CN109598400A - A kind of global resource distribution method and device based on distribution model - Google Patents
A kind of global resource distribution method and device based on distribution model Download PDFInfo
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Abstract
This specification embodiment provides a kind of global resource distribution method and device based on distribution model, which comprises resource can be increased by obtaining multiple first；Obtain multiple resource pools；Model of optimizing allocation, so that before compared to optimization, resource can be increased in the case where being currently injected separately into the multiple resource pool for corresponding first in the allocation result based on the distribution model after optimization, the respective valuation in the target date of the multiple resource pool closer to its it is respective on the same day be expected valuation；Based on the allocation result of the distribution model after optimization, resource can be increased by the multiple first and inject the multiple resource pool.
Description
Technical field
This specification embodiment is related to mixed-integer nonlinear programming model optimization, is based on dividing more particularly, to one kind
Global resource distribution method and device with model.
Background technique
In the business of intelligent resource allocation, the resource that can rise in value accordingly is distributed respectively for multiple resource pools.Wherein, described
Multiple resource pools are corresponding with multiple services clients.The resource of rising in value for example including bond etc., with corresponding valuation,
Expiration time and earning rate.In general, each resource pool can all have expected yield when establishing.Intelligent resource allocation
Target be just desirable to can achieve expected yield for the income of resource of rising in value that each resource pool distributes, but simultaneously also not
It will be beyond too many.The problem can be embodied as distributing multiple resources of rising in value to multiple resource pools, while carry out earning rate control
It is controlled with the vacancy rate for the resource that can rise in value.Currently, can by the scale forecast for the resource that can rise in value and the rule progress of tune ginseng manually
Increment resource allocation, matches different rise in value resource and resource pool, and the method is suitable for the resource allocation that can individually rise in value.Cause
This, needs a kind of more effective global resource allocation plan.
Summary of the invention
This specification embodiment is intended to provide a kind of more effectively global resource distribution method and dress based on distribution model
It sets, to solve deficiency in the prior art.
To achieve the above object, this specification provides a kind of global resource distribution side based on distribution model on one side
Method, wherein the distribution model is mixed-integer nonlinear programming model, which comprises
Resource can be increased by obtaining multiple first, wherein the multiple first can increase resource and be exchanged into the respective same day
This and daily valuation, wherein described first can increase the same day switching cost of resource based on first same day that can increase resource
Valuation determines；
Obtain multiple resource pools, wherein each resource pool, which is currently included multiple second had been injected into, can increase resource
With the commutative resource of predetermined quantity, and each resource pool has daily expected valuation, wherein the multiple second can
Increasing resource has respective daily valuation；
The valuation that the resource respective target date after the same day can be increased based on the multiple first and the same day hand over
Change this and the respective commutative resource of the multiple resource pool into, in the expection valuation of the target date and described more
A second can increase the respective valuation in the target date of resource, model of optimizing allocation, so that before compared to optimization,
Allocation result based on the distribution model after optimization can increase resource for corresponding first and currently be injected separately into the multiple money
After the pond of source, the respective valuation in the target date of the multiple resource pool closer to its it is respective on the same day be expected valuation；
And
Based on the allocation result of the distribution model after optimization, resource can be increased by the multiple first and inject the multiple money
Source pond.
In one embodiment, valuation of the resource pool in the target date is the sum of following two: resource pool exists
Include after current injection each first can increase resource and each second can to increase resource respective in the target date
The sum of valuation, the resource pool commutative resource that includes after current injection total amount.
In one embodiment, the resource pool obtains corresponding first and paying the commutative resource of predetermined quantity
The injection of resource can be increased, wherein the commutative resource corresponding with this first of the predetermined quantity can increase the same day of resource
Switching cost is corresponding.
In one embodiment, model of optimizing allocation includes model of optimizing allocation, so that before compared to optimization, in base
The allocation result of distribution model after optimization is injected into the multiple resource currently can increasing resource for the multiple first
In the case where pond, the valuation in the target date in the first resource pond in the multiple resource pool is expected on the same day closer to it
Valuation, wherein in the multiple resource pool, the allocation result based on the distribution model before optimization will be the multiple currently
First can increase in the case where resource is injected into the multiple resource pool, the estimating in the target date in the first resource pond
Value is expected the disparity of valuation with it on the same day.
In one embodiment, the resource pool has intended duration, and model of optimizing allocation includes model of optimizing allocation,
So that the multiple first can be increased currently in the allocation result based on the distribution model after optimization before compared to optimization
In the case where resource is injected into the multiple resource pool, first resource pond in the multiple resource pool in the target date
Valuation be expected valuation on the same day closer to it, wherein in the multiple resource pool, in point based on the distribution model before optimization
With result in the case where currently can increase resource for the multiple first and be injected into the multiple resource pool, the first resource
First parameter in pond and the product of the second parameter are maximum, wherein first parameter is based on the first resource pond described
The valuation of target date and its gap for being expected valuation on the same day determine that second parameter is determined based on relevant influence factor.
In one embodiment, the relevant influence factor includes the first resource pond in the target date distance
The remaining number of days of its Expiration Date.
In one embodiment, the target date be the same day one day after.
In one embodiment, model of optimizing allocation includes passing through simulated annealing, model of optimizing allocation.
In one embodiment, described first can increase resource and the resource pool all has the respective Expiration Date, described
Distribution model includes at least following constraint condition:
Each described first, which can increase resource, can only distribute to a resource pool or be not assigned to any one resource pool；
Each described first, which can increase resource, can only distribute to the resource pool of Expiration Date behind；And
The total amount for the commutative resource that each resource pool includes before current injection, which is more than or equal in current injection, to be injected
Each first can increase the sum of switching cost of resource.
In one embodiment, obtaining multiple first to increase resource includes that can increase resource to the first of acquisition and carry out
Accumulation, and when the first number that can increase resource of accumulation reaches predetermined number or accumulated time is more than the predetermined time, knot
Shu Suoshu accumulation.
In one embodiment, obtaining multiple first to increase resource includes that a batch first can be increased resource and be divided into n
Group, and obtain one group in the n group include multiple first can increase resource, wherein every group in the n group includes number
Essentially identical first can increase resource；
Obtaining multiple resource pools includes obtaining multiple first resource ponds, each first resource pond is divided into n parts, and obtain
A resource pool in n part for taking each first resource pond to include, to obtain the multiple resource pool.
On the other hand this specification provides a kind of global resource distributor based on distribution model, wherein the distribution
Model is mixed-integer nonlinear programming model, and described device includes:
First acquisition unit is configured to, and resource can be increased by obtaining multiple first, wherein the multiple first can increase resource
With respective same day switching cost and daily valuation, wherein the described first same day switching cost that can increase resource is based on should
First same day valuation that can increase resource determines；
Second acquisition unit is configured to, and obtains multiple resource pools, wherein each resource pool, which is currently included, to be had been injected into
The multiple second commutative resources that can increase resource and predetermined quantity, and there is each resource pool daily expection to estimate
Value, wherein the multiple second can increase resource with respective daily valuation；
Optimize unit, is configured to, the resource respective target date after the same day can be increased based on the multiple first
Valuation and the respective commutative resource of the same day switching cost and the multiple resource pool, in the target date
It is expected that valuation and the multiple second can increase the respective valuation in the target date of resource, model of optimizing allocation, so that
Before obtaining compared to optimization, resource can be increased by corresponding first in the allocation result based on the distribution model after optimization and divided currently
Do not inject after the multiple resource pool, the respective valuation in the target date of the multiple resource pool closer to it respectively
On the same day be expected valuation；And
Injection unit is configured to, and based on the allocation result of the distribution model after optimization, can increase money for the multiple first
The multiple resource pool is injected in source.
In one embodiment, valuation of the resource pool in the target date is the sum of following two: resource pool exists
Include after current injection each first can increase resource and each second can to increase resource respective in the target date
The sum of valuation, the resource pool commutative resource that includes after current injection total amount.
In one embodiment, the resource pool obtains corresponding first and paying the commutative resource of predetermined quantity
The injection of resource can be increased, wherein the commutative resource corresponding with this first of the predetermined quantity can increase the same day of resource
Switching cost is corresponding.
In one embodiment, the optimization unit is additionally configured to, model of optimizing allocation, so that before compared to optimization,
The allocation result based on the distribution model after optimization currently by the multiple first can increase resource be injected into it is the multiple
In the case where resource pool, the valuation in the target date in the first resource pond in the multiple resource pool closer to it on the same day
It is expected that valuation, wherein in the multiple resource pool, the allocation result based on the distribution model before optimization will be described currently
Multiple first can increase in the case where resource is injected into the multiple resource pool, the first resource pond in the target date
Valuation and its on the same day be expected valuation disparity.
In one embodiment, the resource pool has intended duration, and the optimization unit is additionally configured to, optimization distribution mould
Type so that before compared to optimization, the allocation result based on the distribution model after optimization can by the multiple first currently
Increase in the case where resource is injected into the multiple resource pool, the first resource pond in the multiple resource pool described predetermined
The valuation on date is expected valuation closer to it on the same day, wherein in the multiple resource pool, based on the distribution model before optimization
Allocation result in the case where currently can increase resource for the multiple first and be injected into the multiple resource pool, described first
The product of first parameter of resource pool and the second parameter is maximum, wherein first parameter is existed based on the first resource pond
The valuation of the target date and its gap for being expected valuation on the same day determine that it is true that second parameter is based on relevant influence factor
It is fixed.
In one embodiment, the optimization unit is additionally configured to, and passes through simulated annealing, model of optimizing allocation.
In one embodiment, described first can increase resource and the resource pool all has the respective Expiration Date, described
Distribution model includes at least following constraint condition:
Each described first, which can increase resource, can only distribute to a resource pool or be not assigned to any one resource pool；
Each described first, which can increase resource, can only distribute to the resource pool of Expiration Date behind；And
The total amount for the commutative resource that each resource pool includes before current injection, which is more than or equal in current injection, to be injected
Each first can increase the sum of switching cost of resource.
In one embodiment, the first acquisition unit is additionally configured to, to the first of acquisition can increase resource carry out it is tired
Product, and when the first number that can increase resource of accumulation reaches predetermined number or accumulated time is more than the predetermined time, terminate
The accumulation.
In one embodiment, the first acquisition unit is additionally configured to, and a batch first can be increased resource and be divided into n
Group, and obtain one group in the n group include multiple first can increase resource, wherein every group in the n group includes number
Essentially identical first can increase resource；
The second acquisition unit is additionally configured to, and obtains multiple first resource ponds, and each first resource pond is divided into n
Part, and a resource pool in n part that each first resource pond includes is obtained, to obtain the multiple resource pool.
On the other hand this specification provides a kind of calculating equipment, including memory and processor, which is characterized in that described to deposit
It is stored with executable code in reservoir, when the processor executes the executable code, realizes any of the above-described method.
By the intelligent global assignment scheme according to this specification embodiment, the intelligent and automatic of assets investment is realized
To change, the program does not depend on asset size prediction and adjusts ginseng manually, but carries out problem modeling and solution from the angle of global optimization,
It, which surpasses, proofreads less, is not necessarily to manual intervention, intelligent and automation may be implemented；Moreover, it is achieved that the batch decision of assets investment,
The program carries out accumulated process to assets first, and then carries out mass distributed decision, so as to realize that the overall situation in batch is excellent
Change.
Detailed description of the invention
This specification embodiment is described in conjunction with the accompanying drawings, and this specification embodiment can be made clearer:
Fig. 1 shows the schematic diagram of the global resource distribution system 100 according to this specification embodiment；
Fig. 2 shows a kind of global resource distribution methods based on distribution model according to this specification embodiment；
Fig. 3 shows the schematic diagram for carrying out asset allocation to n fund pool and injecting；
Fig. 4 shows the schematic diagram of the multiple groups global assignment；And
Fig. 5 shows a kind of global resource distributor 500 based on distribution model according to this specification embodiment.
Specific embodiment
This specification embodiment is described below in conjunction with attached drawing.
Fig. 1 shows the schematic diagram of the global resource distribution system 100 according to this specification embodiment.The system is used for will be more
A resource allocation that increases to multiple resource pools, in the resource pool include commutative resource and it is multiple obtained increase money
Source.The resource that increases is, for example, assets, the assets are for example wrapped with the corresponding amount of money, expiration time and earning rate
Include bond etc..Commutative resource can be it is various can in market with the resource of certain price free exchange, be, for example, currency,
Fund etc..The resource pool is, for example, fund pool comprising the initial capital of predetermined number, and by paying the purchase of part fund
Assets and obtain multiple assets.To be hereinafter described by taking assets and fund pool as an example, but embodiment can be generalized to it is suitable
It is other possible to increase resource and commutative resource.
As shown in Figure 1, system 100 includes assets accumulation module 11, the first grouping module 12, second packet module 13, divides
With model 14, merging module 15 and distribution module 16.First in assets accumulation module 11, to the assets of the acquisition of system 100
Added up.The system 100 be, for example, Alipay server, constantly from each client receive client loan, flower
Draw equal business activities, which draws fund and all can serve as assets and added up.In the first grouping module 12,
A collection of assets are divided into n group at random.In second packet module 13, obtained and each fund pool is divided into n parts respectively
N group fund pool is taken, wherein the portion in n part in every group of fund pool including each fund pool.Distribution model 14 includes multiple calculations
Method module (schematically illustrate in figure is three), wherein each algoritic module is to the one group of assets and n group fund pool in n group assets
In one group of fund pool carry out asset allocation.Specifically, one group of asset allocation is given one by Optimized model by each algoritic module
Group fund pool, and valuation tomorrow of each fund pool in this group of fund pool after distribution is made to approach its tomorrow of expected valuation.
Merging module 15 is for combining the above-mentioned distribution to n group assets.And distribution module 16 is used for based on above-mentioned distribution model 14
Allocation result distributes the n group assets to the n group fund pool respectively.
System 100 shown in FIG. 1 is only schematical, and the system according to this specification embodiment is without being limited thereto, for example, being
The a collection of asset allocation that the allocation result that system 100 can be directly based upon distribution model will acquire is to multiple fund pools, without right
It is grouped respectively.For example, may include n algoritic module in distribution model, carried out respectively for each pair of group of assets and money
The distribution of Jin Chi group optimizes.
Fig. 2 shows a kind of global resource distribution methods based on distribution model according to this specification embodiment, wherein institute
Stating distribution model is mixed-integer nonlinear programming model, and this method is for example executed in server end, which comprises
In step S202, resource can be increased by obtaining multiple first, wherein the multiple first can increase resource with respective
Same day switching cost and daily valuation, wherein the described first same day switching cost that can increase resource, which is based on this, first can increase
The same day valuation of long resource determines；
In step S204, multiple resource pools are obtained, wherein each resource pool is currently included multiple second had been injected into
The commutative resource of resource and predetermined quantity can be increased, and each resource pool has daily expected valuation, wherein described
Multiple second can increase resource with respective daily valuation；
In step S206, the resource respective target date after the same day can be increased based on the multiple first valuation and
The same day switching cost and the respective commutative resource of the multiple resource pool, the expection in the target date are estimated
Value and the multiple second can increase the respective valuation in the target date of resource, model of optimizing allocation, so that comparing
Before optimization, resource can be increased by corresponding first in the allocation result based on the distribution model after optimization and be injected separately into currently
In the case where the multiple resource pool, the respective valuation in the target date of the multiple resource pool is respective closer to its
It is expected valuation on the same day；And
In step S208, based on the allocation result of the distribution model after optimization, resource note can be increased by the multiple first
Enter the multiple resource pool.
Firstly, in step S202, resource can be increased by obtaining multiple first, wherein the multiple first can increase resource and have
Respective same day switching cost and daily valuation, wherein described first can increase resource same day switching cost be based on this first
The same day valuation that resource can be increased determines.As described in reference diagram 1 above, can increase resource is that one kind has the corresponding amount of money, arrives
The resource of time phase and earning rate, are illustrated by taking assets as an example here.Here can increase resource representation with first will be current
Fund pool is distributed in the distribution of round but also unappropriated assets, i.e. the first assets.As it was noted above, server end example
For example Alipay server end, constantly receive the loan of client, flower the business activities such as draw, the loan fund,
Drawing fund can be seen as assets.To which server end can constantly receive new assets.By since particular moment
It is accumulative to carry out assets, the multiple first assets can be obtained.Before starting accumulative assets, the predetermined of this batch of assets can be set
Number and time-out time.After starting accumulative assets, when the number of accumulative assets reaches the predetermined number or adds up
When time is more than the time-out time, the accumulative of this batch of assets can be terminated, so as to obtain the multiple first assets.Described
Capital, following gross interest and first assets of the daily valuation of one assets for example based on the assets obtain in the remaining time limit of this day
It takes, for example, as shown in formula (1):
The same day switching cost of first assets is for example the same day valuation of the assets.By formula (1) as it can be seen that single
The daily valuation of assets is fewer and fewer with remaining number of days, and daily valuation is gradually increased.That is, the assets the same day it
Daily valuation afterwards is all higher than same day valuation.
In step S204, multiple resource pools are obtained, wherein including multiple second had been injected into before each resource pool can
Increase the commutative resource of resource and predetermined quantity, and each resource pool has daily expected valuation, wherein described more
A second can increase resource with respective daily valuation.
As described in reference diagram 1 above, resource pool is, for example, fund pool.Fund pool is, for example, (such as to be paid by investment platform
It is precious) it signs a contract and establishes with certain banks or enterprise, initial capital is provided for corresponding fund pool by these companies, by
Investment platform buys assets to corresponding fund pool for it.Fig. 3 is shown to n fund pool progress asset allocation and injection is shown
It is intended to.As shown in figure 3, fund pool 1, fund pool 2 ... fund pool n is, for example, to build between investment platform and each bank or enterprise
Vertical fund pool, assets will be injected into the assets of n fund pool, this specification for what the investment platform obtained in a wheel injection
The method of embodiment is the asset allocation for optimizing this to multiple fund pools.In general, each fund pool can be limited when establishing
Expected yield and Expiration Date.The target of the method for this specification embodiment is exactly so that the assets for the purchase of each fund pool are received
Benefit can achieve expected earning rate at the date of maturity, but also not get higher than simultaneously too much, preferably.
After initialization, in order to make earning rate in control range always, investment platform can be the fund pool to fund pool
Every day in time limit all presets an earning rate range, so that final earning rate is controllable volume.And in daily, investment
Platform will do it purchase of more wheels to assets, for example, being within every 15 minutes a wheel, every wheel buys 20,000 assets.To work as
Before the assets investment of preceding round, assets (being hereafter expressed as the second assets) and remaining money have been bought including multiple in the fund pool
Gold.Second assets have respective daily valuation as first assets.Wherein, by based on each fund pool
Expected yield can obtain its daily expected yield.Daily expected yield based on fund pool, can obtain the every of fund pool
Day expected valuation.
In step S206, the resource respective target date after the same day can be increased based on the multiple first valuation and
The same day switching cost and the respective commutative resource of the multiple resource pool, the expection in the target date are estimated
Value and the multiple second can increase the respective valuation in the target date of resource, model of optimizing allocation, so that comparing
Before optimization, resource can be increased by corresponding first in the allocation result based on the distribution model after optimization and be injected separately into currently
In the case where the multiple resource pool, the respective valuation in the target date of the multiple resource pool is respective closer to its
It is expected valuation on the same day.
The distribution model is mixed-integer nonlinear programming model, includes integer type in decision variable in the model
The Non-Linear Programming of variable and continuous variable.For example, in the model, it is assumed that multiple resource pools are M resource pool, then with Vi
Indicate the valuation of target date after the same day of i-th of resource pool after epicycle injection, wherein i value is 1 to M.Working as
Target date after day can be a cycle of the earning rate for controlling fund pool set, such as can be one
It, two days, one week etc., will be hereafter illustrated for one day, that is, the target date after the same day is the latter of the same day
It, that is, tomorrow.After epicycle injection, i-th of resource pool is shown in the valuation such as formula (2) of tomorrow:
Vi=∑kAV(pk)+CCi+∑jXij*(AV(pj)-C(pj)) (2)
Wherein, AV (pj) indicating valuation of j-th of first assets in tomorrow of epicycle injection, wherein the value of j is 1 to arrive
N, that is, epicycle assets investment is filled with N number of assets to M fund pool altogether.C(pj) indicate to buy jth in epicycle assets investment
The cost of a assets.As it was noted above, C (pj) it can be equal to the same day valuations of the assets.XijValue is 0 or 1, wherein when taking 0,
It indicates in epicycle injection, unimplanted i-th of the fund pool of j-th of assets, when taking 1, indicates in epicycle injection, j-th of assets
Inject i-th of fund pool, that is, the selection whether every assets are only put into each fund pool, i.e., 0 or 1.AV(pk) indicate
Valuation of k-th of second assets being had been injected into preceding i-th of the fund pool of epicycle injection in tomorrow, wherein the value of k arrives for 1
Q, that is, i-th of fund pool has been injected into Q the second assets before epicycle injection.CCiIt indicates before epicycle injection, i-th of cash
Remaining cash amount in pond.From formula (2) as can be seen that after epicycle injection, valuation of i-th of resource pool in tomorrow is pond
In assets (the first assets and the second assets) the sum of valuation of tomorrow and epicycle injection after remaining cash it is (preflood
Remaining cash subtract epicycle injection cost) summation.
In addition, there is the following constraint indicated with formula (3)-(5) for the parameter in the injection of above-mentioned epicycle:
Wherein, formula (3) indicates that every assets can only be put into a fund pool, or not be put into any fund pool；In public affairs
In formula (4), EDiIndicate the Expiration Date of i-th of fund pool, EDjIndicate the Expiration Date of j-th of first assets, formula (4) indicates, often
Assets, which can choose, is put into the fund pool of any Expiration Date behind；Formula (5) indicates that each resource pool is before current injection
The total amount for the remaining cash for including is more than or equal to the sum of the switching cost for each first assets injected in current injection.
Distribution model in this specification embodiment passes through optimization XijValue (0 or 1) come so that each fund pool this
Take turns the expection valuation E after injecting in the valuation of tomorrow closer to its tomorrowi.Wherein, the expection valuation E in tomorrow of fund pooli
Can the expection annualized return based on the fund pool calculated and obtain by simulation program, for example, being averaged by the way that annualized return will be expected
To every day, to obtain daily expected yield.
In one embodiment, shown in the objective function of the distribution model such as formula (6):
As shown in formula (6), which is indicated, so that V in M fund pooliWith EiThe maximum fund pool of difference is estimated
It is worth error to reduce.By the objective function, by repeatedly circulation, the valuation for constantly reducing that maximum fund pool of difference is missed
Difference, so that the valuation error of each fund pool of M fund pool is smaller, that is, so that valuation tomorrow of each fund pool is more
Close to its tomorrow of expected valuation.
In one embodiment, shown in the objective function of the distribution model such as formula (7):
Wherein, WiIndicate other factors influence, including fund pool " urgent " degree (fund pool residue number of days it is more few more
Preferentially), the priority (the more assets residue number of days the more preferential) etc. of asset allocation.WiSuch as it is obtained by formula (8), wherein LDi
Indicate that the remaining number of days of fund pool i, α are the coefficient of elasticity of remaining number of days influence power:
It is appreciated that the objective function of the distribution model is not limited to as shown in formula (6) or (7), and this can be passed through
The retrievable other forms in field, for example, the objective function can for each fund pool valuation error quadratic sum, absolutely
It is worth and waits forms.
From formula (2) as it can be seen that the distribution model be mixed-integer nonlinear programming model, optimize the distribution model namely
Solve the problems, such as mixed integer nonlinear programming.Therefore, when being based on objective function optimization distribution model, such as simulation can be used and move back
A kind of fiery algorithm (heuritic approach), model of optimizing allocation.It is calculated it is appreciated that the optimization method is not limited to above-mentioned simulated annealing
Method, but can be using various for solving the calculation of mixed integer nonlinear programming problem obtained by those skilled in the art
Method, such as branch and bound method, ant group algorithm, particle swarm algorithm, are not described in detail one by one herein.
Finally, in step S208, based on the allocation result of the distribution model after optimization, money can be increased by the multiple first
The multiple resource pool is injected in source.After S206 model of optimizing allocation through the above steps, based on the distribution model after optimization
Allocation result N number of first assets are injected to M fund pool so that valuation tomorrow of each fund pool closer to its
Tomorrow is expected valuation, to optimize the global assignment of assets.
In one embodiment, in the case where the amount of assets of a wheel injection is larger, the assets of a wheel injection can be divided equally
For multiple groups assets, multiple fund pools are also carried out it is corresponding divide equally, to carry out multiple groups global assignment.It is complete that Fig. 4 shows the multiple groups
The schematic diagram that score of the game is matched.The a collection of assets that left side includes in Fig. 4 for a wheel injection, i.e., above-mentioned first assets, for example (,) it is random
It is divided into n group assets, G1、G2、…Gn, wherein every group of assets GiIn include essentially identical amount of assets.
As shown in figure 4, right side is m fund pool, including fund pool P1、P2、…Pm, each fund pool is divided equally
For n parts of (q1、q2、…qn).Wherein, a fund pool qjIncluding remaining cash amount be corresponding fund pool PiIncluding remaining money
The 1/n of gold amount, the portion fund pool qjIncluding the sum of the valuation of the second assets (having been injected into assets) be corresponding fund pool Pi
Including the sum of the valuation of the second assets 1/n, the portion fund pool qjDaily expected valuation be corresponding fund pool Pi's
The 1/n of daily expected valuation.By obtaining each fund pool PiRespective portion fund pool, can obtain including m qjOne group of money
Jin Chi, for example, obtaining each fund pool PiRespective portion fund pool p1, first group of fund pool can be obtained, each fund pool is obtained
PiRespective portion fund pool p2, second group of fund pool can be obtained, thus, n group fund pool can be obtained.
By it is above-mentioned respectively to the grouping of assets and fund pool after, can respectively to each grouping implement shown in Fig. 2 point
Method of completing the square.For example, as shown in figure 4, carrying out Fig. 2 institute to first group of assets G1 and first group of fund pool by algoritic module G1-AD
The global resource distribution method shown, thus, include to first group of fund pool by each assets investment that first group of assets G1 includes
Each fund pool q1.Similarly, second group of assets G2 and second group of fund pool are carried out by algoritic module G2-AD described complete
Office's resource allocation ... carries out the global resource distribution to n-th group assets Gn and n-th group fund pool by algoritic module Gn-AD.
To in integrated decision-making object module, the distribution of comprehensive each algoritic module obtains a collection of assets injected to the wheel to more
A fund pool PiGlobal assignment.
It is appreciated that global assignment scheme shown in Fig. 4 is only schematical, it is not intended to limit the complete of this specification embodiment
Office's allocation plan for example, algoritic module shown in Fig. 4 is not limited to n, and can be arbitrary number, for example, only including
In the case where one algoritic module, successively n group assets can be allocated, to obtain the allocation result to total assets.
Fig. 5 shows a kind of global resource distributor 500 based on distribution model according to this specification embodiment,
In, the distribution model is mixed-integer nonlinear programming model, and described device includes:
First acquisition unit 51, is configured to, and resource can be increased by obtaining multiple first, wherein the multiple first can increase money
Source has respective same day switching cost and daily valuation, wherein the described first same day switching cost that can increase resource is based on
First same day valuation that can increase resource determines；
Second acquisition unit 52, is configured to, and obtains multiple resource pools, wherein each resource pool, which is currently included, have been infused
Multiple second entered can increase the commutative resource of resource and predetermined quantity, and there is each resource pool daily expection to estimate
Value, wherein the multiple second can increase resource with respective daily valuation；
Optimize unit 53, is configured to, the resource respective target date after the same day can be increased based on the multiple first
Valuation and the same day switching cost and the respective commutative resource of the multiple resource pool, in the target date
Expection valuation and the multiple second can increase the respective valuation in the target date of resource, model of optimizing allocation, with
So that resource can be increased current by corresponding first in the allocation result based on the distribution model after optimization before compared to optimization
In the case where being injected separately into the multiple resource pool, the respective valuation in the target date of the multiple resource pool is closer
Its respective valuation expected on the same day；And
Injection unit 54, is configured to, and based on the allocation result of the distribution model after optimization, the multiple first can be increased
Resource injects the multiple resource pool.
In one embodiment, valuation of the resource pool in the target date is the sum of following two: resource pool exists
Include after current injection each first can increase resource and each second can to increase resource respective in the target date
The sum of valuation, the resource pool commutative resource that includes after current injection total amount.
In one embodiment, the resource pool obtains corresponding first and paying the commutative resource of predetermined quantity
The injection of resource can be increased, wherein the commutative resource corresponding with this first of the predetermined quantity can increase the same day of resource
Switching cost is corresponding.
In one embodiment, the optimization unit 53 is additionally configured to, model of optimizing allocation, so that compared to optimization
Before, the allocation result based on the distribution model after optimization currently by the multiple first can increase resource be injected into it is described more
In the case where a resource pool, the valuation in the target date in the first resource pond in the multiple resource pool is same closer to it
Day expected valuation, wherein in the multiple resource pool, in the allocation result based on the distribution model before optimization currently by institute
Stating multiple first can increase in the case where resource is injected into the multiple resource pool, the first resource pond on the pre- settled date
The valuation of phase and its disparity for being expected valuation on the same day.
In one embodiment, the resource pool has intended duration, and the optimization unit 53 is additionally configured to, optimization distribution
Model, so that before compared to optimization, in the allocation result based on the distribution model after optimization currently by the multiple first
Can increase in the case where resource is injected into the multiple resource pool, the first resource pond in the multiple resource pool described pre-
The valuation fixed the date is expected valuation closer to it on the same day, wherein in the multiple resource pool, based on the distribution mould before optimization
The allocation result of type is in the case where currently can increase resource for the multiple first and be injected into the multiple resource pool, and described
First parameter of one resource pool and the product of the second parameter are maximum, wherein first parameter is based on the first resource pond
Determine that second parameter is based on relevant influence factor in the valuation of the target date and its gap for being expected valuation on the same day
It determines.
In one embodiment, the optimization unit 53 is additionally configured to, and passes through simulated annealing, model of optimizing allocation.
In one embodiment, described first can increase resource and the resource pool all has the respective Expiration Date, described
Distribution model includes at least following constraint condition:
Each described first, which can increase resource, can only distribute to a resource pool or be not assigned to any one resource pool；
Each described first, which can increase resource, can only distribute to the resource pool of Expiration Date behind；And
The total amount for the commutative resource that each resource pool includes before current injection, which is more than or equal in current injection, to be injected
Each first can increase the sum of switching cost of resource.
In one embodiment, the first acquisition unit 51 is additionally configured to, and can be increased resource to the first of acquisition and be carried out
Accumulation, and when the first number that can increase resource of accumulation reaches predetermined number or accumulated time is more than the predetermined time, knot
Shu Suoshu accumulation.
In one embodiment, the first acquisition unit 51 is additionally configured to, and a batch first can be increased resource and be divided into n
Group, and obtain one group in the n group include multiple first can increase resource, wherein every group in the n group includes number
Essentially identical first can increase resource；
The second acquisition unit 52 is additionally configured to, and obtains multiple first resource ponds, and each first resource pond is divided into n
Part, and a resource pool in n part that each first resource pond includes is obtained, to obtain the multiple resource pool.
On the other hand this specification provides a kind of calculating equipment, including memory and processor, which is characterized in that described to deposit
It is stored with executable code in reservoir, when the processor executes the executable code, realizes method shown in Fig. 2.
By the intelligent global assignment scheme according to this specification embodiment, the intelligent and automatic of assets investment is realized
To change, the program does not depend on asset size prediction and adjusts ginseng manually, but carries out problem modeling and solution from the angle of global optimization,
It, which surpasses, proofreads less, is not necessarily to manual intervention, intelligent and automation may be implemented；Moreover, it is achieved that the batch decision of assets investment,
The program carries out accumulated process to assets first, and then carries out mass distributed decision, so as to realize that the overall situation in batch is excellent
Change.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for system reality
For applying example, since it is substantially similar to the method embodiment, so being described relatively simple, related place is referring to embodiment of the method
Part explanation.
It is above-mentioned that this specification specific embodiment is described.Other embodiments are in the scope of the appended claims
It is interior.In some cases, the movement recorded in detail in the claims or step can be come according to the sequence being different from embodiment
It executes and desired result still may be implemented.In addition, process depicted in the drawing not necessarily require show it is specific suitable
Sequence or consecutive order are just able to achieve desired result.In some embodiments, multitasking and parallel processing be also can
With or may be advantageous.
Those of ordinary skill in the art should further appreciate that, describe in conjunction with the embodiments described herein
Each exemplary unit and algorithm steps, can be realized with electronic hardware, computer software, or a combination of the two, in order to clear
Illustrate to Chu the interchangeability of hardware and software, generally describes each exemplary group according to function in the above description
At and step.These functions hold track actually with hardware or software mode, depending on technical solution specific application and set
Count constraint condition.Those of ordinary skill in the art can realize each specific application using distinct methods described
Function, but this realization is it is not considered that exceed scope of the present application.
The step of method described in conjunction with the examples disclosed in this document or algorithm, can hold track with hardware, processor
Software module or the combination of the two implement.Software module can be placed in random access memory (RAM), memory, read-only storage
Device (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technology neck
In any other form of storage medium well known in domain.
Above-described specific embodiment has carried out further the purpose of the present invention, technical scheme and beneficial effects
It is described in detail, it should be understood that being not intended to limit the present invention the foregoing is merely a specific embodiment of the invention
Protection scope, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should all include
Within protection scope of the present invention.
Claims (23)
1. a kind of global resource distribution method based on distribution model, wherein the distribution model is the non-linear rule of MIXED INTEGER
Draw model, which comprises
Resource can be increased by obtaining multiple first, wherein the multiple first can increase resource with respective same day switching cost and
Daily valuation, wherein described first can increase the same day switching cost of resource based on first same day valuation that can increase resource
It determines；
Obtain multiple resource pools, wherein each resource pool, which is currently included multiple second had been injected into, can increase resource and pre-
The commutative resource of fixed number amount, and each resource pool has daily expected valuation, wherein and the multiple second can increase
Resource has respective daily valuation；
The valuation and the same day that the resource respective target date after the same day can be increased based on the multiple first are exchanged into
This and the respective commutative resource of the multiple resource pool, in the expection valuation of the target date and the multiple the
Two can increase the respective valuation in the target date of resource, model of optimizing allocation, so that being based on before compared to optimization
The allocation result of distribution model after optimization can increase resource for corresponding first and currently be injected separately into the multiple resource pool
In the case where, the respective valuation in the target date of the multiple resource pool closer to its it is respective on the same day be expected valuation；
And
Based on the allocation result of the distribution model after optimization, resource can be increased by the multiple first and inject the multiple resource
Pond.
2. according to the method described in claim 1, wherein, valuation of the resource pool in the target date be following two it
Include after current injection with: resource pool each first can increase resource and each second can to increase resource respective in institute
State the total amount of the sum of valuation of target date, the commutative resource that resource pool includes after current injection.
3. according to the method described in claim 2, wherein the resource pool is obtained and paying the commutative resource of predetermined quantity
Take the corresponding first injection that can increase resource, wherein the commutative resource corresponding with this first of the predetermined quantity can increase
The same day switching cost of long resource is corresponding.
4. according to the method described in claim 1, wherein, model of optimizing allocation includes model of optimizing allocation, so that compared to
Before optimization, institute is injected into currently resource can be increased by the multiple first in the allocation result based on the distribution model after optimization
In the case where stating multiple resource pools, the valuation in the target date in the first resource pond in the multiple resource pool is closer
It is expected valuation on the same day, wherein in the multiple resource pool, in the allocation result based on the distribution model before optimization current
The multiple first can be increased in the case where resource is injected into the multiple resource pool, the first resource pond described pre-
The valuation fixed the date and its disparity for being expected valuation on the same day.
5. according to the method described in claim 1, wherein, the resource pool has intended duration, and model of optimizing allocation includes, excellent
Change distribution model so that before compared to optimization, the allocation result based on the distribution model after optimization will be described more currently
A first can increase in the case where resource is injected into the multiple resource pool, the first resource pond in the multiple resource pool
The valuation of the target date is expected valuation closer to it on the same day, wherein in the multiple resource pool, before based on optimization
The allocation result of distribution model in the case where currently can increase resource for the multiple first and be injected into the multiple resource pool,
First parameter in the first resource pond and the product of the second parameter are maximum, wherein first parameter is based on first money
Gap that valuation is expected in the valuation in the target date in source pond with it on the same day determines that second parameter is based on relevant shadow
The factor of sound determines.
6. according to the method described in claim 5, wherein, the relevant influence factor includes the first resource pond described
Remaining number of days of the target date apart from its Expiration Date.
7. according to the method described in claim 1, wherein, the target date be the same day one day after.
8. according to the method described in claim 1, wherein, model of optimizing allocation includes passing through simulated annealing, optimization distribution
Model.
9. according to the method described in claim 1, wherein, described first can increase resource and the resource pool all have it is respective
Expiration Date, the distribution model include at least following constraint condition:
Each described first, which can increase resource, can only distribute to a resource pool or be not assigned to any one resource pool；
Each described first, which can increase resource, can only distribute to the resource pool of Expiration Date behind；And
The total amount for the commutative resource that each resource pool includes before current injection is each more than or equal to injecting in current injection
A first can increase the sum of switching cost of resource.
10. according to the method described in claim 1, wherein, obtains multiple first and can increase resource and include, it can to the first of acquisition
Increase resource to be accumulated, and reaches predetermined number in the first number that can increase resource of accumulation or accumulated time is more than
When the predetermined time, terminate the accumulation.
11. according to the method described in claim 1, wherein,
Obtaining multiple first to increase resource includes that a batch first can be increased resource and be divided into n group, and obtained in the n group
One group include multiple first can increase resource, wherein every group in the n group to include that number is essentially identical first can increase
Long resource；
Obtaining multiple resource pools includes obtaining multiple first resource ponds, each first resource pond is divided into n parts, and obtain every
A resource pool in n part that a first resource pond includes, to obtain the multiple resource pool.
12. a kind of global resource distributor based on distribution model, wherein the distribution model is the non-linear rule of MIXED INTEGER
Model is drawn, described device includes:
First acquisition unit is configured to, and obtaining multiple first can increase resource, wherein the multiple first can increase resource and have
Respective same day switching cost and daily valuation, wherein described first can increase resource same day switching cost be based on this first
The same day valuation that resource can be increased determines；
Second acquisition unit is configured to, and obtains multiple resource pools, wherein each resource pool be currently included have been injected into it is more
A second can increase the commutative resource of resource and predetermined quantity, and each resource pool has daily expected valuation,
In, the multiple second can increase resource with respective daily valuation；
Optimize unit, is configured to, the valuation that the resource respective target date after the same day can be increased based on the multiple first
With the respective commutative resource of the same day switching cost and the multiple resource pool, in the expection of the target date
Valuation and the multiple second can increase the respective valuation in the target date of resource, model of optimizing allocation, so that phase
Than that can increase resource for corresponding first in the allocation result based on the distribution model after optimization and be infused respectively currently before optimization
In the case where entering the multiple resource pool, the respective valuation in the target date of the multiple resource pool closer to it respectively
On the same day be expected valuation；And
Injection unit is configured to, and based on the allocation result of the distribution model after optimization, can increase resource note for the multiple first
Enter the multiple resource pool.
13. device according to claim 12, wherein valuation of the resource pool in the target date is following two
The sum of: resource pool include after current injection each first can increase resource and each second can increase resource it is respective
The total amount for the commutative resource that the sum of valuation of the target date, resource pool include after current injection.
14. device according to claim 13, wherein the resource pool is and paying the commutative resource of predetermined quantity
The injection of resource can be increased by obtaining corresponding first, wherein the commutative resource corresponding with this first of the predetermined quantity can
The same day switching cost for increasing resource is corresponding.
15. device according to claim 12, wherein the optimization unit is additionally configured to, model of optimizing allocation, so that
Before optimization, resource note can be increased by the multiple first currently in the allocation result based on the distribution model after optimization
In the case where entering to the multiple resource pool, the valuation in the target date in the first resource pond in the multiple resource pool
It is expected valuation on the same day closer to it, wherein in the multiple resource pool, in the allocation result based on the distribution model before optimization
In the case where currently can increase resource for the multiple first and be injected into the multiple resource pool, the first resource pond
The valuation of the target date and its disparity for being expected valuation on the same day.
16. device according to claim 12, wherein the resource pool has intended duration, and the optimization unit is also matched
It is set to, model of optimizing allocation, so that currently will before compared to optimization in the allocation result based on the distribution model after optimization
The multiple first can increase in the case where resource is injected into the multiple resource pool, the first resource in the multiple resource pool
The valuation in the target date in pond is expected valuation closer to it on the same day, wherein in the multiple resource pool, based on excellent
The allocation result of distribution model before change is injected into the multiple resource pool currently can increasing resource for the multiple first
In situation, first parameter in the first resource pond and the product of the second parameter are maximum, wherein first parameter is based on described
Gap that valuation is expected in the valuation in the target date in first resource pond with it on the same day determines that second parameter is based on phase
The influence factor of pass determines.
17. device according to claim 16, wherein the relevant influence factor includes the first resource pond in institute
State remaining number of days of the target date apart from its Expiration Date.
18. device according to claim 12, wherein the target date be the same day one day after.
19. device according to claim 12, wherein the optimization unit is additionally configured to, excellent by simulated annealing
Change distribution model.
20. device according to claim 12, wherein described first, which can increase resource and the resource pool, all has respectively
Expiration Date, the distribution model include at least following constraint condition:
Each described first, which can increase resource, can only distribute to a resource pool or be not assigned to any one resource pool；
Each described first, which can increase resource, can only distribute to the resource pool of Expiration Date behind；And
The total amount for the commutative resource that each resource pool includes before current injection is each more than or equal to injecting in current injection
A first can increase the sum of switching cost of resource.
21. device according to claim 12, wherein the first acquisition unit is additionally configured to, can to the first of acquisition
Increase resource to be accumulated, and reaches predetermined number in the first number that can increase resource of accumulation or accumulated time is more than
When the predetermined time, terminate the accumulation.
22. device according to claim 12, wherein
The first acquisition unit is additionally configured to, and a batch first can be increased resource and be divided into n group, and obtained in the n group
One group include multiple first can increase resource, wherein every group in the n group to include that number is essentially identical first can increase
Resource；
The second acquisition unit is additionally configured to, and obtains multiple first resource ponds, and each first resource pond is divided into n parts, and
A resource pool in n part that each first resource pond includes is obtained, to obtain the multiple resource pool.
23. a kind of calculating equipment, including memory and processor, which is characterized in that be stored with executable generation in the memory
Code realizes method of any of claims 1-11 when the processor executes the executable code.
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