CN109359777A - For the Express firm city distribution method under demand blowout - Google Patents
For the Express firm city distribution method under demand blowout Download PDFInfo
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Abstract
The present invention provides a kind of Express firm city distribution methods under blowout for demand, comprising steps of (1) visits and investigates related electric business, acquire the order volume under the blowout of electric business demand, based on big data information, analyze the characteristics of City Object dispense under demand blowout situation and there are the problem of；(2) using distribution time, distribution cost, dispatching three indexs of fairness as target, with the path planning model of mathematical modeling building multiple target, optimal Distribution path is obtained；(3) judgment matrix that 3 targets compare two-by-two is constructed with analytic hierarchy process (AHP), the relative weighting for being haggled over element is calculated by judgment matrix, determines the weight of each optimization aim；(4) its city distribution model is solved using multiple target heuritic approach；The present invention proposes the optimization strategy in the case of demand blowout by the modeling and optimization in the city distribution path to express delivery, promotes service ability of the Express firm under demand blowout situation.
Description
Technical field
The invention belongs to logistics technology, and in particular to one kind is for fast under demand blowout (i.e. growth rate quickly)
Pass enterprise's city distribution method.
Background technique
With flourishing for e-commerce, " double 11 " (i.e. shopping Carnival) have become major electric business and improve profit
Important sources, " on double 11 " activity same day, the whole network sales volume is up to 254,000,000,000 yuan within 2017 according to statistics.The package of electric business logistics in 2017
It counts up to 23,500,000,000, remove " on the day of double 11 ", average daily 0.6 hundred million, and " the package number generated on the day of double 11 " is this data
16 times, huge sales volume be behind logistics burden sharp increase.Compared with usual, double 11 while bring businessman's profit, quotient
Product glide therewith from the validity for being stored into dispatching.
Sales volume is substantially improved, while also proposing huge challenge to the Express firm of collaboration.If express delivery
Enterprise does not handle this problem well in time, and " cargo on the day of double 11 " will postpone to reach for a couple of days even more than ten days, finally
The decline of the said firm's customer satisfaction will be will cause, thus bring biggish loss simultaneously to electric business company and Express firm.This
Outside, there are the up to thousands of families of the electric business of blowout outbox demand, this phenomenon matches corresponding cooperation Express firm bring
Pressurization pressure is also unprecedented.How under limited resource effectively arrange " the dispatching task on the day of double 11 " is to numerous express deliveries
It is also no small problem for enterprise.For " demand of Express firm city distribution during the demands blowout such as double 11 ",
The urban inner region distribution mode traditional to Express firm optimizes, to enhance clothes of the Express firm during demand blowout
Business ability.
Summary of the invention
The present invention provides a kind of Express firm city distribution method under the blowout for demand to solve the above-mentioned problems.
For achieving the above object, technical solution of the present invention is as follows:
A kind of Express firm city distribution method under the blowout for demand, includes the following steps:
(1) related electric business is visited and investigated, the order volume under the blowout of electric business demand is acquired, is based on big data information, analyzes city
The characteristics of city's object dispenses under demand blowout situation with there are the problem of；
(2) using distribution time, distribution cost, dispatching three indexs of fairness as target, more mesh are constructed with mathematical modeling
Target path planning model, obtains optimal Distribution path；
(3) judgment matrix that 3 targets compare two-by-two is constructed with analytic hierarchy process (AHP), member is haggled over by judgment matrix calculating
The relative weighting of element, determines the weight of each optimization aim；
(4) its city distribution model is solved using multiple target heuritic approach, obtains optimal multiple target solution, i.e.,
Distribution path, distribution cost and distribution time three synthesis are optimal.
It is preferred that the step (1) specifically: analysis such as " 618 " " express delivery under double 11 " demand blowout situations
The changes in demand of enterprise's city distribution visits related electric business by inquiry, acquires the order volume under the blowout of electric business demand, obtains phase
The data of changes in demand, and the relative distance according to express company between the transshipment center and each district in object city are closed, and
In conjunction with the practical order demand amount in each district, basic data is obtained.
It is preferred that the step (2) specifically: use more useful loads for 1.6 tons van-type large-sized truck into
The mode of row multiloop dispatching, i.e., to the more reasonable distribution routes of freight wagon design, all cargos of disposable loading, from transhipment
Center is sailed out of, and successively goes to corresponding branch according to route, is eventually returned to the mode of transshipment center, then with distribution time, match
Sending cost, dispatching three indexs of fairness is target, realizes optimal path planning by building multiple target mathematical modeling.
It is preferred that the step (3) specifically: for the multi-objective optimization question, using the side of aggregate function
Method is handled, and the determination of weight is carried out using analytic hierarchy process (AHP), i.e., carries out the marking of different degree according to expertise, obtains this
The different degree comparator matrix of corresponding three targets of model, obtains corresponding weight vector.
It is preferred that the step (4) specifically: corresponding multiple target heuritic approach is designed, it is excellent to multiple target
Change model solution, and acquires Express firm in the transshipment center in object city and the geographical location of each branch and demand blowout situation
The dispatching demand data of lower each branch one day is emulated, the distribution project after being optimized, and optimizes front and back emulation
As a result comparison.
It is preferred that specifically being wrapped in the step (2) with the path planning model of mathematical modeling building multiple target
Include following steps:
Consider the Vehicle Routing Problems under general scenario first: one shares N number of dispatching demand point, and this area has and only one
A home-delivery center, and do following hypothesis:
(1) dispatching vehicle is unique, and dispatching at the uniform velocity drives on the way, and travel speed considers the laytime,
(2) all vehicles are eventually returned to home-delivery center from home-delivery center,
(3) limitation of the not stringent time window of the dispatching of each demand point,
(4) home-delivery center is only responsible for considering the problems of to dispense demand point,
(5) cargo is the packaging unit of unified specification,
Model variable is as follows:
K: the set of distribution vehicle；
K: the number in distribution vehicle collection K；
Qk: the dead weight of vehicle k；
N: the set of demand point is dispensed；
I, j, p: the number in demand point set N；
gi: the dispatching demand of demand point i；
dij: the distance between demand point i and demand point j；
xijk: 0 or 1；0 expression vehicle k does not pass through demand point i to demand point j；1 indicates vehicle k by demand point i to need
Seek point j；
Xipk: indicate that vehicle k passes through demand point i to demand point p；
xjpk: indicate that vehicle k passes through demand point j to demand point p；
yik: 0 or 1；0 expression vehicle k does not have requirements for access point i；1 expression vehicle k accessed demand point i；
ypkIndicate that vehicle k accessed demand point p；
c1: the distribution cost of unit distance；
c2: the dispatching fixed cost of unit vehicle, including labour cost, depreciation cost；
L: the farthest operating range of unit vehicle；
C1ij: the freight of i point to j point；
C1ji: the freight of j point to i point；
Fi (x) is the objective function of i target；
From the actual requirement that dispenses between the urban area that many aspects consider under demand blowout situation, consider distribution time,
With the path planning model of mathematical modeling building multiple target on the basis of distribution cost, dispatching fairness；
The total distance of entire delivery process is most short, i.e., total distribution time Z1It is most short；
The totle drilling cost Z of entire delivery process2Minimum, variable cost and fixed cost including dispatching；
Difference Z in distribution project between longest distribution route and shortest distribution route3Minimum, so that entire scheme
Time balance it is more preferable；
Constraint condition includes:
(2.1) each demand point has under conditions of meet demand amount requires and only 1 vehicle accesses；
(2.2) each distribution vehicle must will finally return to home-delivery center from home-delivery center, after demand point；
(2.3) useful load of each distribution vehicle is greater than the demand of its demand point accessed, i.e., overload condition does not occur
Occur；
(2.4) the sum of operating range of each distribution vehicle is no more than the farthest operating range in the regulation working time；
(2.5) freight of i point to j point is equal with the freight of j point to i point；
c1ij=c1ji (8)。
It is preferred that in the step (2), for the multi-objective optimization question, using aggregate function method into
Row processing, the essence of this method is specific way the problem of converting single object optimization for the problem of multiple-objection optimization
It is to confer to the certain weight coefficient of sub-goal, it, can be by this method by the optimization of N number of sub-goal if there is N number of sub-goal
Problem is converted to:
Wherein wiIt is the weight coefficient of i-th of objective function, w under usual situationiMeet following condition:
It is preferred that carrying out the determination of weight in step (3) with analytic hierarchy process (AHP), i.e., weight is carried out according to expertise
The marking to be spent obtains the corresponding distribution time Z of this model1, distribution cost Z2, dispatching fairness Z3The different degree of three targets
Comparator matrix, as shown in formula (11):
Therefore, corresponding weight vector is obtained are as follows:
W=[0.633 0.106 0.261] (12)
In view of the value range of different target, logarithm is taken to three sub-goals, is then weighted according to formula (12)
Summation, finally obtains simple target function are as follows:
fobj=0.633logz1+0.106logz2+0.261logz3。
It is preferred that multiple target heuritic approach includes genetic algorithm, particle swarm algorithm in step (4).
Beneficial effects of the present invention are as follows: transshipment center and each branch of the present invention by acquisition Express firm in city
The data such as the dispatching demand of geographical location and each branch demand blowout situation lower one day, are matched accordingly by mathematical model
Send scheme.Express firm can effectively improve its dispatching operational paradigm under demand blowout situation with its distribution project,
Distribution cost is reduced, front end distribution time is shortened, advantageous condition is created to dispense in time for end, ultimately helps to improve
Satisfaction of the client under demand blowout situation realizes win-win.Result of study shows to Express firm under demand blowout situation
Urban area between delivery operation provide strong decision support.
Detailed description of the invention
Fig. 1 is the multiloop dis-tribution model of allocator of the present invention.
Specific embodiment
Illustrate embodiments of the present invention below by way of specific specific example, those skilled in the art can be by this specification
Other advantages and efficacy of the present invention can be easily understood for disclosed content.The present invention can also pass through in addition different specific realities
The mode of applying is embodied or practiced, the various details in this specification can also based on different viewpoints and application, without departing from
Various modifications or alterations are carried out under spirit of the invention.
As shown in Figure 1, a kind of Express firm city distribution method under blowout for demand, i.e., close more freight wagon designs
The distribution route of reason, all cargos of disposable loading, is sailed out of from transshipment center, successively goes to corresponding branch according to route,
Be eventually returned to the mode of transshipment center, to improve dispatching efficiency of the Express firm under demand blowout situation, reduce dispatching at
This, mitigates the working pressure of transshipment center.
Allocator includes the following steps:
(1) related electric business (a certain shop of such as Taobao) is visited and investigated, analysis such as " 618 " is " under double 11 " demand blowout situations
The changes in demand of Express firm city distribution acquires the order volume under the blowout of electric business demand, big data information is based on, according to object
The characteristics of its practical dis-tribution model is analyzed in city, and analysis City Object dispense under demand blowout situation and there are the problem of；It is special
Point such as: electric business order volume is 6 times under normal condition, express delivery warehouse wharf explosion etc., there are the problem of for example: Express firm without and
When handle the timely dispatching problem of order well, the cargo in the case of demand blowout can postpone to reach for a couple of days even more than ten days, cause
Electric business and the customer satisfaction of the cooperation Express firm decline, and both sides bring biggish loss；According to express company in object
Relative distance between the transshipment center in city and each district, and the practical order demand amount in each district is combined, obtain basic number
According to；
(2) more useful loads are used to carry out the mode of multiloop dispatching for 1.6 tons of van-type large-sized truck, i.e., to more goods
Vehicle designs reasonable distribution route, and all cargos of disposable loading are sailed out of from transshipment center, successively gone to accordingly according to route
Branch, be eventually returned to the mode of transshipment center, then using distribution time, distribution cost, dispatching three indexs of fairness as mesh
Mark obtains optimal Distribution path with the path planning model of mathematical modeling building multiple target；
Specifically comprise the following steps: in the step (2) with the path planning model of mathematical modeling building multiple target
Consider the Vehicle Routing Problems under general scenario first: one shares N number of dispatching demand point, and this area has and only one
A home-delivery center, and do following hypothesis:
(2.1) dispatching vehicle is unique, and dispatching at the uniform velocity drives on the way, and travel speed considers the laytime,
(2.2) all vehicles are eventually returned to home-delivery center from home-delivery center,
(2.3) limitation of the not stringent time window of the dispatching of each demand point,
(2.4) home-delivery center is only responsible for considering the problems of to dispense demand point,
(2.5) cargo is the packaging unit of unified specification,
Model variable is as follows:
K: the set of distribution vehicle；
K: the number in distribution vehicle collection K；
Qk: the dead weight of vehicle k；
N: the set of demand point is dispensed；
I, j, p: the number in demand point set N；
gi: the dispatching demand of demand point i；
dij: the distance between demand point i and demand point j；
xijk: 0 or 1；0 expression vehicle k does not pass through demand point i to demand point j；1 indicates vehicle k by demand point i to need
Seek point j；
Xipk: indicate that vehicle k passes through demand point i to demand point p；
xjpk: indicate that vehicle k passes through demand point j to demand point p；
yik: 0 or 1；0 expression vehicle k does not have requirements for access point i；1 expression vehicle k accessed demand point i；
ypkIndicate that vehicle k accessed demand point p；
c1: the distribution cost of unit distance；
c2: the dispatching fixed cost of unit vehicle, including labour cost, depreciation cost；
L: the farthest operating range of unit vehicle；
C1ij: the freight of i point to j point；
C1ji: the freight of j point to i point；
Fi (x) is the objective function of i target；
From the actual requirement that dispenses between the urban area that many aspects consider under demand blowout situation, consider distribution time,
With the path planning model of mathematical modeling building multiple target on the basis of distribution cost, dispatching fairness；
The total distance of entire delivery process is most short, i.e., total distribution time Z1It is most short；
The totle drilling cost Z of entire delivery process2Minimum, variable cost and fixed cost including dispatching；
Difference Z in distribution project between longest distribution route and shortest distribution route3Minimum, so that entire scheme
Time balance it is more preferable；
Constraint condition includes:
(2.1) each demand point has under conditions of meet demand amount requires and only 1 vehicle accesses；
(2.2) each distribution vehicle must will finally return to home-delivery center from home-delivery center, after demand point；
(2.3) useful load of each distribution vehicle is greater than the demand of its demand point accessed, i.e., overload condition does not occur
Occur；
(2.4) the sum of operating range of each distribution vehicle is no more than the farthest operating range in the regulation working time；
(2.5) freight of i point to j point is equal with the freight of j point to i point；
c1ij=c1ji (8)。
In the step (2), for the multi-objective optimization question, handled using the method for aggregate function, this side
The essence of method is the problem of converting single object optimization for the problem of multiple-objection optimization, and specific way is to confer to sub-goal one
The optimization problem of N number of sub-goal can be converted to by fixed weight coefficient by this method if there is N number of sub-goal:
Wherein wiIt is the weight coefficient of i-th of objective function, w under usual situationiMeet following condition:
(3) it for the multi-objective optimization question, is handled using the method for aggregate function, is constructed using analytic hierarchy process (AHP)
The judgment matrix that 3 targets compare two-by-two carries out the determination of weight, i.e., carries out the marking of different degree according to expertise, obtain
The different degree comparator matrix of corresponding three targets of this model is calculated the relative weighting for being haggled over element by judgment matrix, is determined
The weight of each optimization aim；
Corresponding distribution time Z1, distribution cost Z2, dispatching fairness Z3The different degree comparator matrix of three targets, such as formula
(11) shown in:
Therefore, corresponding weight vector is obtained are as follows:
W=[0.633 0.106 0.261] (12)
In view of the value range of different target, logarithm is taken to three sub-goals, is then weighted according to formula (12)
Summation, finally obtains simple target function are as follows:
fobj=0.633logz1+0.106logz2+0.261logz3。
(4) corresponding multiple target heuritic approach (such as genetic algorithm, particle swarm algorithm etc.) is designed, to multiple-objection optimization mould
Type solve, and acquire Express firm object city transshipment center and each branch geographical location and demand blowout situation under certain
The dispatching demand data of Ge branch is emulated, the distribution project after being optimized, and optimizes front and back simulation result
Comparison.
Claims (9)
1. a kind of Express firm city distribution method under blowout for demand, it is characterised in that include the following steps:
(1) related electric business is visited and investigated, the order volume under the blowout of electric business demand is acquired, is based on big data information, analyzes city pair
As under demand blowout situation dispense the characteristics of and there are the problem of；
(2) using distribution time, distribution cost, dispatching three indexs of fairness as target, with mathematical modeling building multiple target
Path planning model obtains optimal Distribution path；
(3) judgment matrix that 3 targets compare two-by-two is constructed with analytic hierarchy process (AHP), element is haggled over by judgment matrix calculating
Relative weighting determines the weight of each optimization aim；
(4) its city distribution model is solved using multiple target heuritic approach, obtains optimal multiple target solution, that is, dispenses
Path, distribution cost and distribution time three synthesis are optimal.
2. utilizing the Express firm city distribution method of claim 1 being used under demand blowout, it is characterised in that:
The step (1) specifically: analysis such as " 618 " " demand of Express firm city distribution under double 11 " demand blowout situations
Related electric business is visited in variation by inquiry, acquires the order volume under the blowout of electric business demand, obtains the data of related needs variation,
And the relative distance according to express company between the transshipment center and each district in object city, and combine actually ordering for each district
Single demand amount, obtains basic data.
3. utilizing the Express firm city distribution method of claim 1 being used under demand blowout, it is characterised in that: the step
(2) specifically: use more useful loads to carry out the mode of multiloop dispatching for 1.6 tons of van-type large-sized truck, i.e., to more goods
Vehicle designs reasonable distribution route, and all cargos of disposable loading are sailed out of from transshipment center, successively gone to accordingly according to route
Branch, be eventually returned to the mode of transshipment center, then using distribution time, distribution cost, dispatching three indexs of fairness as mesh
Mark realizes optimal path planning by building multiple target mathematical modeling.
4. utilizing the Express firm city distribution method of claim 1 being used under demand blowout, it is characterised in that: the step
(3) specifically: for the multi-objective optimization question, handled using the method for aggregate function, carried out using analytic hierarchy process (AHP)
The determination of weight carries out the marking of different degree according to expertise, obtains the different degree ratio of corresponding three targets of this model
Compared with matrix, corresponding weight vector is obtained.
5. utilizing the Express firm city distribution method of claim 1 being used under demand blowout, it is characterised in that: the step
(4) specifically: design corresponding multiple target heuritic approach, Model for Multi-Objective Optimization is solved, and acquire Express firm right
As the transshipment center in city and the dispatching demand data in the geographical location of each branch and each branch demand blowout situation lower one day
It is emulated, the distribution project after being optimized, and optimizes the comparison of front and back simulation result.
6. utilizing the Express firm city distribution method of claim 1 being used under demand blowout, it is characterised in that: the step
(2) specifically comprise the following steps: in the path planning model of mathematical modeling building multiple target
Consider the Vehicle Routing Problems under general scenario first: one shares N number of dispatching demand point, this area one and only one match
Center is sent, and does following hypothesis:
(2.1) dispatching vehicle is unique, and dispatching at the uniform velocity drives on the way, and travel speed considers the laytime,
(2.2) all vehicles are eventually returned to home-delivery center from home-delivery center,
(2.3) limitation of the not stringent time window of the dispatching of each demand point,
(2.4) home-delivery center is only responsible for considering the problems of to dispense demand point,
(2.5) cargo is the packaging unit of unified specification,
Model variable is as follows:
K: the set of distribution vehicle；
K: the number in distribution vehicle collection K；
Qk: the dead weight of vehicle k；
N: the set of demand point is dispensed；
I, j, p: the number in demand point set N；
gi: the dispatching demand of demand point i；
dij: the distance between demand point i and demand point j；
xijk: 0 or 1；0 expression vehicle k does not pass through demand point i to demand point j；1 indicates vehicle k by demand point i to demand point
j；
Xipk: indicate that vehicle k passes through demand point i to demand point p；
xjpk: indicate that vehicle k passes through demand point j to demand point p；
yik: 0 or 1；0 expression vehicle k does not have requirements for access point i；1 expression vehicle k accessed demand point i；
ypkIndicate that vehicle k accessed demand point p；
c1: the distribution cost of unit distance；
c2: the dispatching fixed cost of unit vehicle, including labour cost, depreciation cost；
L: the farthest operating range of unit vehicle；
C1ij: the freight of i point to j point；
C1ji: the freight of j point to i point；
Fi (x) is the objective function of i target；
From the actual requirement dispensed between the urban area that many aspects consider under demand blowout situation, distribution time, dispatching are considered
With the path planning model of mathematical modeling building multiple target on the basis of cost, dispatching fairness；
The total distance of entire delivery process is most short, i.e., total distribution time Z1It is most short；
The totle drilling cost Z of entire delivery process2Minimum, variable cost and fixed cost including dispatching；
Difference Z in distribution project between longest distribution route and shortest distribution route3Minimum so that entire scheme when
Between balance it is more preferable；
Constraint condition includes:
(2.1) each demand point has under conditions of meet demand amount requires and only 1 vehicle accesses；
(2.2) each distribution vehicle must will finally return to home-delivery center from home-delivery center, after demand point；
(2.3) useful load of each distribution vehicle is greater than the demand of its demand point accessed, i.e., overload condition does not occur；
(2.4) the sum of operating range of each distribution vehicle is no more than the farthest operating range in the regulation working time；
(2.5) freight of i point to j point is equal with the freight of j point to i point；
c1ij=c1ji (8)。
7. utilizing the Express firm city distribution method of claim 1 being used under demand blowout, it is characterised in that: the step
(2) it in, for the multi-objective optimization question, is handled using the method for aggregate function, the essence of this method is by more mesh
The problem of the problem of mark optimization is converted into single object optimization, specific way is to confer to the certain weight coefficient of sub-goal, such as
Fruit has N number of sub-goal, can by this method be converted to the optimization problem of N number of sub-goal:
Wherein wiIt is the weight coefficient of i-th of objective function, w under usual situationiMeet following condition:
8. utilizing the Express firm city distribution method of claim 1 being used under demand blowout, it is characterised in that: step (3)
The middle determination that weight is carried out with analytic hierarchy process (AHP) carries out the marking of different degree according to expertise, it is corresponding to obtain this model
Distribution time Z1, distribution cost Z2, dispatching fairness Z3The different degree comparator matrix of three targets, as shown in formula (11):
Therefore, corresponding weight vector is obtained are as follows:
W=[0.633 0.106 0.261] (12)
In view of the value range of different target, logarithm is taken to three sub-goals, is then weighted summation according to formula (12),
Finally obtain simple target function are as follows:
fobj=0.633logz1+0.106logz2+0.261logz3。
9. utilizing the Express firm city distribution method of claim 1 being used under demand blowout, it is characterised in that: step (4)
Middle multiple target heuritic approach includes genetic algorithm, particle swarm algorithm.
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