first embodiment and sale renovation are set according to the present invention The method flow diagram of standby quantity；
Fig. 4 is the method flow for the equipment total amount that the solution each cycle in first embodiment needs to retain according to the present invention Figure；
Fig. 5 is the method flow diagram of the equipment inventory management decision optimization method in second embodiment according to the present invention；
Fig. 6 is the monthly data distribution map of the Samsung mobile phone sales in second embodiment according to the present invention；
Fig. 7 is the distribution schematic diagram of the new equipment in second embodiment and refreshing appliance price according to the present invention；
Fig. 8 is the f in second embodiment according to the present inventionT, sObey lognormal distribution plot；
Fig. 9 is the probability normal distribution figure that customer according to the present invention in second embodiment returns equipment；
Figure 10-1 to Figure 10-4 be according to the present invention different manufacturer's maintenance times in second embodiment to systematicness The influence situation schematic diagram of energy；
Figure 11-1 to Figure 11-4 be according to the present invention different supplier's maintenance times in second embodiment to systematicness The influence situation schematic diagram of energy；
Figure 12-1 to Figure 12-4 is that the system in second embodiment is anti-for the distinct device guarantee period according to the present invention Answer situation schematic diagram；
Figure 13 is the structural schematic diagram of the equipment inventory management decision optimization system in third embodiment according to the present invention；
Figure 14 is the electronic devices structure schematic diagram in the 4th embodiment according to the present invention.
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 equipment inventory management decision optimization methods, as shown in Figure 1, comprising:
Step 101, it establishes and in each period to the refreshing appliance total amount e of the demand b of refreshing appliance and deposit warehouse Related inventory management decision Optimized model, inventory management decision Optimized model include dynamic profit function and several constraints；
Step 102, according to inventory management decision Optimized model, the quantity and sale renovation of each moment purchase of equipment are determined The quantity of equipment；
Wherein, dynamic profit function is related in each period the profit on sales of refreshing appliance and purchase new equipment cost, deposits Set the difference of refreshing appliance cost, several constraint include new equipment quantity purchase constraint, refreshing appliance sales volume about Beam and refreshing appliance store number constraint.
Logistics Mode used by most enterprises is to establish special reverse logistic center to handle customer at present Goods return and replacement equipment, and by the equipment for meeting service contract send to manufacturer's processing center repair, maintenance renovation after equipment Can be used as customer exchange goods or two time selling earning profit.In this mode, it will usually which there are customer, supplier and manufacturers three It is big to participate in main body, and have manufacturer's service contract, sales return contract and maintenance contract to guarantee that Reverse Logistics System operates.
Specifically, service contract, sales return contract, maintenance contract are respectively suitable for practical application scene below:
1. service contract, manufacturer's service contract, that is, manufacturer is the warranty policy that customer provides, it is however generally that, guarantee to keep in good repair base This length is 1 year, and customer can also independently select purchase to extend guarantee.When the equipment of customer's purchase breaks down, can first contact Related technical personnel simultaneously attempt to solve the problems, such as, if equipment fault can not be solved by phone, can apply for Swap Repair, exist side by side Equipment is returned into supplier's processing center, it, can be immediately from warehouse when supplier's processing center receives the equipment that customer need to repair It sends a refreshing appliance and is given to customer.When the refreshing appliance shortage of stock, then the new equipment of same model is bought by supplier Or the new equipment of model upgrading is sent to customer.Every equipment can only carry out a Swap Repair, and if customer's purchase is set Standby to break down but warranty have expired for, then faulty equipment will not be replaced.
2. sales return contract, i.e. customer can return equipment in certain time after point of purchase, in general, contracted Fundamental length is one month, and return of goods equipment need to fully meet the contract requirement just achievable return of goods.Return of goods equipment is directly entered confession It is put in storage after answering quotient's processing center to repair, exchanges goods demand or two time selling as customer is met.
3. with regard to the conjunction of the formulations such as the maintenance standard of equipment and time of delivery between maintenance contract, i.e. manufacturer and supplier Together, the service interval of equipment be product Life cycle, usually 2 years.Supplier's processing center is receiving what customer returned After the equipment that need to be repaired, sort operation will do it, send the equipment for meeting maintenance contract to manufacturer processing center and repair, Incongruent equipment repairs indwelling supplier processing center.When supplier is by the delivery for appointing maintenance of equipment with manufacturer Between, the details such as delivery quantity.
Reverse logistic center described above contains supplier's processing center and equipment storage warehouse.In supplier's processing The heart is the first stop for handling customer's goods return and replacement demand, carries out sort operation when equipment reaches, and repair return of goods equipment and be not inconsistent Close the equipment of exchanging goods of maintenance contract.
Below in conjunction with the dynamic flow at Fig. 2 detailed description reverse logistic center:
(1) process such as in Fig. 2 is 1. shown, when customer has the demand of the return of goods or maintenance of equipment, need to be addressed to equipment Supplier's processing center.
(2) process such as in Fig. 2 is 2. shown, and when supplier's processing center receives equipment, warehouse will send a renovation Equipment or new equipment give the customer for having maintenance requirements.
(3) process such as in Fig. 2 is 3. shown, after supplier's processing center sorts, will meet manufacturer's service contract Equipment send to manufacturer's processing center repair, the equipment and return of goods equipment for not meeting manufacturer's service contract will be in suppliers Processing center maintenance.
The sort process of supplier's processing center would generally generate following four situation: a. equipment is not found the problem, then It is renovated by supplier's processing center；B. equipment does not meet maintenance contract, then is repaired by supplier's processing center；C. existing for equipment Problem a part meets maintenance contract, and a part is not met, then by being sent again after the maintenance of supplier's processing center to manufacturer The maintenance of reason center；D. equipment there are the problem of all meet maintenance contract, then send to manufacturer's processing center repair.
(4) as the process in Fig. 2 4. shown in, after manufacturer and supplier have repaired equipment, be transported to warehouse storage.
(5) process such as in Fig. 2 is 5. shown, and refreshing appliance can also carry out two time selling by Sales Channel.These channels Including other same types supplier, equipment component manufacturer and supplier and discount store etc..Two time selling can not only increase System profit is also used as storage controlling mechanism, and balanced stock is horizontal, equipment carrying cost is reduced, especially in product The period that life cycle terminates.
In the Closed Loop Supply Chain system, the quantity required of exchanging goods (process in Fig. 2 is 2.) and refreshing appliance of customer is reached The quantity (process in Fig. 2 3. with process 4.) in warehouse is close association.As mentioned above, not every equipment It can all be repaired, then be to have partial loss in the system.And when supplier's processing center receives the equipment that customer need to repair, A refreshing appliance can be sent from warehouse immediately and be given to customer, if supplier need to spend into original when the refreshing appliance shortage of stock The new equipment of the new equipment or model upgrading of buying same model is sent to customer.But if retaining excessive equipment in warehouse, Higher carrying cost can be not only generated, can also lose the profit of two time selling, and over time, turning in warehouse New equipment can also devalue rapidly.Generally speaking, the cost of carry of the system is mainly related with the side pin allowance for depreciation of channel, and punishes Cost is then the unit purchase cost of new equipment.Therefore, product unstable in face of equipment goods return and replacement demand and electronic equipment is raw Period shorter Closed Loop Supply Chain situation is ordered, how to balance this two costs is present embodiment problem to be solved.
In view of the profit or cost of the three parts involved in the current period stock control under s scene: first part is In current period, when the refreshing appliance quantity in warehouse is greater than Optimal Inventory level, it can will have more part and carry out two time selling, The profit obtained is kT, suT, s；Second part is in current period, when the refreshing appliance quantity in warehouse is not enough claimed damages to customer When, need to buy new Claims for equipment to customer, the cost spent is pT, sqT, s；Part III is warehouse storage refreshing appliance Carrying cost be cT, szT, s.To make the system net maximum revenue, present embodiment can establish following inventory management decision Optimized model:
z0, s=0 3)
Wherein, dynamic profit function 1) it is related to the profit on sales k of refreshing appliance in each periodT, suT, sWith purchase new equipment Cost pT, sqT, s, store refreshing appliance cost cT, szT, sDifference, { bT, s, eT, s| t=1 ..., T } it is a random process；About Beam condition 2) and 3) number constraint is stored for refreshing appliance, indicate when t end cycle remaining refreshing appliance quantity in warehouse, Initial inventory is 0；Constraint condition 4) and 5) be respectively refreshing appliance sales volume constraint and new equipment quantity purchase constrain, Expression can be sold if stockpile number has residue, if stockpile number is unsatisfactory for customer and exchanges goods demand, will buy new equipment.
Wherein, each parameter and the meaning of variable are as follows:
pT, sFor under s scene the t period buy the cost of new equipment；
kT, sFor the income of the t cyclical sales refreshing appliance under s scene；
cT, sFor the carrying cost of the period warehouse the t storage refreshing appliance under s scene；
qT, sFor under s scene the t period buy the quantity of new equipment；
uT, sFor the quantity of the t cyclical sales refreshing appliance under s scene；
zT, sFor the remaining refreshing appliance quantity in warehouse when t end cycle under s scene.
Preferably, in present embodiment, the refreshing appliance total amount e of each period t is determined according to minor function: eT, s =wT, s+vT, s+aT, s, wherein eT, sFor the refreshing appliance total amount in each cycle t deposit warehouse under s scene, wT, sFor under s scene Each cycle t manufacturer repairs exchange goods equipment after be stored in warehouse number of devices, vT, sFor under s scene each cycle t supplier tie up Fix the number of devices that warehouse is stored in after exchanging goods equipment, aT, sAfter each cycle t supplier has repaired return of goods equipment under s scene It is stored in the number of devices in warehouse.
Specifically, it will be assumed that time t be it is discrete, the number of devices that each period customer t need to return goods be rT, s, need to change The number of devices of goods is dT, s, time for returning equipment beAnd exchanging goods for customer is received in supplier's processing and is set Equipment is sent to customer from warehouse at once after standby, then demand (number of devices that supplier demand pay for of the t period to refreshing appliance Amount)When supplier's processing center receive customer exchange goods equipment after, sort operation is carried out, in next model We assume that sorting is completed at once, the time ignores, and the probability that the equipment that customer need to exchange goods meets manufacturer's service contract is κs(0≤κs≤ 1), the qualification rate of manufacturer's maintenance of equipment and maintenance time are respectively αs(0≤αs≤ 1) with The qualification rate of supplier's maintenance of equipment and maintenance time distinguish βs(0≤βs≤ 1) withThen t period manufacturer ties up Fix the number of devices that warehouse is stored in after exchanging goods equipmentSupplier repairs exchange goods equipment after be stored in The number of devices in warehouseSupplier has repaired the number of devices in deposit warehouse after return of goods equipment AmountTherefore the t period is stored in the refreshing appliance total amount e in warehouseT, s=wT, s+vT, s+aT, sComprising it returns goods Refreshing appliance that equipment, manufacturer have repaired etc. enters all devices in the warehouse at reverse logistic center, can be used for meeting customer Demand of exchanging goods or two time selling.
It is noted that in reality, if equipment is the faster electronic product that updates, in its entire Life Cycle The sales value of product can devalue rapidly in phase, i.e., the price of new equipment and the price of refreshing appliance be can be over time And decline.So we assume that buying the cost p of new equipment in the t periodT, s, sale refreshing appliance income kT, sAnd warehouse storage The carrying cost c of refreshing applianceT, sIt is that passage at any time successively decreases and is more than or equal to zero, i.e. pT, s≥pT+1, s≥0、kT, s≥kT+1, s ≥0、cT, s≥cT+1, s≥0.New equipment is bought in order to avoid supplier is strategic simultaneously, then the price for buying new equipment will be greater than Sell the price of refreshing appliance, i.e. pT, s≥kT, s。
As advanced optimizing, present embodiment determines that each moment purchase is set according to inventory management decision Optimized model The quantity of standby quantity and sale refreshing appliance, specifically includes following steps shown in Fig. 3:
Step 301, according to the carrying cost of equipment, the equipment total amount that each cycle needs to retain is solved；
Step 302, the equipment total amount retained is needed to ask using incremental formula and gradient search algorithm according to each cycle The Optimal Inventory for solving each cycle is horizontal；
Step 303, according to the quantity purchase of the Optimal Inventory of each cycle level, dynamic profit function, new equipment constraint and The sales volume of refreshing appliance constrains, and determines the quantity of each moment purchase of equipment and the quantity of sale refreshing appliance.
Specifically, in step 301, according to the carrying cost of equipment, the equipment total amount that each cycle needs to retain is solved, into One step includes shown in Fig. 4 following:
Step 401, according to the carrying cost c of each cycle h equipmentH, s, it is determined that the maximum time of retaining device
Step 402, according to should retaining device maximum timeWith each cycle h to the demand b of refreshing applianceH, s With the refreshing appliance total amount e in deposit warehouseH, s, determineNet demand in period section
Step 403, according to net demandSolve the equipment total amount o that each cycle t needs to retainT, s；
Wherein, period h is greater than period t.
Specifically, the inventory management decision of each cycle is turning in the demand and deposit warehouse for observing refreshing appliance New equipment total amount does decision after we know the state of current period system again.Assuming that state, that is, warehouse of t periodic system Only inventory isEach cycle can two time selling go out extra refreshing appliance, but not necessarily will Equipment all sells Income Maximum when i.e. quantity in stock is 0.Due to being assumed in [1, T] period section herein, { kT, s}、{pT, sAnd {cT, sAll be the increase with the period and successively decrease, and pT, s≥kT, s>=0, then we need to retain certain number of devices in the t period Amount, meets the demand of exchanging goods of customer for avoiding that high price to be spent to buy in new equipment at the time of later.
Assuming that in [1, T] period section, the number of devices b of demand compensationT, sWith the refreshing appliance quantity e in deposit warehouseT, s Be it is determining, we can in the hope of each cycle buy and sell equipment optimal number.Each cycle needs the equipment total amount that retains to be OT, s, in the period section [t, j] maximum time of retaining device be
ForThenEquipment is sold in the t period and is bought in the j period, phase It is higher for the cost for retaining this unit in [t, the j] period, therefore optimizing decision is will not to sell this equipment simultaneously in the t period ?It buys in；ForEquipment is sold in the t period and is bought in the j period, relative in [t, the j] period The cost for retaining this unit is lower, therefore optimizing decision is will not to retain this equipment in [t, the j] period.Therefore, existNet demand in period section are as follows:
?The sum of net demand in section is equal to the equipment total amount for needing to retain in the t period, then has:
By above-mentioned analysis it is not difficult to find that the equipment total amount o for needing to retain in the solution t periodT, sWhen, it requires no knowledge about h weeks The price k of the sale refreshing appliance of phase (h > t)H, s, it is only necessary to know that the carrying cost c of h periodic deviceH, s, come it is determined that retaining The maximum time of equipmentAfterwards, pass through formula 8) and 9) can acquire.
After the equipment total amount that each cycle needs to retain has been determined, it can be analyzed more at a certain moment by incremental formula The situation of change of the marginal return of the unit of reservation, and by gradient search algorithm, determine that the Optimal Inventory of each cycle is horizontal And then acquire the optimal number of each cycle dealing equipment:
Formula 10) indicate current system conditionsWhen, new equipment will be bought.Formula 11) if indicating current system conditions Greater than Optimal Inventory levelTwo time selling will be carried out to the refreshing appliance having more.Pass through formula 11) and 12) acquire out each cycle Optimizing decision ensure that system gross profit is maximum.
Further, using incremental formula and gradient search algorithm, the Optimal Inventory for solving each cycle is horizontal, specifically Process is as follows:
The Expect Profits of current systemIt can be expressed as:
To formula (12), it is solved, and available Optimal Inventory is horizontalExpression formula are as follows:
By calculating above, it is known that each period needs the equipment total amount (o retainedT, s..., oT, s), net stockpile numberIn the t period, by inventory level from oT, sBecome oT, sIt when+1, analyzes in the period section [t+1, T], to keep needing to retain Equipment total amount (oT+1, s..., oT, s) constant, the marginal situation of change of Expect Profits.
If net inventory levelThen stock buildup level will not change expectation in the period section [t+1, T] Profit；If net inventory levelThen from t+1, there is the additional inventory of a unit, if inventory level increased It is added to OT, s+ 1, then it may change Expect Profits.Therefore in the period section [t+1, T], stockpile number oT, sAnd oT, s+ 1 library A path difference at most unit is deposited, and on certain point, two inventory paths will couple, until the T period
If stochastic variableIndicate oT, sInventory level path and oT, sThe period of+1 inventory level path coupling, ExistAll periods later, the path of two inventory levels are identical.And when in [t+1, ω 'T, s] period section Any equipment is not sold inside, first need buys an equipment to meet inventory level oT, sPeriod in inventory path beWhen in [t+1, ω "T, s] any equipment is not bought in period section, first need sells an equipment to meet inventory Horizontal oT, sThe period in+1 inventory path isThenWithIt may be expressed as:
If net inventory levelThen inventory level is from oT, sBecome oT, sWhen+1, it is expected that incremental benefit Are as follows:
It is expected that the inventory level for determining this increased unit is followed by by incremental benefit should be sold (i.e.), it is also used as avoiding purchase (i.e.).If the expectation incremental benefit of the unit Higher than the price of current period sale, i.e.,Then answer retention increment unit.Therefore, the expression of Optimal Inventory level Formula is then are as follows:
The Optimal Inventory that each period can be acquired by gradient search algorithm is horizontalGradient search algorithm is existing Well-known technique, those of ordinary skill in the art are not required to creative work i.e. it is contemplated that this will not be repeated here.
Preferably, by analysis Closed Loop Supply Chain system, the sales situation of equipment, equipment fault and the return of goods point Cloth situation and other features, the available one number of devices b paid for about demandT, sWith the refreshing appliance quantity in deposit warehouse eT, sNonstationary random process { bT, s, eT, s| t=1 ..., T }, and this random process is sufficiently complex.Therefore, to library Before depositing administrative decision Optimized model progress numerical experiment, we will determine the influence factor of system mode.
Given that it is known that in the quantity x of t cyclical sales equipmentT, sAnd fault time and the return of goods Annual distribution of equipment, only take Certainly in the age of equipment, i.e. customer's time for using equipment.We indicate that customer is broken down using the i-th periodic device of equipment Probability be ηI, s, then t period customer need to exchange goods number of devices dT, sAre as follows:
Similarly, we indicate that customer is using the probability that the i-th period customer of equipment returns equipment
γI, s, then t period customer need to return goods number of devices rT, sAre as follows:
Inventory management decision Optimized model according to the present embodiment as a result, obtains per moment warehouse by solving first The equipment total amount that need to retain, and then calculate by incremental formula and gradient search algorithm the Optimal Inventory water in each period It is flat, then and calculate the quantity of each moment purchase new equipment and sell the quantity i.e. optimizing decision of system of refreshing appliance, most The total revenue of system can be made to reach maximum eventually.
Second embodiment of the present invention is related to a kind of equipment inventory management decision optimization method, as shown in Figure 5, comprising:
Step 501, it establishes and in each period to the refreshing appliance total amount e of the demand b of refreshing appliance and deposit warehouse Related inventory management decision Optimized model, inventory management decision Optimized model include dynamic profit function and several constraints；
Step 502, design multiple groups experiment, determines the best scene number of the experiment of inventory management decision Optimized model；
Step 503, it in conjunction with the inventory management decision Optimized model of sales data basis under best scene number, determines different The quantity of the quantity of each moment purchase of equipment and sale refreshing appliance when parameter；
Wherein, dynamic profit function is related in each period the profit on sales of refreshing appliance and purchase new equipment cost, deposits Set the difference of refreshing appliance cost, several constraint include new equipment quantity purchase constraint, refreshing appliance sales volume about Beam and refreshing appliance store number constraint, and different parameters include at least the maintenance time of the maintenance time of supplier, manufacturer And the equipment guarantee period.
Present embodiment analyzes sensitivity of the inventory management decision Optimized model to major parameter, and analyzes each parameter pair Optimal Inventory level and the influence to objective function, to provide support for the inventory management decision of product.
Since inventory management decision Optimized model is a Stochastic Programming Model in present embodiment, it is contemplated that parameters Different scenes, scene quantity is more, based on the scene building Stochastic Programming Model closer to reality, therefore, scene The size of quantity has significant impact to experiment.If scene quantity is very little, it is not enough to illustrate that the Stochastic Programming Model is applicable in wide General property, and scene quantity is excessive, then it is too long to will lead to experiment runing time, causes redundancy.It is therefore desirable to carry out subsequent reality Before testing, best scene quantity is determined.
Theoretically, the standard deviation of the target function value of same scene quantity case is answered when scene number increases The reduction, therefore present embodiment is provided with multiple groups experiment of the scene quantity from 10 to 80, assesses suitable experiment scene quantity. 10 different cases will be randomly generated for the scene quantity (i.e. 10,20,30,40,50,60,70 and 80) of each setting Example, these cases solve the Stochastic Programming Model proposed with present embodiment.The probability of each scene is assumed in experiment Be it is identical, as scene quantity is | s |, then the probability of each scene isSpecific experiment data are as shown in Table 1 below:
1 scene number of table tests table
Learnt from table 1, every group of experimental result include the maximum values of lower 10 cases of each situation, minimum value, it is very poor, Average value, standard deviation and corresponding system operation time.When scene quantity increases, model criteria difference is gradually reduced, feasible Solution will be concentrated more, which is consistent with theory.Simultaneously it can be seen that the very poor and standard deviation of every group of 10 cases Between gap can reduce with the increase of scene quantity, and when scene quantity is more than 60, with the increasing of scene quantity Add, the reduction trend of standard deviation is slow, but system operation time increases comparatively fast.Therefore, in next numerical experiment, I Scene quantity is set as 60.
As described in first embodiment of the invention, the Closed Loop Supply Chain system mode is sufficiently complex, includes each week The number of devices of different service life in the market in phase.The number of devices r that each period customer need to return goodsT, s, customer need to exchange goods Number of devices dT, sWith the refreshing appliance total amount e in deposit warehouseT, s, not simple markoff process, depending on current The service life of equipment and the Under Repair service life of equipment in the market.
Present embodiment dynamically calculates each period warehouse storage renovation and sets by establishing inventory management decision Optimized model Standby Optimal Inventory is horizontalTo solve the problems, such as this.Gradient search algorithm is such as first passed through, the optimal library from the t period is calculated Water is flatThen the Optimal Inventory of each cycle is horizontal after the t+1 period is recalculated System mode is constantly updated with identical process later.
Since the number of devices in the system is very big, and the probability of some periodic device failure or the return of goods will be for its future Failure rate, the distribution of return of goods rate do not have a significant impact, so the model has good practicality.For parameter each in analysis model Influence to the Closed Loop Supply Chain system assumes it as follows.
(1) sales volume of new equipment
Assuming that the sales cycle of new equipment is 2 years (104 weeks), the quantity xt, s of each cycle sale equipment we with reference to Samsung Mobile phone in January, 2014 in December, 2015, the sales data in Hunan area carried out numerical experiment, monthly data distribution such as Fig. 6 It is shown.For ease of calculation, the quantity of each cycle sale equipment is the average value of the monthly sales volume.
(2) new equipment price, refreshing appliance price, carrying cost
The price of new equipment period 1 is p1, s, the price of the period 1 of refreshing appliance is k1, s, and with sales cycle Increase and successively decrease, and the price of new equipment is consistently higher than the price of refreshing appliance, as shown in Figure 7.Every refreshing appliance is deposited It is set to this cT, sIt is 1 yuan of each cycle.
(3) equipment return of goods probability, probability of exchanging goods
When customer buys new equipment, the return of goods, service contract come into force, and the time limit of returning goods is month (4 weeks), a guarantee time one Year (52 weeks), every equipment once can only be returned goods or be exchanged goods.If customer purchase device fails but the guarantee period It crosses, then faulty equipment will not be replaced.
What we had used for reference that current the art proposes fails the solving model of number of devices in the t period:
Wherein d (t) is number of devices of exchanging goods in the t period, ws(k) it is sales volume that equipment using the time is the s period,For The probability of equipment faultftFor the quantity for equipment of exchanging goods, this equipment that need to be exchanged goods with this paper t period customer established The expression formula (17) of quantity unanimously, and assumes f in current techniques fieldT, sLogarithm normal distribution is obeyed, as shown in Figure 8.
Pointed out simultaneously according to Ronald etc., product in life cycle, return of goods amount be it is with sales volume highly relevant, And the consumer's return of goods function proposed in the art at present by analysis:
Wherein R be return of goods number of devices, S (q) be device sales amount, G be return of goods probability, then the quantity for equipment of returning goods be with What device sales amount and return of goods probability determined, this is consistent with the expression formula (18) established herein.Then herein assuming that equipment is moved back On the basis of delivery date is limited to 1 month (4 weeks) and does not consider customer payment back goods freight, analysis returned work psychology, closer to the phase A possibility that limit deadline, return of goods behavior occurs for customer, is higher, it is therefore assumed that customer is returned using the i-th period customer of equipment The probability γ of equipmentI, sNormal Distribution, as shown in Figure 9.
(4) maintenance time and qualification rate
Customer returns the period of equipmentIt is 1 week, the equipment for needing Swap Repair returned meets manufacturer's service contract Probability (κs) it is 70%, the time of manufacturer's maintenance of equipmentIt is 2 weeks, qualification rate (αs) it is 80%；Return the system of not meeting Make that quotient's service contract need to exchange goods equipment and the equipment that need to return goods is repaired by supplier, the period of supplier's maintenance of equipmentIt is 1 week, Qualification rate (βs) it is 95%.
Maintenance time is covered: 1) time that equipment is sorted in supplier's processing center；2) from suppliers after sorting It sends to the time of manufacturer's processing center at reason center；3) time of manufacturer and supplier's maintenance of equipment；4) manufacturer and confession After answering quotient to repair equipment, it is transported to the warehouse storage time used.This is 3. opposite to the time of step 4. with the step in Fig. 2 It answers.
Following sensitivity of the present embodiment Main Analysis inventory management decision Optimized model to major parameter, and analyze Influence of each parameter to Optimal Inventory level and to objective function.
(1) time of manufacturer's maintenance of equipment
In practice, maintenance time can pass through: 1) reducing supplier's processing center to the sorting time of equipment；2) it reduces It sends from supplier's processing center to the time of manufacturer's processing center；3) reduce manufacturer and supplier's maintenance of equipment when Between；4) time that warehouse is transported to from manufacturer's processing center and supplier's processing center is reduced.Figure 10-1 to Figure 10-4 description Influences of the different manufacturer's maintenance times to system performance.
By analysis it is found that the growth of the time of manufacturer's maintenance of equipment will increase the Optimal Inventory level and purchase of system The quantity of new equipment, while the quantity for selling refreshing appliance also will increase, but system gross profit will decline.
Due to the increase of the time of manufacturer's maintenance of equipment, the number of devices in deposit warehouse can be reduced, and is trapped in it Manufacturer's processing center, therefore will increase the quantity of purchase new equipment needed for maintenance system state.It exchanges goods demand peak in customer After (the 55th week) past in period, due to sending the equipment repaired to manufacturer maintenance center in peak time, repair good rear continuous It is sent to warehouse, so increasing the two time selling quantity of refreshing appliance.And the situation shorter in the time of manufacturer's maintenance of equipment Under, the case where two time selling refreshing appliance, there is also the incipient stage in life period of equipment, because of the equipment repaired at this time Warehouse can be arrived at as early as possible, and demand of exchanging goods is not also high, therefore stock equipment has residue, therefore can two time selling earning profit.
(2) time of supplier's maintenance of equipment
The source of equipment is except the equipment and newly in addition to the equipment bought of exchanging goods in Closed Loop Supply Chain system, and there are also customers to equipment not The equipment for being satisfied with and returning goods.Figure 11-1 to Figure 11-4 describes influence of the different supplier's maintenance times to system performance.
By analysis, it is found that the growth of the time of supplier's maintenance of equipment can make, the Optimal Inventory in system is horizontal, buys The quantity of new equipment, the quantity for selling refreshing appliance increase, but system gross profit will decline.
Just as expected, Optimal Inventory level can increase with the growth of the time of supplier's maintenance of equipment, because The increase of maintenance time can be such that the equipment for reaching warehouse is postponed, so may require that the more new equipments of purchase subsequent and tie up Customer demand is held, and longer maintenance time can make to buy time advance of the new equipment to maintain the number of devices of demand peak. Due to before us it is assumed that the equipment of supplier's maintenance by 30 percent exchange goods equipment and all return of goods equipment forms , it is lower for demand and the quantity of return of goods equipment is relatively exchanged goods, so the change of supplier's maintenance of equipment time is for system Influence it is smaller than the influence of manufacturer's maintenance of equipment time.
(3) the equipment guarantee period
The equipment guarantee period is the important parameter of Closed Loop Supply Chain system, and the different equipment guarantee periods can change equipment in system In the retention period.System for the distinct device guarantee period reaction as shown in Figure 12-1 to Figure 12-4.
By analysis it is found that the growth of equipment guarantee period will increase the Optimal Inventory level of system and the number of purchase new equipment Amount, while the quantity for selling refreshing appliance also can optionally decline.
No matter whether the equipment guarantee period increases first, all need to system at the beginning state just buy equipment component meet care for Visitor exchanges goods demand, because customer's maintenance of equipment is not stored in warehouse also at this time.When the equipment guarantee period is 13 weeks, system need to only opened 2 weeks purchase of equipment begin to retain fraction inventory, starts do not have the case where replacement equipment in state repository to meet system, Profit can be earned by all devices total number is sold in addition to exchanging goods to customer in inventory later, therefore gross profit also highest.When When the equipment guarantee period is 26 weeks, except in the case of it need to meet the purchase of equipment that the guarantee period is 13 weeks, it need to retain at the 20-30 weeks and turn over New equipment meets the demand of exchanging goods of customer, because customer need to exchange goods, equipment will start to reach peak state at the 18th week.When setting The standby guarantee period at 52 weeks or more, increases since each cycle need to repair the number of devices exchanged goods, needs more refreshing appliances It is stored in warehouse, but the number of devices at the beginning in system Under Repair is limited, the demand of exchanging goods after being insufficient for, then need to be from Retain large number of equipment at the very start, and is changed in customer's the 40-60 weeks purchase new equipment that demand is most concentrated of exchanging goods to meet customer Goods demand, therefore, the fall of gross profit are also larger.And price because of equipment and carrying cost are opened in the life cycle of equipment Stage beginning occupies leading position, so its inventory path is roughly the same, increasingly with the maintenance of equipment having in system later More, nearly all equipment that need to exchange goods can be met by the refreshing appliance in system, then inventory does not need stock, but due to equipment Sales volume be also gradually reduced, and enter system without return of goods equipment after 108 weeks, then sell the quantity of refreshing appliance also by Gradually decline.
To sum up, present embodiment combination sales data carries out numerical experiment, determines the best scene number of the experiment of model, and divide Analysed sensitivity that model changes different parameters (such as the time of the time of manufacturer's maintenance of equipment, supplier's maintenance of equipment and The equipment guarantee period), support is provided for the inventory management decision of equipment.
Third embodiment of the invention provides a kind of equipment inventory management decision optimization system, as shown in figure 13, comprising:
Optimized model modeling module 1301, for establishing and in each period to the demand b of refreshing appliance and deposit storehouse The related inventory management decision Optimized model of refreshing appliance total amount e in library, inventory management decision Optimized model includes dynamic profit Function and several constraints；
Optimizing decision determining module 1302 determines each moment purchase of equipment according to inventory management decision Optimized model The quantity of quantity and sale refreshing appliance；
Wherein, dynamic profit function is related in each period the profit on sales of refreshing appliance and purchase new equipment cost, deposits Set the difference of refreshing appliance cost, several constraint include new equipment quantity purchase constraint, refreshing appliance sales volume about Beam and refreshing appliance store number constraint.
In present embodiment, the refreshing appliance total amount e of each period t is determined according to minor function:
eT, s=wT, s+vT, s+aT, s,
Wherein, eT, sFor the refreshing appliance total amount in each cycle t deposit warehouse under s scene, wT, sFor each cycle under s scene T manufacturer repairs exchange goods equipment after be stored in warehouse number of devices, vT, sFor under s scene each cycle t supplier repair and change The number of devices in warehouse, a are stored in after goods equipmentT, sFor the equipment that supplier has repaired deposit warehouse after return of goods equipment under s scene Quantity.To combine the calculation method that practical application request provides the refreshing appliance total amount of determining each cycle.
Further, in invention embodiment, wT, sIt calculates according to the following formula:
Wherein, κsMeet the probability of manufacturer's service contract, d for the equipment that each cycle customer t need to exchange goods under s sceneT, s For the number of devices that each cycle customer t need to exchange goods under s scene, αsFor the conjunction of each cycle t manufacturer maintenance of equipment under s scene Lattice rate, βsFor the qualification rate of each cycle t supplier maintenance of equipment under s scene, rT, sFor under s scene each cycle customer t need to move back The number of devices of goods.The calculation formula of above-mentioned each element is further clarified.
In addition, optimizing decision determining module 1302 specifically includes in present embodiment::
Retain number calculating section 1321, for the carrying cost according to equipment, solves the equipment that each cycle needs to retain Total amount；
Optimal Inventory computing module 1322, the equipment total amount for needing to retain according to each cycle, utilizes increment point Analysis method and gradient search algorithm, the Optimal Inventory for solving each cycle are horizontal；
It buys and sells number calculating section 1323, horizontal, the described dynamic profit letter for the Optimal Inventory according to each cycle The quantity purchase of several, the described new equipment constrains and the constraint of the sales volume of the refreshing appliance, determines each moment purchase The quantity of equipment and the quantity of sale refreshing appliance.
In present embodiment, retains number calculating section 1321 and specifically includes:
Maximum time determining module 13121, for the carrying cost c according to each cycle h equipmentH, s, set it is determined that retaining Standby maximum time
Net demand determining module 13221, for according to should retaining device maximum timeWith it is described weekly Demand b of the phase h to refreshing applianceH, sWith the refreshing appliance total amount e in deposit warehouseH, s, determineIn period section Net demand
Retain quantity determining module 13321, for according to the net demandDetermine what each cycle t needed to retain Equipment total amount is oT, s；
Wherein, period h is greater than period t.
In addition, present embodiment further include:
Scene number determining module 1304 determines the reality of the inventory management decision Optimized model for designing multiple groups experiment Test best scene number；
Sensitivity analysis module 1305 divides under the best scene number for combining sales data to carry out numerical experiment Analyse the sensitivity that the inventory management decision Optimized model changes different parameters；
Wherein, the different parameters include at least the maintenance time of supplier, the maintenance time of manufacturer and equipment guarantee Phase.
The above-mentioned apparatus implementation method of present embodiment is interior referring to described in first embodiment and second embodiment Hold, details are not described herein.
Four embodiment of the invention is related to a kind of electronic equipment, and the electronic equipment of present embodiment is it may be said that terminal side is set Standby, such as mobile phone, the terminal devices such as tablet computer are also possible to the server of network side.
Figure 14 is the electronic equipment schematic diagram that the 4th embodiment provides according to the present invention.The electronic equipment includes: at least One processor 1401；And the memory 1402 with the communication connection of at least one processor 1401；And with scanning means The communication component 1403 of communication connection, communication component 1403 send and receive data under the control of processor 1401；Wherein, it deposits Reservoir 1402 is stored with the instruction that can be executed by least one processor 1401, instruction by least one processor 1401 execute with It realizes:
It establishes interior to the related library the demand b and the deposit refreshing appliance total amount e in warehouse of refreshing appliance with each period Administrative decision Optimized model is deposited, inventory management decision Optimized model includes dynamic profit function and several constraints；
According to inventory management decision Optimized model, the quantity of each moment purchase of equipment and the number of sale refreshing appliance are determined Amount；
Wherein, dynamic profit function is related in each period the profit on sales of refreshing appliance and purchase new equipment cost, deposits Set the difference of refreshing appliance cost, several constraint include new equipment quantity purchase constraint, refreshing appliance sales volume about Beam and refreshing appliance store number constraint.
Specifically, which includes: one or more processors 1401 and memory 1402, with one in Figure 14 For processor 1401.Processor 1401, memory 1402 can be connected by bus or other modes, to pass through in Figure 14 For bus connection.Memory 1402 is used as a kind of non-volatile computer readable storage medium storing program for executing, can be used for storing non-volatile Software program, non-volatile computer executable program and module.Processor 1401 is stored in memory 1402 by operation In non-volatile software program, instruction and module, thereby executing the various function application and data processing of equipment, i.e., in fact Existing above-mentioned ship disposes management method.
Memory 1402 may include storing program area and storage data area, wherein storing program area can store operation system Application program required for system, at least one function；Storage data area can store the historical data etc. of shipping network transport.This Outside, memory 1402 may include high-speed random access memory, can also include nonvolatile memory, for example, at least one Disk memory, flush memory device or other non-volatile solid state memory parts.In some embodiments, memory 1402 Optional includes the memory remotely located relative to processor 1401, these remote memories can be by being connected to the network to external Equipment.The example of above-mentioned network includes but is not limited to internet, intranet, local area network, mobile radio communication and combinations thereof.
One or more module is stored in memory 1402, when being executed by one or more processor 1401, Execute the equipment inventory management decision optimization method in above-mentioned any means embodiment.
The said goods can be performed the application embodiment provided by method, have the corresponding functional module of execution method and Beneficial effect, the not technical detail of detailed description in the present embodiment, reference can be made to method provided by the application embodiment.
5th embodiment of the invention is related to a kind of non-volatile memory medium, for storing computer-readable program, The computer-readable program is used to execute above-mentioned all or part of embodiment of the method for computer.
That is, it will be understood by those skilled in the art that all or part of the steps in the method for realization above-described embodiment is can Completed with instructing relevant hardware by program, which is stored in a storage medium, including some instructions to So that an equipment (can be single-chip microcontroller, chip etc.) or processor (processor) execute described in each embodiment of the application The all or part of the steps of method.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 be with Store the medium of program 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 (16)

1. a kind of equipment inventory management decision optimization method characterized by comprising
It establishes interior to the related inventory's pipe of the demand b and the deposit refreshing appliance total amount e in warehouse of refreshing appliance with each period Decision optimization model is managed, the inventory management decision Optimized model includes dynamic profit function and several constraints；
According to the inventory management decision Optimized model, determines the quantity of each moment purchase new equipment and sell refreshing appliance Quantity；
Wherein, the dynamic profit function is related in each period the profit on sales of refreshing appliance and purchase new equipment cost, deposits The difference of refreshing appliance cost is set, several described constraints include the sale number of the quantity purchase constraint of new equipment, refreshing appliance Amount constraint stores one or more of number constraint with refreshing appliance.
2. equipment inventory management decision optimization method according to claim 1, which is characterized in that turn in the deposit warehouse New equipment total amount e is determined according to minor function:
eT, s=wT, s+vT, s+aT, s,
Wherein, eT, sFor under s scene period t memory enter the refreshing appliance total amount in warehouse, wT, sFor each cycle t system under s scene Make quotient repair exchange goods equipment after be stored in warehouse number of devices, vT, sFor under s scene each cycle t supplier repair and exchange goods The number of devices in warehouse, a are stored in after equipmentT, sFor under s scene each cycle t supplier repaired return of goods equipment after be stored in warehouse Number of devices.
3. equipment inventory management decision optimization method according to claim 2, which is characterized in that described, vT, s、aT, sAccording to Following formula calculates:
Wherein, κsMeet the probability of manufacturer's service contract, d for the equipment that each cycle customer t need to exchange goods under s sceneT, sFor in s The number of devices that each cycle customer t need to exchange goods under scene, αsFor the qualification rate of each cycle t manufacturer maintenance of equipment under s scene, βsFor the qualification rate of each cycle t supplier maintenance of equipment under s scene, rT, sEach cycle customer t need to return goods under s scene Number of devices.
4. equipment inventory management decision optimization method according to claim 1, which is characterized in that described according to stock control Decision optimization model determines the quantity of each moment purchase new equipment and the quantity of sale refreshing appliance, specifically:
Number of devices b, the refreshing appliance quantity e in deposit warehouse and the carrying cost of equipment paid for according to each cycle demand, solve Each cycle needs the equipment total amount retained；
The equipment total amount retained is needed according to each cycle, using incremental formula and gradient search algorithm, solves each cycle Optimal Inventory it is horizontal；
According to the Optimal Inventory of each cycle horizontal, the described dynamic profit function, the new equipment quantity purchase constraint and The sales volume of the refreshing appliance constrains, and determines the quantity of each moment purchase of equipment and the number of sale refreshing appliance Amount.
5. equipment inventory management decision optimization method according to claim 4, which is characterized in that the depositing according to equipment It is set to this, solves the equipment total amount that each cycle needs to retain, specifically:
According to the carrying cost c of each cycle h equipmentH, s, it is determined that the maximum time of retaining device
According to it is described should retaining device maximum timeWith each cycle h to the demand b of refreshing applianceH, sWith deposit Enter the refreshing appliance total amount e in warehouseH, s, determineNet demand in period section
According to the net demandSolving the equipment total amount that each cycle t needs to retain is oT, s；
Wherein, period h is greater than period t.
6. equipment inventory management decision optimization method according to claim 1, which is characterized in that further include:
Multiple groups experiment is designed, determines the best scene number of the experiment of the inventory management decision Optimized model.
7. equipment inventory management decision optimization method according to claim 6, which is characterized in that further include:
Numerical experiment is carried out in conjunction with sales data, analyzes the inventory management decision Optimized model pair under the best scene number The sensitivity of different parameters variation；
Wherein, the different parameters include at least the maintenance time and equipment guarantee period of the maintenance time of supplier, manufacturer.
8. a kind of equipment inventory management decision optimization system characterized by comprising
Optimized model modeling module, for establishing and the renovation in each period to the demand b of refreshing appliance and deposit warehouse The related inventory management decision Optimized model of equipment total amount e, the inventory management decision Optimized model include dynamic profit function With several constraint one or more of；
Optimizing decision determining module determines the quantity of each moment purchase of equipment according to the inventory management decision Optimized model With the quantity of sale refreshing appliance；
Wherein, the dynamic profit function is related in each period the profit on sales of refreshing appliance and purchase new equipment cost, deposits The difference of refreshing appliance cost is set, several described constraints include the sale number of the quantity purchase constraint of new equipment, refreshing appliance Amount constraint stores number constraint with refreshing appliance.
9. equipment inventory management decision optimization system according to claim 8, which is characterized in that the refreshing appliance total amount E is determined according to minor function:
eT, s=wT, s+vT, s+aT, s,
Wherein, eT, sFor the refreshing appliance total amount in each cycle t deposit warehouse under s scene, wT, sFor each cycle t system under s scene Make quotient repair exchange goods equipment after be stored in warehouse number of devices, vT, sFor under s scene each cycle t supplier repair and exchange goods The number of devices in warehouse, a are stored in after equipmentT, sFor under s scene supplier repaired and be stored in the number of devices in warehouse after return of goods equipment Amount.
10. equipment inventory management decision optimization system according to claim 9, which is characterized in that the wT, s、vT, s、aT, s It calculates according to the following formula:
Wherein, κsMeet the probability of manufacturer's service contract, d for the equipment that each cycle customer t need to exchange goods under s sceneT, sFor in s The number of devices that each cycle customer t need to exchange goods under scene, αsFor the qualification rate of each cycle t manufacturer maintenance of equipment under s scene, βsFor the qualification rate of each cycle t supplier maintenance of equipment under s scene, rT, sEach cycle customer t need to return goods under s scene Number of devices.
11. equipment inventory management decision optimization system according to claim 8, which is characterized in that the optimizing decision is true Cover half block specifically includes:
Retain number calculating section, for the carrying cost according to equipment, solves the equipment total amount that each cycle needs to retain；
Optimal Inventory computing module, the equipment total amount for needing to retain according to each cycle, utilizes incremental formula and ladder Searching algorithm is spent, the Optimal Inventory for solving each cycle is horizontal；
It buys and sells number calculating section, for the dynamic profit function horizontal, described according to the Optimal Inventory of each cycle, described new The quantity purchase constraint of equipment and the sales volume of the refreshing appliance constrain, and determine the quantity of each moment purchase of equipment With the quantity of sale refreshing appliance.
12. equipment inventory management decision optimization system according to claim 11, which is characterized in that the encumbrance meter Module is calculated to specifically include:
Maximum time determining module, for the carrying cost c according to each cycle h equipmentH, s, it is determined that the maximum of retaining device Time
Net demand determining module, for according to should retaining device maximum timeWith each cycle h to renovation The demand b of equipmentH, sWith the refreshing appliance total amount e in deposit warehouseH, s, determineNet demand in period section
Retain quantity determining module, for according to the net demandDetermine that each cycle t needs the equipment total amount that retains to be oT, s；
Wherein, period h is greater than period t.
13. equipment inventory management decision optimization system according to claim 8, which is characterized in that further include:
Scene number determining module determines the best feelings of experiment of the inventory management decision Optimized model for designing multiple groups experiment Scape number.
14. equipment inventory management decision optimization system according to claim 13, which is characterized in that further include:
Sensitivity analysis module analyzes the library under the best scene number for combining sales data to carry out numerical experiment Deposit the sensitivity that administrative decision Optimized model changes different parameters；
Wherein, the different parameters include at least the maintenance time and equipment guarantee period of the maintenance time of supplier, manufacturer.
15. a kind of electronic equipment, which is characterized in that including memory and processor, memory stores computer program, processor Equipment inventory management decision optimization method described in any one of perform claim requirement 1 to 7 when running program.
16. a kind of non-volatile memory medium, for storing computer-readable program, which is characterized in that described computer-readable Program is used for for equipment inventory management decision optimization method described in any one of computer perform claim requirement 1 to 7.
CN201811236373.3A 2018-10-23 2018-10-23 Equipment inventory management decision optimization method, system, electronic equipment and storage medium Pending CN109543881A (en)

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CN113361993A (en) * 2021-05-31 2021-09-07 中国科学技术大学 Data-driven ordering and preventive transfer optimization method and system
CN113467403A (en) * 2021-07-23 2021-10-01 张家口卷烟厂有限责任公司 Cigarette equipment management system and method
CN113505908A (en) * 2021-05-01 2021-10-15 合肥食里挑一网络科技有限公司 Dynamic inventory optimization method
CN113627729A (en) * 2021-07-09 2021-11-09 国网冀北电力有限公司物资分公司 Method and device for determining product quantity and electronic device
CN113793086A (en) * 2020-09-30 2021-12-14 北京沃东天骏信息技术有限公司 Spare capacity determination method and device, computer storage medium and electronic equipment
CN114925896A (en) * 2022-05-10 2022-08-19 中国人民解放军32181部队 Maintenance equipment inventory optimization method, device and system

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CN110826928A (en) * 2019-11-12 2020-02-21 山东怡之家智能科技有限公司 ERP inventory optimization analysis method and system based on big data
CN111126905A (en) * 2019-12-16 2020-05-08 武汉理工大学 Casting enterprise raw material inventory management control method based on Markov decision theory
CN111126905B (en) * 2019-12-16 2023-08-01 武汉理工大学 Casting enterprise raw material inventory management control method based on Markov decision theory
CN111369193A (en) * 2020-03-04 2020-07-03 东莞理工学院 Multi-dimensional inventory control method based on manufacturing-remanufacturing hybrid production system
CN111369193B (en) * 2020-03-04 2023-04-18 东莞理工学院 Multi-dimensional inventory control method based on manufacturing-remanufacturing hybrid production system
CN111639770A (en) * 2020-05-30 2020-09-08 哈尔滨理工大学 Closed-loop supply system model based on product grading recovery remanufacturing and construction method thereof
CN111639770B (en) * 2020-05-30 2023-11-21 哈尔滨理工大学 Closed-loop supply system model based on product grading recovery remanufacturing and building method thereof
CN113793086A (en) * 2020-09-30 2021-12-14 北京沃东天骏信息技术有限公司 Spare capacity determination method and device, computer storage medium and electronic equipment
CN113505908A (en) * 2021-05-01 2021-10-15 合肥食里挑一网络科技有限公司 Dynamic inventory optimization method
CN113505908B (en) * 2021-05-01 2024-01-12 合肥食里挑一网络科技有限公司 Dynamic inventory optimization method
CN113361993B (en) * 2021-05-31 2023-06-23 中国科学技术大学 Data-driven ordering and preventive transferring optimization method and system
CN113361993A (en) * 2021-05-31 2021-09-07 中国科学技术大学 Data-driven ordering and preventive transfer optimization method and system
CN113627729A (en) * 2021-07-09 2021-11-09 国网冀北电力有限公司物资分公司 Method and device for determining product quantity and electronic device
CN113627729B (en) * 2021-07-09 2024-03-15 国网冀北电力有限公司物资分公司 Method and device for determining product quantity and electronic device
CN113467403A (en) * 2021-07-23 2021-10-01 张家口卷烟厂有限责任公司 Cigarette equipment management system and method
CN114925896A (en) * 2022-05-10 2022-08-19 中国人民解放军32181部队 Maintenance equipment inventory optimization method, device and system

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