CN109711596A - A kind of the Location Selection of Logistics Distribution Center optimization method and system of multi-target evolution - Google Patents
A kind of the Location Selection of Logistics Distribution Center optimization method and system of multi-target evolution Download PDFInfo
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Abstract
The present invention discloses the Location Selection of Logistics Distribution Center optimization method and system of a kind of multi-target evolution.On the basis of traditional single goal Logistics Distribution Center Location Model, home-delivery center is optimized to the dispatching expense of distribution point and home-delivery center's expenditure of construction as two targets, enables selected home-delivery center address farthest to reduce transportation charges and reduces construction cost.
Description
Technical field
The present invention relates to location of logistics center fields, select more particularly to a kind of logistics distribution center of multi-target evolution
Location optimization method and system.
Background technique
Logistics distribution center is to be engaged in cargo outfit and the Modern circulation equipment to distribution point delivery operation, is logistics system
The central hub of system.In Logistics network design and design, Location Selection of Logistics Distribution Center needs modelling, quantification, reasonably
Selection home-delivery center place can reduce transportation charges, cut operating costs, can also eliminate different cities or same city
Different location land price difference bring negative effect, reduce construction cost, promote two kinds of flows of production and consumption coordination
With cooperation, guarantee the balanced growth of logistics system.
Traditional Location Selection of Logistics Distribution Center problem can be one with abstract in certain constraint condition and objective function
Under mathematical programming problem, usually most with the sum of construction cost of the transportation cost of home-delivery center to distribution point and home-delivery center
Low or other requirements are target to solve the problems, such as.However, due to may relate to conflicting target, during addressing
Make multiple partial objectives for while being optimal often highly difficult.
Summary of the invention
The object of the present invention is to provide the Location Selection of Logistics Distribution Center optimization method and system of a kind of multi-target evolution, energy
It is enough rationally and effectively to select home-delivery center place, farthest improve the operational paradigm and save the cost of logistics system.
To achieve the above object, the present invention provides following schemes:
A kind of Location Selection of Logistics Distribution Center optimization method of multi-target evolution, which comprises
All logistics distribution centers to be selected are obtained to match to the dispatching expense of each distribution point and all logistics to be selected
Send the expenditure of construction at center；
According to the dispatching expense and the expenditure of construction, initial population is generated at random, includes N in the initial population
Individual；
According to the dispatching expense, function is utilizedDetermine the first object of k-th of individual
Value, wherein S indicates that the element number of the set of distribution point, C indicate the element number of the set of home-delivery center, dijIt indicates from matching
Send point i to the distance of home-delivery center j, ZijIndicate whether distribution point i is serviced by home-delivery center j；
According to the expenditure of construction, function is utilizedDetermine the second target value of k-th of individual,
In, C indicates the element number of the set of home-delivery center, VjIndicate the construction cost of j-th of home-delivery center, hjIt indicates to match for j-th
Send whether center builds；
According to the logistics distribution center to be selected and all distribution points to be selected, function is utilizedDetermine the third target value of k-th of individual, wherein S indicates the element of the set of distribution point
Number, C indicate the element number of the set of home-delivery center, ZijIndicate whether distribution point i is serviced by home-delivery center j；
According to the first object value, second target value and the third target value to the individual of initial population
It is layered, each layer includes multiple individuals, and the low individual of level dominates the high individual of level；
Calculate the crowding distance of the individual；
According to the crowding distance and the level of the individual, M individual of initial population is filtered out；
The M individual filtered out is intersected, is made a variation, population of new generation is generated, includes M in a new generation population
Individual after a intersection, variation；
Initial population and population of new generation are merged, generates and merges population；
All individuals in the merging population are layered；
According to the layering for merging population as a result, filtering out preferable individual；
By the individual screened as Selection of Logistic Distribution Center to be selected.
Optionally, it is described according to the first object value, second target value and the third target value to initial kind
The individual of group is layered, and each layer includes multiple individuals, and the low individual of level dominates the high individual of level, specifically includes:
According to the first object value, second target value and the third target value of each individual, determine each
The corresponding variable of individual and set, the variable are number of individuals better than current individual in population, and the collection is combined into current individual
The set of good individual serial number than in population；
It is layered according to the variable of each individual and the set.
Optionally, described to be layered according to the variable and the set of each individual, it specifically includes:
For i-th of individual, judge whether the variable k of i-th of individual is equal to 0, obtains the first judging result；
When first judging result indicates the variable of i-th of individual equal to 0, i-th of individual is determined
For m layers of individual, m >=1；
When first judging result indicates the variable of i-th of individual not equal to 0, judge whether m-1 layers deposited
It is preferably individual in than i-th individual, obtain the second judging result；
When second judging result indicates to have than i-th individual preferably individual in described m-1 layers, by institute
The variable update for stating i-th of individual is k-1, judges whether the updated variable of i-th of individual is equal to 0, obtains third and sentences
Disconnected result；
When the third judging result indicates that the updated variable of i-th of individual is equal to 0, by described i-th
Body is determined as m+1 layers of individual；
When the third judging result indicates that described i-th individual updated variable not equal to 0, judges the m
Layer is preferably individual with the presence or absence of than i-th individual；
Successively all individuals are layered.
Optionally, the crowding distance and the level according to the individual filters out M individual of initial population,
It specifically includes:
N individual is randomly selected from initial population,；
Obtain the described n minimum individual of individual middle layer number；
Judge to obtain the 4th judging result whether comprising multiple individuals in the minimum individual of the number of plies；
When the 4th judging result indicates in the minimum individual of the number of plies comprising multiple individuals, described in determination
The maximum individual of crowding distance is determined as one in M filtered out individual by the maximum individual of crowding distance in multiple individuals
Individual；
When the 4th judging result indicates in the minimum individual of the number of plies only to include an individual, most by the number of plies
Low individual is determined as the individual in M filtered out individual；
Successively determine the M individual filtered out.
Optionally, the M individual that will be filtered out is intersected, is made a variation, and is generated population of new generation, is specifically included:
By the way of single point crossing, randomly chooses i-th of individual and j-th of individual is intersected, after being intersected
Two individuals, 1≤i≤n, 1≤j≤n；
To each of population individual, Mutation, the individual after being made a variation are carried out；
Individual after successively obtaining all variations.
Optionally, it is described according to the layering for merging population as a result, filter out preferable individual, also want later
It carries out:
Obtain current iteration number；
Judge whether the current iteration number reaches maximum number of iterations, obtains the 5th judging result；
When the 5th judging result indicates that current iteration number reaches maximum number of iterations, by the best N of screening
Individual is determined as the individual of final output；
When the 5th judging result indicates that current iteration number is not up to maximum number of iterations, by the best of screening
Individual be updated to initial population.
To achieve the above object, the present invention provides following schemes:
A kind of Location Selection of Logistics Distribution Center optimization system of multi-target evolution, the system comprises:
Module is obtained, for obtaining dispatching expense and institute of all logistics distribution centers to be selected to each distribution point
There is the expenditure of construction of logistics distribution center to be selected；
Initial population generation module, for generating initial kind at random according to the dispatching expense and the expenditure of construction
Group, it include individual in the initial population；
First object value determining module, for utilizing function according to the dispatching expenseDetermine
The first object value of k individual, wherein S indicates that the element number of the set of distribution point, C indicate the set of home-delivery center
Element number, dijIt indicates from distribution point i to the distance of home-delivery center j, ZijIndicate whether distribution point i is serviced by home-delivery center j；
Second target value determining module, for utilizing function according to the expenditure of constructionDetermine kth
Second target value of individual, wherein C indicates the element number of the set of home-delivery center, VjIndicate building for j-th of home-delivery center
This is caused, hjIndicate whether j-th of home-delivery center builds；
Third target value determining module, for according to the logistics distribution center to be selected and all described wait match
It send a little, utilizes functionDetermine the third target value of k-th of individual, wherein S indicates distribution point
The element number of set, C indicate the element number of the set of home-delivery center, ZijIndicate whether distribution point i is taken by home-delivery center j
Business；
First layer module, for according to the first object value, second target value and the third target value pair
The individual of initial population is layered, and each layer includes multiple individuals, and the low individual of level dominates the high individual of level；
Crowding distance computing module, for calculating the crowding distance of the individual；
First screening module filters out the M of initial population for the crowding distance and the level according to the individual
Individual；
Population generation module of new generation, the M individual for will filter out are intersected, are made a variation, and a new generation kind is generated
Group, intersect in a new generation population comprising M, the individual after variation；
Merge population generation module, for merging initial population and population of new generation, generates and merge population；
Second hierarchical block, for being layered to all individuals in the merging population；
Second screening module, for the layering according to the merging population as a result, filtering out preferable individual；
Determining module, for individual as Selection of Logistic Distribution Center to be selected by what is screened.
Optionally, the first layer module, specifically includes:
Variable, set determination unit, for according to the first object value of each individual, second target value and
The third target value, determines the corresponding variable of each individual and set, and the variable is better than current individual in population
Body number, it is described to collect the set for being combined into the current individual individual serial number better than in population；
Delaminating units, for being layered according to the variable and the set of each individual.
Optionally, the delaminating units, specifically include:
First judging unit is obtained for judging whether the variable k of i-th of individual is equal to 0 for i-th of individual
To the first judging result；
Individual determination unit will when for indicating that the variable of i-th of individual is equal to 0 when first judging result
I-th of individual is determined as m layers of individual, m >=1；
Second judgment unit, when for indicating the variable of i-th of individual when first judging result not equal to 0,
M-1 layers are judged with the presence or absence of than the i-th better individual of individual, obtain the second judging result；
Variable update unit, for indicating there is than i-th individual in described m-1 layers when second judging result
Preferably when individual, the variable update by i-th of individual is k-1；
Third judging unit obtains third judgement for judging whether the updated variable of i-th of individual is equal to 0
As a result；
Individual determination unit, for indicating the updated variable etc. of i-th of individual when the third judging result
In 0, i-th of individual is determined as to m+1 layers of individual；
When the third judging result indicates that described i-th individual updated variable not equal to 0, judges the m
Layer is preferably individual with the presence or absence of than i-th individual；
Successively all individuals are layered.
Optionally, first screening module, specifically includes:
Individual selection unit, for randomly selecting n individual from initial population,；
Number of plies acquiring unit, for obtaining the described n minimum individual of individual middle layer number；
Whether 4th judging unit obtains fourth judgement knot comprising multiple individuals in the minimum individual of the number of plies for judging
Fruit；
Crowding distance determination unit, for when the 4th judging result indicate include in the minimum individual of the number of plies
When multiple individuals, determines the maximum individual of crowding distance in multiple individuals, the maximum individual of crowding distance is determined as
The individual in M individual filtered out；
Individual determination unit, for indicating in the minimum individual of the number of plies when the 4th judging result only comprising one
When individual, the minimum individual of the number of plies is determined as the individual in M filtered out individual；
Successively determine the M individual filtered out.
The specific embodiment provided according to the present invention, the invention discloses following technical effects: it is more that the present invention provides one kind
The Location Selection of Logistics Distribution Center optimization method that target is evolved, on the basis of traditional single goal Logistics Distribution Center Location Model
On, home-delivery center is optimized to the dispatching expense of distribution point and home-delivery center's expenditure of construction as two targets, is made
Transportation charges can farthest be reduced and reduce construction cost by obtaining selected home-delivery center address.
Detailed description of the invention
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be in embodiment
Required attached drawing is briefly described, it should be apparent that, the accompanying drawings in the following description is only some realities of the invention
Example is applied, it for those of ordinary skill in the art, without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is the Location Selection of Logistics Distribution Center optimization method flow chart of multi-target evolution；
Fig. 2 is 1 bivariate table figure of the embodiment of the present invention；
Fig. 3 is the service scenario figure of 1 distribution point of the embodiment of the present invention；
Fig. 4 is that cross and variation procedure chart occurs for 1 individual A and B of the embodiment of the present invention；
Fig. 5 is that the embodiment of the present invention 1 generates individual C and D procedure chart；
Fig. 6 is that 1 individual E of the embodiment of the present invention generates variation figure；
Fig. 7 is that 1 individual F of the embodiment of the present invention generates figure；
Fig. 8 is the Location Selection of Logistics Distribution Center optimization system structure chart of multi-target evolution；
Fig. 9 is the individual exemplary diagram of the specific embodiment of the invention 2；
Figure 10 is that the specific embodiment of the invention 2 solves data；
Figure 11 is that the Location Selection of Logistics Distribution Center problem that the specific embodiment of the invention is obtained using multi-objective Evolutionary Algorithm is excellent
The effect diagram of change.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts it is all its
His embodiment, shall fall within the protection scope of the present invention.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention is described in further detail.
Fig. 1 is the Location Selection of Logistics Distribution Center optimization method flow chart of multi-target evolution.As shown in Figure 1, a kind of multiple target
The Location Selection of Logistics Distribution Center optimization method of evolution includes:
Step 101: obtaining all logistics distribution centers to be selected to the dispatching expense of each distribution point and all to be selected
Logistics distribution center expenditure of construction；
Step 102: according to the dispatching expense and the expenditure of construction, generating initial population, the initial population at random
In include individual；
Step 103: according to the dispatching expense, the first object value of k-th of individual, institute are determined using first function
Stating first function isWherein, S indicates that the element number of the set of distribution point, C indicate home-delivery center
The element number of set, dijIt indicates from distribution point i to the distance of home-delivery center j, ZijIndicate distribution point i whether by home-delivery center j
Service；
Step 104: according to the expenditure of construction, the second target value of k-th of individual is determined using second function, it is described
Second function isWherein, C indicates the element number of the set of home-delivery center, VjIt indicates in j-th of dispatching
The construction cost of the heart, hjIndicate whether j-th of home-delivery center builds；
Step 105: according to the logistics distribution center to be selected and all distribution points to be selected, utilizing third letter
Number determines the third target value of k-th of individual, and the third function isWherein, S indicates distribution point
Set element number, C indicate home-delivery center set element number, ZijIndicate distribution point i whether by home-delivery center j
Service；
Step 106: according to the first object value, second target value and the third target value to initial population
Individual be layered, each layer includes multiple individuals, and the low individual of level dominates the high individual of level；
Step 107: calculating the crowding distance of the individual；
Step 108: according to the crowding distance and the level of the individual, filtering out M individual of initial population；
Step 109: the M individual filtered out being intersected, is made a variation, population of new generation, a new generation population are generated
In comprising M intersect, make a variation after individual；
Step 110: initial population and population of new generation being merged, generates and merges population；
Step 111: all individuals in the merging population are layered；
Step 112: being successively from minimum according to the layering for merging population as a result, filtering out preferable individual
Layer is to top, if level is identical, selective aggregation is apart from biggish, until reaching population scale；
Step 113: by the individual screened as Selection of Logistic Distribution Center to be selected.
The present invention provides a kind of Location Selection of Logistics Distribution Center optimization method of multi-target evolution, in traditional single goal object
On the basis of flowing distribution center location model, by the dispatching expense of home-delivery center to distribution point and home-delivery center's expenditure of construction point
Not Zuo Wei two targets optimize, enable selected home-delivery center address farthest to reduce transportation charges
With reduction construction cost.
Specific embodiment 1:
Step 101: obtaining the address of all logistics centers to be selected and the address of construction cost and distribution point.Object to be selected
Stream home-delivery center refers to that, in the logistics distribution center not yet built undetermined, construction cost refers in logistics distribution yet to be built
The heart estimates cost, and distribution point refers to the place that logistics distribution center needs for article to be sent to.
Step 102: according to all logistics distribution centers and distribution point to be selected, generating initial population at random.Initial population
P includes individual, should generally choose greater than 100 individuals, N > 100 under foundation actual conditions.Each individual indicates each
Which logistics distribution center is distribution point should choose, and the logistics center being selected is equivalent to and has been selected, final to indicate
At the On The Choice of logistics distribution center.
Wherein the following example of individual UVR exposure mode (assuming that there is No. I, No. II, No. III home-delivery center to be selected has No. 1, No. 2,3
Number, No. 4 distribution points):
Individual UVR exposure mode:
Fig. 2 is bivariate table of embodiment of the present invention figure, and a kind of Location Selection of Logistics Distribution Center side is indicated using above-mentioned bivariate table
Case, each scheme represent an individual.Whether the value that the i-th row j is arranged in table represents distribution point i by home-delivery center j service (1
Indicate dispatching, 0 indicates not dispense).Such as the 3rd row the 1st arrange 1, indicate that No. 3 distribution points are serviced by No. I home-delivery center, the 2nd row
The 0 of 3rd column indicates that No. 2 distribution points are not serviced by No. III home-delivery center.
Since the coding of each individual is a bivariate table, every a line of bivariate table only one 1, indicate that each is matched
It send and is a little merely able to be serviced by a home-delivery center.
According to above-mentioned coding, No. 1 distribution point is serviced by III home-delivery center, and No. 2 distribution points are serviced by II home-delivery center, and 3
Number distribution point is serviced by I home-delivery center, and No. 4 distribution points are serviced by II home-delivery center, the service scenario of distribution point such as following figure institute
Show:
Step 103: according to the construction cost of all logistics distribution centers to be selected and dispatching dot address and logistics center to be selected
And transportation cost and average degree, all individuals in initial population are layered.Each layer includes multiple individuals, the number of plies
The fitness of low individual is higher than the fitness of the high individual of the number of plies.
Stratification step is specific as follows:
(1) according to the address of all logistics distribution centers to be selected and distribution point, each individual is determined using formula (1)
First object value, the total distance of expression home-delivery center to distribution point.
The wherein meaning that each variable represents:
N: the element number of the set of all distribution points
C: the element number of the set of logistics distribution center to be selected
I: i-th distribution point；
J: j-th home-delivery center；
dij: distance of the distribution point i to home-delivery center j；
Zij: whether distribution point i is serviced by home-delivery center j, if Zij=1, then whether distribution point i is serviced by home-delivery center j.
Obvious transportation cost is lower, and target value is smaller, meets actual demand.
(2) construction cost for the logistics distribution center scheme and logistics distribution center chosen according to each individual, utilizes public affairs
Formula (2) determines the second target value of each individual, indicates total capital cost.
The wherein meaning that each variable represents:
Vj: the construction cost of j-th of logistics distribution center；
hj: whether j-th of home-delivery center is built, if hj=1, then j-th of home-delivery center is to be built；
Each individual because having had chosen which logistics distribution center to be selected as actual logistics distribution center,
So using only needing to add up the construction cost of the logistics distribution center of selection, so that it may know its construction of each individual
Cost.Obviously, construction cost is lower, and target value is smaller, corresponds to actual needs.
(3) the logistics distribution center Choice according to represented by each individual, determines each individual using formula (3)
Third target value, indicate distribution point distribute to logistics distribution center average degree.
Wherein, the addressing scheme of each individual will lead to the dispatching of each selected logistics distribution center undertaken
Point number is different, and leading to some distribution points, over-burden.Therefore, it is possible to use variance indicates its average degree, it is clear that average
Degree is lower, and target value is lower.Meet actual demand.
(4) n and s of each individual are calculated；N indicates that the number of individuals that current individual is dominated in population, s indicate current
The set for the individual serial number that individual dominates；
Judge the dominance relation of current individual and other individuals, if dominating other individuals, other individuals are added to currently
In the s set of individual, if being dominated by other individuals, the n of current individual records the number dominated by other individuals；Such as have
Individual A and individual B, fitness is its corresponding (F respectively1,F2,F3)A(F1,F2,F3)B.It is now assumed that there are two targets by A
Value, for (2,5)A, there are two target value (3,6) for B individualB.It is now assumed that target value is smaller more excellent, it can be seen that the target of A individual
Value is superior to B individual, so A dominates B, i.e. B is dominated by A, and B is added into the s set of current individual A.Assuming that have (2,
6)A(3,4)B, it can be observed that the first aim value of A is better than B, but second target value B is better than A, so A is not propped up
A is not also dominated with B, B.
Judge whether the n of each individual in population is equal to 0, if so, being m layers of non-dominant individual；M > 0；If being not equal to
0, then enter next layer, and the n of the individual subtracts 1, and restarts to judge whether the n of the individual is 0, if it is, being m+
1 layer of non-dominant individual.Current operation is repeated, until all individual layerings terminate；
Finally, each individual exists in the level corresponding to oneself, and the obvious lower individual of level, more outstanding.
Step 104: obtaining the crowding distance of each individual in each layer.The crowding distance of each individual, represents individual
With the distance of individual (in same layer) distance around.Crowding distance is bigger, and individual is remoter with surrounding individual distance.Aggregation away from
From smaller, individual is closer with surrounding individual distance.It is desirable that the crowding distance between the individual of same layer is the smaller the better, because
Such angle distribution is more uniform, is more conducive to reducing leading to the problem of locality.Specific formula is as follows:
In formula, P [i]distanceFor the crowding distance of individual i, P [i].M indicates function of the individual i on objective function m
Value；The number of r expression objective function.When calculating the crowding distance of each individual, need to group by each specific item scalar functions
Value carries out descending arrangement.
Step 105: according to the crowding distance of individual each in initial population and the locating number of plies, initial population out at random
In M individual.1 < M < N.Initial population selection course uses polynary algorithm of tournament selection.Detailed process is as follows:
N individual is randomly choosed from initial population.It finds out in n individual, classic individual (level where i.e.
The smallest individual looks for the maximum individual of crowding distance if having multiple individuals in same layer) enter match-pool, repeat current behaviour
Make, until match-pool is full.Such generation process, the probability that the super more outstanding direction of initial population can be made to develop is more
Greatly.
Step 106: the population Q by M individual intersection, variation, after generating variation.Include in population Q after the variation
Individual after M intersection, variation.Using the method for single point crossing, the 2q-1 individual and the 2q individual are intersected,
Two individuals after being intersected；Two individuals after the intersection are swapped into variation, are made a variation
Two individuals afterwards；Individual after successively obtaining all variations.Fig. 4 is that cross and variation occurs for individual of embodiment of the present invention A and B
Procedure chart；Cross and variation occurs for following two individual A and B.
Fig. 5 is that the embodiment of the present invention generates individual C and D procedure chart.If choosing third is classified as crosspoint, then A and B it
Between three or four rows exchange, generate new individual C and D.
Such as individual E generates variation, Fig. 6 is that individual of embodiment of the present invention E generates variation figure, and variant sites occur the
Two rows
After variation, become individual F, Fig. 7 is that individual of embodiment of the present invention F generates figure, and meaning is second distribution point
The logistics distribution center of selection is transformed into first logistics distribution center by second to dispense.
It, then can be according to upper because the individual amount of variation and intersection front and back is constant if there is 100 individuals in match-pool
Mode is stated, 100 new individuals is generated, is put into Q population, as sub- population.
Step 107: initial population being merged with the population after variation, generates population R.
Step 108: the individual in population R is layered.It is layered according to the layered mode of step 104.
Step 109: according to the layering of population R as a result, the selection highest individual of fitness.N is the initial scale of population.
According to above-mentioned example, R population is one and possesses 200 individual populations, according to the method being layered inside step 104, each
Individual can be all assigned in corresponding level.The lower individual more fitness of level is higher.It is successively that level is lower every
Layer individual is added in new population, until meet initial population scale, if number individual in new population has been more than 100,
The big individual of crowding distance in this layer is added in new population P, so that the number of total individual is just 100 in new population
It is a.
Step 1010: if reaching the number of iterations, the highest individual of the fitness of selection being determined as final defeated
Individual out；If not reaching the number of iterations, continue for the highest individual of the fitness of selection to be updated to initially
Population, return step 103 continue iteration.
Step 1011: individual is determined as to the scheme of Location Selection of Logistics Distribution Center to be selected.
Initial population has been executed a NSGA- using II algorithm of NSGA- inside multi-objective Evolutionary Algorithm by the present invention
The process of II algorithm is that population iteration is primary, when population iterates to specified number (such as being appointed as 300 generations), terminates journey
Sequence, the individual that output population meets the requirements in the middle.
Fig. 8 is the Location Selection of Logistics Distribution Center optimization system structure chart of multi-target evolution of the embodiment of the present invention.Such as Fig. 8 institute
Show, a kind of Location Selection of Logistics Distribution Center optimization system of multi-target evolution, the system comprises:
Obtain module 201, for obtain all logistics distribution centers to be selected to the dispatching expense of each distribution point and
The expenditure of construction of all logistics distribution centers to be selected；
Initial population generation module 202, for according to the dispatching expense and the expenditure of construction, random generation to be initial
Population includes individual in the initial population；
First object value determining module 203, for utilizing function according to the dispatching expense
Determine the first object value of k-th of individual, wherein S indicates that the element number of the set of distribution point, C indicate home-delivery center
The element number of set, dijIt indicates from distribution point i to the distance of home-delivery center j, ZijIndicate distribution point i whether by home-delivery center
J service；
Second target value determining module 204, for utilizing function according to the expenditure of constructionIt determines
Second target value of k-th of individual, wherein C indicates the element number of the set of home-delivery center, VjIndicate j-th of home-delivery center
Construction cost, hjIndicate whether j-th of home-delivery center builds；
Third target value determining module 205, for according to the logistics distribution center to be selected and all described to be selected
Distribution point utilizes functionDetermine the third target value of k-th of individual, wherein S indicates distribution point
Set element number, C indicate home-delivery center set element number, ZijIndicate distribution point i whether by home-delivery center j
Service；
First layer module 206, for according to the first object value, second target value and the third target
Value is layered the individual of initial population, and each layer includes multiple individuals, and the low individual of level dominates high of level
Body；
Crowding distance computing module 207, for calculating the crowding distance of the individual；
First screening module 208 filters out initial population for the crowding distance and the level according to the individual
M individual；
Population generation module 209 of new generation, the M individual for will filter out are intersected, are made a variation, and a new generation is generated
Population, it is described a new generation population in comprising M intersect, make a variation after individual；
Merge population generation module 210, for merging initial population and population of new generation, generates and merge population；
Second 211 pieces of mould of layering, for being layered to all individuals in the merging population；
Second screening module 212, for according to the layering for merging population as a result, filter out preferable N it is individual,
It is successively from lowermost layer to top, if level is identical, selective aggregation is apart from biggish, until reaching population scale；
Determining module 213, for individual as Selection of Logistic Distribution Center to be selected by what is screened.
The first layer module 206, specifically includes:
Variable, set determination unit, for according to the first object value of each individual, second target value and
The third target value, determines the corresponding variable of each individual and set, and the variable is better than current individual in population
Body number, it is described to collect the set for being combined into the current individual individual serial number better than in population；
Delaminating units, for being layered according to the variable and the set of each individual.
The delaminating units, specifically include:
First judging unit is obtained for judging whether the variable k of i-th of individual is equal to 0 for i-th of individual
To the first judging result；
Individual determination unit will when for indicating that the variable of i-th of individual is equal to 0 when first judging result
I-th of individual is determined as m layers of individual, m >=1；
Second judgment unit, when for indicating the variable of i-th of individual when first judging result not equal to 0,
M-1 layers are judged with the presence or absence of than the i-th better individual of individual, obtain the second judging result；
Variable update unit, for indicating there is than i-th individual in described m-1 layers when second judging result
Preferably when individual, the variable update by i-th of individual is k-1；
Third judging unit obtains third judgement for judging whether the updated variable of i-th of individual is equal to 0
As a result；
Individual determination unit, for indicating the updated variable etc. of i-th of individual when the third judging result
In 0, i-th of individual is determined as to m+1 layers of individual；
When the third judging result indicates that described i-th individual updated variable not equal to 0, judges the m
Layer is preferably individual with the presence or absence of than i-th individual；
Successively all individuals are layered.
First screening module 208, specifically includes:
Individual selection unit, for randomly selecting n individual from initial population,；
Number of plies acquiring unit, for obtaining the described n minimum individual of individual middle layer number；
Whether 4th judging unit obtains fourth judgement knot comprising multiple individuals in the minimum individual of the number of plies for judging
Fruit；
Crowding distance determination unit, for when the 4th judging result indicate include in the minimum individual of the number of plies
When multiple individuals, determines the maximum individual of crowding distance in multiple individuals, the maximum individual of crowding distance is determined as
The individual in M individual filtered out；
Individual determination unit, for indicating in the minimum individual of the number of plies when the 4th judging result only comprising one
When individual, the minimum individual of the number of plies is determined as the individual in M filtered out individual；
Successively determine the M individual filtered out.
Specific embodiment 2:
Step 1: first counting the construction cost of all logistics distribution centers and the coordinate of logistics distribution center, dispense
The coordinate of point.
1 logistics distribution center coordinate of table
| Logistics distribution center title | X/ meters | Y/ meters |
| Logistics distribution center 1 | 205.6 | 315.4 |
| Logistics distribution center 2 | -104.0 | 26.5 |
| Logistics distribution center 3 | -79.3 | -82.5 |
| Logistics distribution center 4 | 193.2 | 258.8 |
| Logistics distribution center 5 | 590.1 | -200.6 |
2 distribution point coordinate of table
| Distribution point title | X/ meters | Y/ meters |
| Distribution point 1 | 314.6 | 587.7 |
| Distribution point 2 | 298.4 | 25.3 |
| Distribution point 3 | -272.4 | 10.8 |
| Distribution point 4 | 4.6 | 374.7 |
| Distribution point 5 | 131.6 | -256.5 |
3 logistics distribution center construction cost of table
Step 2: random generate contains 300 individual initial populations, individual example such as Fig. 9 of generation.Fig. 9 is this hair
The individual exemplary diagram of bright specific embodiment 2.
Step 3: calculating the first object value of each individual in current population, the second target value and third target value；
Step 4: obtaining the non-dominant individual collection of first layer according to three target values of each of current population individual
It closes；
Step 5: calculating the crowding distance of each individual；
Step 6: randomly choosing n individual from current population.It finds out in n individual, the smallest individual of level, if
There is n individual, finds out the maximum individual of crowding distance and enter match-pool, current operation is repeated, until match-pool is full；
Step 7: the individual in match-pool is intersected, variation, generates population Q of new generation；
Step 8: P population and Q population are merged into R population；
Step 9: individual each in R population is layered；R population is divided according to the layered approach of step 104
Layer；
Step 10:, according to current solution space, selecting suitable solution after successive ignition, saving data.Figure 10 is this
Invention specific embodiment 2 solves data.
Indicate the results are shown in Figure 10, guarantee dispense the lesser situation of total distance under so that construction cost it is smaller with
And distribution point distribution is more uniform.Suitable logistics distribution center is built by selection, reaches and reduces cost and raising dispatching
The purpose of efficiency.This has practical application value to the dispatching of delivery industry " last one kilometer " very much.
Figure 11 is that the Location Selection of Logistics Distribution Center problem that the specific embodiment of the invention is obtained using multi-objective Evolutionary Algorithm is excellent
The effect diagram of change.
For solving the problems, such as Location Selection of Logistics Distribution Center with genetic algorithm, traditional algorithm is with home-delivery center to dispatching
The minimum target of the sum of the construction cost of point and home-delivery center, but building for logistics distribution center often can not be considered simultaneously
If expense and logistics distribution center are conflicting between the two objective functions to the expense between distribution point.The present invention
Innovation be, using multi-objective Evolutionary Algorithm, establish three objective functions, both considered building for logistics distribution center
This is caused, it is contemplated that the distribution point of each home-delivery center distribution is impartial as far as possible, prevents the load of some logistics distribution center
It is excessive, the address of logistics distribution center can be effectively selected in this way, improves the efficiency of logistics system, saved construction logistics and matched
Send the cost of centring system.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with its
The difference of his embodiment, the same or similar parts in each embodiment may refer to each other.For being disclosed in embodiment
For system, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is referring to method portion
It defends oneself bright.
Used herein a specific example illustrates the principle and implementation of the invention, above embodiments
Illustrate to be merely used to help understand method and its core concept of the invention；At the same time, for those skilled in the art,
According to the thought of the present invention, there will be changes in the specific implementation manner and application range.In conclusion this specification
Content should not be construed as limiting the invention.
Claims (10)
1. a kind of Location Selection of Logistics Distribution Center optimization method of multi-target evolution, which is characterized in that the described method includes:
All logistics distribution centers to be selected are obtained into the dispatching expense and all logistics distributions to be selected of each distribution point
The expenditure of construction of the heart；
According to the dispatching expense and the expenditure of construction, initial population is generated at random, includes N number of in the initial population
Body；
According to the dispatching expense, function is utilizedDetermine the first object value of k-th of individual, wherein
S indicates that the element number of the set of distribution point, C indicate the element number of the set of home-delivery center, dijIt indicates from distribution point i to matching
Send the distance of center j, ZijIndicate whether distribution point i is serviced by home-delivery center j；
According to the expenditure of construction, function is utilizedDetermine the second target value of k-th of individual, wherein C table
Show the element number of the set of home-delivery center, VjIndicate the construction cost of j-th of home-delivery center, hjIndicating j-th of home-delivery center is
No construction；
According to the logistics distribution center to be selected and all distribution points to be selected, function is utilizedDetermining the third target value of k-th of individual, wherein S indicates the element number of the set of distribution point,
C indicates the element number of the set of home-delivery center, ZijIndicate whether distribution point i is serviced by home-delivery center j；
The individual of initial population is divided according to the first object value, second target value and the third target value
Layer, each layer include multiple individuals, and the low individual of level dominates the high individual of level；
Calculate the crowding distance of the individual；
According to the crowding distance and the level of the individual, M individual of initial population is filtered out；
The M individual filtered out is intersected, is made a variation, population of new generation is generated, includes M friendship in a new generation population
Individual after fork, variation；
Initial population and population of new generation are merged, generates and merges population；
All individuals in the merging population are layered；
According to the layering for merging population as a result, filtering out preferable individual；
By the individual screened as Selection of Logistic Distribution Center to be selected.
2. the Location Selection of Logistics Distribution Center optimization method of multi-target evolution according to claim 1, which is characterized in that described
The individual of initial population is layered according to the first object value, second target value and the third target value,
Each layer includes multiple individuals, and the low individual of level dominates the high individual of level, specifically includes:
According to the first object value, second target value and the third target value of each individual, each individual is determined
Corresponding variable and set, the variable are number of individuals better than current individual in population, and the collection is combined into current individual than kind
The set of good individual serial number in group；
It is layered according to the variable of each individual and the set.
3. the Location Selection of Logistics Distribution Center optimization method of multi-target evolution according to claim 1, which is characterized in that described
It is layered, is specifically included according to the variable of each individual and the set:
For i-th of individual, judge whether the variable k of i-th of individual is equal to 0, obtains the first judging result；
When first judging result indicates the variable of i-th of individual equal to 0, i-th of individual is determined as m
The individual of layer, m >=1；
When first judging result indicates the variable of i-th of individual not equal to 0, judge m-1 layers whether there is than
I-th of individual is preferably individual, obtains the second judging result；
When second judging result indicates to have than i-th individual preferably individual in described m-1 layers, by described i-th
The variable update of individual is k-1, judges whether the updated variable of i-th of individual is equal to 0, obtains third judgement knot
Fruit；
When the third judging result indicates that the updated variable of i-th of individual is equal to 0, will i-th of individual it is true
It is set to m+1 layers of individual；
When the third judging result indicates that described i-th individual updated variable not equal to 0, judges that described m layers are
It is no to there is than i-th individual preferably individual；
Successively all individuals are layered.
4. the Location Selection of Logistics Distribution Center optimization method of multi-target evolution according to claim 1, which is characterized in that described
According to the crowding distance and the level of the individual, M individual of initial population is filtered out, is specifically included:
N individual is randomly selected from initial population,；
Obtain the described n minimum individual of individual middle layer number；
Judge to obtain the 4th judging result whether comprising multiple individuals in the minimum individual of the number of plies；
When the 4th judging result indicates in the minimum individual of the number of plies comprising multiple individuals, described multiple are determined
The maximum individual of crowding distance is determined as the individual in M filtered out individual by the maximum individual of crowding distance in body；
When the 4th judging result indicates in the minimum individual of the number of plies only to include an individual, by that the number of plies is minimum
Body is determined as the individual in M filtered out individual；
Successively determine the M individual filtered out.
5. the Location Selection of Logistics Distribution Center optimization method of multi-target evolution according to claim 1, which is characterized in that described
The M individual filtered out is intersected, is made a variation, population of new generation is generated, specifically includes:
By the way of single point crossing, randomly chooses i-th of individual and j-th of individual is intersected, two after being intersected
Individual, 1≤i≤n, 1≤j≤n；
To each of population individual, Mutation, the individual after being made a variation are carried out；
Individual after successively obtaining all variations.
6. the Location Selection of Logistics Distribution Center optimization method of multi-target evolution according to claim 1, which is characterized in that described
According to the layering for merging population as a result, filtering out preferable individual, also to carry out later:
Obtain current iteration number；
Judge whether the current iteration number reaches maximum number of iterations, obtains the 5th judging result；
When the 5th judging result indicates that current iteration number reaches maximum number of iterations, by best N number of of screening
Body is determined as the individual of final output；
When the 5th judging result indicates that current iteration number is not up to maximum number of iterations, by the best N number of of screening
Individual is updated to initial population.
7. a kind of Location Selection of Logistics Distribution Center optimization system of multi-target evolution, which is characterized in that the system comprises:
Module is obtained, for obtaining all logistics distribution centers to be selected to the dispatching expense of each distribution point and all to be selected
Logistics distribution center expenditure of construction；
Initial population generation module, it is described for generating initial population at random according to the dispatching expense and the expenditure of construction
It include individual in initial population；
First object value determining module, for utilizing function according to the dispatching expenseIt determines k-th
The first object value of individual, wherein S indicates that the element number of the set of distribution point, C indicate the element of the set of home-delivery center
Number, dijIt indicates from distribution point i to the distance of home-delivery center j, ZijIndicate whether distribution point i is serviced by home-delivery center j；
Second target value determining module, for utilizing function according to the expenditure of constructionDetermine k-th
Second target value of body, wherein C indicates the element number of the set of home-delivery center, VjIndicate being built into for j-th of home-delivery center
This, hjIndicate whether j-th of home-delivery center builds；
Third target value determining module, for according to the logistics distribution center to be selected and all distribution points to be selected,
Utilize functionDetermine the third target value of k-th of individual, wherein S indicates the set of distribution point
Element number, C indicate the element number of the set of home-delivery center, ZijIndicate whether distribution point i is serviced by home-delivery center j；
First layer module is used for according to the first object value, second target value and the third target value to initial
The individual of population is layered, and each layer includes multiple individuals, and the low individual of level dominates the high individual of level；
Crowding distance computing module, for calculating the crowding distance of the individual；
First screening module filters out M of initial population for the crowding distance and the level according to the individual
Body；
Population generation module of new generation, the M individual for will filter out are intersected, are made a variation, and population of new generation is generated, described
Intersect in population of new generation comprising M, the individual after variation；
Merge population generation module, for merging initial population and population of new generation, generates and merge population；
Second hierarchical block, for being layered to all individuals in the merging population；
Second screening module, for the layering according to the merging population as a result, filtering out preferable individual；
Determining module, for individual as Selection of Logistic Distribution Center to be selected by what is screened.
8. the Location Selection of Logistics Distribution Center optimization system of multi-target evolution according to claim 7, which is characterized in that described
First layer module, specifically includes:
Variable, set determination unit, for according to the first object value of each individual, second target value and described the
Three target values, determine the corresponding variable of each individual and set, and the variable is number of individuals better than current individual in population, institute
State the set that collection is combined into the current individual individual serial number better than in population；
Delaminating units, for being layered according to the variable and the set of each individual.
9. the Location Selection of Logistics Distribution Center optimization system of multi-target evolution according to claim 7, which is characterized in that described
Delaminating units specifically include:
First judging unit obtains first for judging whether the variable k of i-th of individual is equal to 0 for i-th of individual
Judging result；
Individual determination unit will be described when for indicating that the variable of i-th of individual is equal to 0 when first judging result
I-th of individual is determined as m layers of individual, m >=1；
Second judgment unit, when for indicating the variable of i-th of individual when first judging result not equal to 0, judgement
M-1 layers preferably individual with the presence or absence of than i-th individual, obtains the second judging result；
Variable update unit, for indicating there is than i-th individual in described m-1 layers preferably when second judging result
When individual, the variable update by i-th of individual is k-1；
Third judging unit obtains third judging result for judging whether the updated variable of i-th of individual is equal to 0；
Individual determination unit, for indicating that the updated variable of i-th of individual is equal to 0 when the third judging result,
I-th of individual is determined as to m+1 layers of individual；
When the third judging result indicates that described i-th individual updated variable not equal to 0, judges that described m layers are
It is no to there is than i-th individual preferably individual；
Successively all individuals are layered.
10. the Location Selection of Logistics Distribution Center optimization system of multi-target evolution according to claim 7, which is characterized in that institute
The first screening module is stated, is specifically included:
Individual selection unit, for randomly selecting n individual from initial population,；
Number of plies acquiring unit, for obtaining the described n minimum individual of individual middle layer number；
Whether 4th judging unit obtains fourth judging result comprising multiple individuals in the minimum individual of the number of plies for judging；
Crowding distance determination unit, for indicating in the minimum individual of the number of plies when the 4th judging result comprising multiple
When body, determines the maximum individual of crowding distance in multiple individuals, the maximum individual of crowding distance is determined as filtering out
M individual in an individual；
Individual determination unit, for indicating in the minimum individual of the number of plies when the 4th judging result only comprising an individual
When, the minimum individual of the number of plies is determined as the individual in M filtered out individual；
Successively determine the M individual filtered out.
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