CN110363455A - A kind of route planning method and system of article collection - Google Patents
A kind of route planning method and system of article collection Download PDFInfo
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- CN110363455A CN110363455A CN201810311994.7A CN201810311994A CN110363455A CN 110363455 A CN110363455 A CN 110363455A CN 201810311994 A CN201810311994 A CN 201810311994A CN 110363455 A CN110363455 A CN 110363455A
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Abstract
The route planning method and system collected the present invention provides a kind of article.The present invention considers the characteristic of article shelf-life different under different weather in goods transportation, improve route optimization model, shelf-life, terminal capacity and transportation cost can be more accurately balanced, guarantees the timeliness of goods transportation while reducing transportation cost.
Description
Technical field
The present invention relates to route planning technical fields, and in particular to a kind of route planning method and system of article collection.
Background technique
In urban life, rubbish is usually poured in the dustbin of cell by resident, then unified by property or environmental sanitation
Garbage transfer station is transported, finally by the unified garbage transporting by garbage transfer station of cram packer to destructor plant (such as rubbish
Rubbish burning/landfill yard).In rural area, peasant household usually sells agricultural product (such as fresh vegetables, fruit, aquatic products) to villages and small towns
In country fair then collect agricultural product, and large size of the consolidated delivery into cities and towns from each country fair by haulage vehicle
Wholesale market of agricultural products.
With the development of urban economy, the emergence of electric business and carryout service, generation increases year by year.In entire rubbish
During rubbish processing, the 75%-80% of the cost accounting totle drilling cost of garbage transporting.Similar, the cost of agricultural product transport
Occupy considerable proportion in agricultural product price.
Route planning, commonly used in design transport paths traversed, to obtain lower transportation cost (such as time, oil
Consumption etc.).Application of the route planning in daily life production is very more, for example, the application scenarios more than being directed to, by planning vehicle
Article is collected from multiple terminals (such as garbage transfer station or country fair) and is transported to the route of terminus, reduce transport
Cost.
There are a features, i.e. article may have certain shelf-life for application scenarios above.The prior art is being planned
When the transit route of use above scene, using Optimum cost as target, carries out modeling and optimal solution solves.In modeling process,
It is usually only concerned transportation cost, there is no the shelf-lifves for considering article itself, therefore, it is difficult to guarantee the timeliness of goods transportation, no
Transportation cost and timeliness can be balanced well.
Summary of the invention
Technical problems to be solved of the embodiment of the present invention are to provide the route planning method and system of a kind of article collection, energy
It is enough to be balanced in route planning for transportation cost and article timeliness, guarantee goods transportation while reducing transportation cost
Timeliness.
In order to solve the above technical problems, the route planning method that article provided in an embodiment of the present invention is collected, is applied to logical
It crosses vehicle to collect the article from multiple terminals and be transported to terminus, the route planning method includes:
The state of weather for obtaining the same day, predicts the number of days N of shelf-life of the article under the state of weather；
Daily article forecast production of each terminal in following N days is obtained, described following N days include the same day
Inside；
The target equation for establishing the transport totle drilling cost in the N days future, under preset restrictive condition, to the target
Equation carries out the solution of transport the lowest cost, obtains the route general planning in the N days future；Wherein, the restrictive condition
It includes at least: being less than the shelf-life of the article on the day of the vehicle in the article that the terminal is collected；And it is any
Object storing amount of the terminal on the day of after article collection and second day the sum of article forecast production, are no more than described any
The capacity of terminal；
According to the route general planning in the N days future, the vehicle routing plan on the same day is exported.
Preferably, the restrictive condition further includes at least one of the following conditions:
The vehicle is daily all from preset initiating station；
In on the same day, each terminal at most only has a vehicle to collect article；
The vehicle does not overload when leaving the terminal；
Object storing amount of vehicle when from the initiating station and behind the arrival terminus is 0；
Object storing amount of the terminal after the vehicle leaves is 0；And
Object storing amount of the vehicle after leaving the terminal is equal to the vehicle before reaching the terminal
Object storing amount and the terminal the sum of object storing amount.
Preferably, the step of target equation for establishing the transport totle drilling cost in the N days future, comprising:
According to transportation cost of each vehicle between the interior website and website passed through daily, count described N days following
Interior transport totle drilling cost obtains the target equation.
Preferably, the step of solution that transport the lowest cost is carried out to the target equation, comprising:
Using genetic algorithm, simulated annealing or ant group algorithm etc., the calculating of optimal solution is carried out to the target equation,
Obtain the route general planning in the N days future.
Preferably, the step of daily article forecast production for obtaining each terminal in following N days, packet
It includes:
Obtain the crowd characteristic in the terminal overlay area, the crowd characteristic include the size of population, age distribution,
One or more of vocational distribution；
Obtain the predeterminable event of state of weather and influence article throughput daily in the N days future；
According to the crowd characteristic in the terminal overlay area, state of weather and shadow daily in the N days future
The predeterminable event for ringing article throughput, predicts daily article forecast production of the terminal in following N days.
Preferably, the state of weather includes: gas epidemic disaster and intensity of illumination.
The embodiment of the invention also provides the route planning system that a kind of article is collected, it is applied to through vehicle from multiple
Turn station to collect the article and be transported to terminus, the route planning system includes:
Weather obtains module, for obtaining the state of weather on the same day, predicts guarantor of the article under the state of weather
The number of days N of matter phase；
Production forecast module, for obtaining daily article forecast production of each terminal in following N days, institute
Following N days were stated including the same day；
Optimization Solution module, the target equation of the transport totle drilling cost for establishing in the N days future, in preset limitation
Under the conditions of, the solution of transport the lowest cost is carried out to the target equation, obtains the route general planning in the N days future；
Wherein, the restrictive condition includes at least: being less than the article in the article that the terminal is collected on the day of the vehicle
Shelf-life；And object storing amount and second day article forecast production of any terminal on the day of after article collection
The sum of, no more than the capacity of any terminal；
Route output module, for exporting the vehicle route rule on the same day according to the route general planning in the N days future
It draws.
Preferably, the restrictive condition further includes at least one of the following conditions:
The vehicle is daily all from preset initiating station；
In on the same day, each website at most only has a vehicle to collect article；
The vehicle does not overload when leaving the terminal；
Object storing amount of vehicle when from the initiating station and behind the arrival terminus is 0；
Object storing amount of the terminal after the vehicle leaves is 0；And
Object storing amount of the vehicle after leaving the terminal is equal to the vehicle before reaching the terminal
Object storing amount and the terminal the sum of object storing amount.
Preferably, the production forecast module, specifically for obtaining the crowd characteristic in the terminal overlay area, institute
Stating crowd characteristic includes one or more of the size of population, age distribution, vocational distribution；It will obtain in the N days future daily
State of weather and influence article throughput predeterminable event；And according in the terminal overlay area crowd characteristic,
Daily state of weather and the predeterminable event of influence article throughput, predict the terminal at following N days in the N days future
Interior daily article forecast production.
The embodiment of the invention also provides another article collect route planning system, comprising: memory, processor and
The computer program that can be run on a memory and on a processor is stored, when the computer program is executed by the processor
The step of realizing the route planning method that article as described above is collected.
The embodiment of the invention also provides a kind of computer readable storage medium, deposited on the computer readable storage medium
Computer program is contained, the computer program realizes the route planning side that article as described above is collected when being executed by processor
The step of method.
Compared with prior art, route planning and system that article provided in an embodiment of the present invention is collected, it is contemplated that article
The characteristic of article shelf-life different under different weather, improves route optimization model in transport, can be with more acurrate Horizon
Weigh shelf-life, terminal capacity and transportation cost, guarantees the timeliness of goods transportation while reducing transportation cost.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by institute in the description to the embodiment of the present invention
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without creative efforts, can also obtain according to these attached drawings
Obtain other attached drawings.
Fig. 1 is a kind of application environment schematic diagram of route planning method provided in an embodiment of the present invention；
Fig. 2 is a kind of flow diagram for the route planning method that article provided in an embodiment of the present invention is collected；
Fig. 3 is a kind of structural schematic diagram for the route planning system that article provided in an embodiment of the present invention is collected；
Fig. 4 is another structural schematic diagram for the route planning system that article provided in an embodiment of the present invention is collected.
Specific embodiment
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and tool
Body embodiment is described in detail.In the following description, such as specific configuration is provided and the specific detail of component is only
In order to help comprehensive understanding the embodiment of the present invention.It therefore, it will be apparent to those skilled in the art that can be to reality described herein
Example is applied to make various changes and modifications without departing from scope and spirit of the present invention.In addition, for clarity and brevity, it is omitted pair
The description of known function and construction.
It should be understood that " one embodiment " or " embodiment " that specification is mentioned in the whole text mean it is related with embodiment
A particular feature, structure, or characteristic is included at least one embodiment of the present invention.Therefore, occur everywhere in the whole instruction
" in one embodiment " or " in one embodiment " not necessarily refer to identical embodiment.In addition, these specific features, knot
Structure or characteristic can combine in any suitable manner in one or more embodiments.
In various embodiments of the present invention, it should be appreciated that the size of the serial number of following each processes is not meant to execute suitable
Sequence it is successive, the execution of each process sequence should be determined by its function and internal logic, the implementation without coping with the embodiment of the present invention
Process constitutes any restriction.
In the application scenes of the route planning of goods transportation, article may have the specific shelf-life.For example, raw
The fortune of rubbish living, which is received, has timeliness, if do not cleared in time, growth and the infectious disease that will lead to bacterium are high-incidence, also,
Timeliness different under different weather conditions, for example in cold winter, the pot-life of rubbish is relatively long, and in sweltering heat
Summer, the timeliness of rubbish requires higher.Similar, agricultural product also have certain shelf-life, if without transporting in time, it can
Agricultural product can be caused to rot, also, the shelf-life of agricultural product, to be also required to weather condition closely related.
Conventional path planning algorithm in the prior art, usually not considers the article timeliness in above-mentioned application scenarios.
If using frequent transport processing of collecting to guarantee that article timeliness is e.g. collected transport daily, then transportation cost will
It can increase；And it is collected again if being collected transport according to fixed time interval (such as 3 days) or packing volume when transfer
Transport, and it is difficult to ensure the timeliness phase of article.
By taking garbage collection as an example, in practical applications, the transport capacity of garbage truck usually is out the daily rubbish of terminal
Yield.If the rising of cost will be will lead to by all carrying out garbage collection to terminal daily, such as some garbage trucks can not expire
It carries, so that the utilization rate of vehicle be caused to decline.It, can be with complex optimum N when terminal article throughput is less than vehicle transport ability
Route in it guarantees that each car is all fully loaded as far as possible (so that the carrying capacity of vehicle is fully used), reduces frequency of sending a car,
To achieve the purpose that cut operating costs.
The embodiment of the invention provides the route planning method that a kind of article is collected, this method is adapted to the fortune of planning article
Defeated route, particularly, the above method of the embodiment of the present invention are particularly suitable for the article with the shelf-life, such as house refuse, vegetable
The agricultural product such as dish fruit and other food etc..The embodiment of the present invention is when carrying out route planning, it is contemplated that the shelf-life of article
With the correlativity of weather, it is balanced so as to be directed to transportation cost and article timeliness, while reducing transportation cost
Guarantee the timeliness of goods transportation.
In the present embodiment, the route planning method that above-mentioned article is collected can be applied to as shown in Figure 1 by server
102 and the environment that is constituted of terminal 104 in.As shown in Figure 1, server 102 is communicated by network with terminal 104, it is above-mentioned
Network includes but is not limited to: wide area network, Metropolitan Area Network (MAN) or local area network, and terminal 104 is not limited to PC (PC), mobile phone, puts down
Plate computer etc..The route planning method of the embodiment of the present invention can be executed by server 102, can also be held by terminal 104
Row can also be and be executed jointly by server 102 and terminal 104.Wherein, terminal 104 executes the route rule of the embodiment of the present invention
The method of drawing is also possible to be executed by client mounted thereto.
Referring to figure 2., the route planning method that article provided by one embodiment of the present invention is collected, applied to passing through vehicle
The route planning collected the article from multiple terminals and be transported to terminus.For example, scene is collected for rubbish above,
Terminal can be garbage transfer station, and terminus can be preset destructor plant (such as waste incineration/landfill yard)；Example again
Such as, scene is collected for agricultural product above, terminal can be each country fair, and terminus can be large-scale agricultural product batch
First sale field.In the embodiment of the present invention, above-mentioned article collection can be carried out by one or more vehicles.There is transport task on the same day
Vehicle is collected article from terminal and is transported to end from preset garage according to route determined by the embodiment of the present invention
Point station.As shown in Fig. 2, route planning method provided in an embodiment of the present invention, comprising:
Step 21, the state of weather for obtaining the same day, predicts the number of days of shelf-life of the article under the state of weather
N。
Here, in embodiments of the present invention, the shelf-life is so that article is when can satisfy article after transporting to terminus
The time limit that effect property requires, here, shelf-life can be with consecutive days (number of days) for unit.For example, needing rubbish in rubbish corruption
It loses and transports before going bad to terminus, therefore its shelf-life can be calculated according under specific state of weather.Similar, for agriculture
A service life can also be calculated in product according to state of weather, it is contemplated that agricultural product, which are sold, reaches ultimate consumer's hand
In need a period of time, therefore, can be subtracted on the basis of the service life one sell required for the time determine.
For a certain article (such as house refuse), it may include different types of rubbish and form, every kind
Constituent may have the different shelf-lifves.To simplify the process, the embodiment of the present invention is by the different constituents of the article
Shelf-life simplification processing, using the same shelf-life, for example, the guarantor with shelf-life shortest constituent, as the article
The matter phase.
In the embodiment of the present invention, obtain the state of weather on the same day, it is then assumed that the weather of following a period of time with the same day
State of weather it is similar, thus predict shelf-life of the article under current weather state, it is assumed that prediction result is N days, i.e. article
Shelf-life be N days, N is integer more than or equal to 1 here.N days including the same day.For example, if N is equal to 1, the shelf-life
It is 1 day, the article of each terminal is required to transport on the day of to terminus.If N is equal to 2, the shelf-life is 2 days, each
The article of terminal be required to include on the day of and on the day of one day after this 2 days in, transport to terminus.
The acquisition of state of weather, may be by from related media, as obtained weather in network, TV programme, broadcast program
State of weather provided by oracle.It is of course also possible to voluntarily acquire the related data of state of weather.In the embodiment of the present invention
In, state of weather can specifically include following parameter: temperature, humidity and photograph intensity etc..Then, vaporous according to the day on the same day
State calculates the shelf-life of the article under the state of weather.A kind of specific calculation may is that collects article in difference in advance
Then the statistical data of shelf-life under state of weather searches the same day state of weather corresponding shelf-life from the statistical data.
Another calculation of shelf-life may is that the correlation model for pre-establishing the parameter of shelf-life and state of weather, utilize thing
The statistical data of shelf-life under the different weather state first collected carries out model training, the model obtained using training, prediction
Shelf-life under current weather state.
Step 22, daily article forecast production of each terminal in following N days is obtained, it is described N days following
Including the same day.
Here, after the N days shelf-life of article has been determined, need to obtain each terminal following N days (on the day of including
It is interior) article forecast production.The prediction mode of article throughput include it is a variety of, for example, a kind of mode are as follows: in advance collect terminal exist
The historical data of article throughput under the different periods of history, then, according to from above-mentioned historical data, finding date institute to be predicted
The historical yield of corresponding historical date, the forecast production as the date to be predicted.The date can be year, the moon or Zhou Weiyi
A measurement period.
Specifically, may is that the article for collecting the terminal in nearest 1 year produces using year as a kind of example of measurement period
Then amount according to date to be predicted (such as on April 1st, 2018), finds over phase same date (such as on April 1st, 2017) in 1 year
Article throughput, or in the past several years phase same date article average product, the article throughput as the date to be predicted.With week
The article throughput that may is that the terminal in collection nearest one week for a kind of example of measurement period, then, according to day to be predicted
Phase (such as on April 1st, 2018 be Sunday), the article throughput of phase same date (i.e. Sunday) in one week is found over, if passing by
The article average product of phase same date in dry week, the article throughput as the date to be predicted.Certainly, the embodiment of the present invention may be used also
To be based on different measurement periods, the article forecast production on date to be predicted is obtained；Then, it is obtained to based on different measurement periods
Article forecast production be weighted summation, obtain final article forecast production.Specific weight can be according to different statistics
The significance level in period is adjusted.
Another prediction mode of article throughput may is that the overlay area according to terminal, acquire in overlay area
Then perimeter data relevant to article throughput carries out yield modeling, and going through using article throughput according to these perimeter datas
History data carry out model training, and then can use trained model, predict the article throughput on date to be predicted.It is with rubbish
Example, it is contemplated that (such as rainstorm weather people can more select to take out house refuse, therefore can produce with resident's quantity, state of weather
The rubbish of raw more such as lunch boxes etc) and particular event (rubbish as double 11 events will lead to package packaging group is a large amount of
Increase) etc. factors it is related, therefore, the perimeter data in terminal overlay area, including but not limited to following data can be acquired:
The size of population, age distribution, vocational distribution, state of weather daily in N days future and the predeterminable event for influencing article throughput,
It is modeled and is predicted based on above-mentioned perimeter data, obtain daily Municipal Garbage Yield of the terminal at following N days.It is with agricultural product
Example, can collect the data such as peasant household's quantity, agricultural cultivation area and the weather conditions of current year in overlay area, according to this
A little data modeling and forecast production.
Step 23, the target equation of the transport totle drilling cost in the N days future is established, it is right under preset restrictive condition
The target equation carries out the solution of transport the lowest cost, obtains the route general planning in the N days future.
Here it is possible to which the transportation cost according to each vehicle between the interior website and website passed through daily, counts institute
The transport totle drilling cost in following N days is stated, the target equation is obtained.For example, it is assumed that the date on the same day is D, the article shelf-life is N
It, then target equation is from D to the calculation formula of the transport totle drilling cost in this N days of (D+N-1).Specifically, transportation cost can
With by money required for the length of transit route or transit route (such as oil consumption expense and the current expense of high speed) come table
Show.One example of target equation are as follows:
Here, above-mentioned target equation indicates to solve so that transport totle drilling cost:It is minimum
Route planning scheme.Wherein, K indicates to participate in the vehicle set of transport, and k indicates current vehicle；A indicates terminal set；dij
It indicates the transportation cost from terminal i to j, specifically can be the length of transit route；yijrkIt indicates in described N days the r days, vehicle
Whether k from terminal i drives to j, wherein if so, yijrkIt is 1, otherwise, yijrkIt is 0.
In the solution procedure of the optimal solution of target equation, need to be arranged relevant restrictive condition, as a kind of realization side
Formula, the restrictive condition may include:
1)D≤Ei
Here, Ei: the shelf-life of the article of terminal i, if there are many article, E in terminaliFor in all items
On nearest date shelf-life, D is less than guaranteeing the quality for the article in the article that terminal i is collected on the day of which indicates vehicle
Phase；
2)
Here,Indicate the article forecast production of D days second day terminal i, LiIndicate that terminal i is working as all kinds of things in nature
Product be collected after object storing amount, Ci: the capacity of terminal i, the formula indicate that any terminal article on the day of collects it
Object storing amount and second day the sum of article forecast production afterwards, no more than the capacity of any terminal.
When carrying out the solution of optimal solution, the embodiment of the present invention can use genetic algorithm, simulated annealing or ant colony
Algorithm etc. carries out the calculating of optimal solution to target equation, obtains the route general planning in the N days future.
For example, can first design gene, (y when being solved using genetic algorithm0011..., ynnNk), gene is one
Vector, the vector illustrate whether each path has haulage vehicle process, i.e., the route general planning in N days in N days.Gene is set
After meter is good, population is generated at random, rejects the individual for not meeting restrictive condition in population, retains one according to the shortest principle of general line
The individual of fixed number amount.Then carry out gene intersection, every generation weed out do not meet the individual of restrictive condition and according to path most
Short sequence leaves a certain number of individuals, until certain generation cross knot beam.Finally, it is corresponding to select the shortest result in path
Gene as route general planning.
Step 24, according to the route general planning in the N days future, the vehicle routing plan on the same day is exported.
After following N days route general plannings including obtaining on the day of, it can be extracted from the route general planning
The vehicle routing plan on the same day and output, and then arrange according to the vehicle routing plan on the same day vehicle transport task on the same day.It is right
Daily vehicle route after the same day can also be arranged according to above-mentioned route general planning.
It is therefore, right in view of there may be certain difference between daily article actual production and article forecast production
Daily vehicle route after the same day, the embodiment of the present invention are recalculated according to above-mentioned steps 11~14, to be based on
More accurately parameter carries out route planning, and totle drilling cost is transported in more efficiently reduction.
By above step, the embodiment of the present invention considers in goods transportation article shelf-life area under different weather
Other characteristic improves route optimization model, can more accurately balance shelf-life, terminal capacity and transportation cost, drop
Guarantee the timeliness of goods transportation while low transportation cost.
In practical applications, in the optimal solution solution procedure for carrying out target equation, in addition to previously described 2 limitations item
More restrictive conditions can also be arranged according to specific application scenarios in part, can specifically include one in the following conditions or
It is multiple:
3)∑j∈Ay0jrk=1 k ∈ K
The formula indicates the vehicle daily all from preset initiating station, y0jrkIt indicates in described N days the r days, vehicle
Whether k from initiating station drives to terminal j.
4)∑k∈Kyijrk≤ 1 (i, j) ∈ A r=1 ... N
The formula indicates on the same day that each terminal at most only has a vehicle to collect article.
5)Sirk≤W
Here, Sirk: the r days in described N days, vehicle k leaves article reserves when terminal i；W: the capacity of vehicle；It should
Formula indicates that vehicle does not overload when leaving terminal.
6)S0rk=S(n+1)rk=0
The formula indicates object storing amount S of vehicle when from the initiating station0rkAnd described in vehicle arrival
Object storing amount S behind terminus(n+1)rkIt is 0.
7)Li=Li×(1-yijrk)
The formula indicates the object storing amount of the r days terminal i in described N days, wherein if by vehicle k come,
The object storing amount that vehicle k leaves rear terminal i is 0.
8)Sjrk=Sirk+Lj
The formula indicates in described N days that object storing amount of the vehicle k after leaving terminal j is equal to vehicle k and exists the r days
Object storing amount S before reaching the terminal jirkWith the object storing amount L of the terminal jjThe sum of.
By taking garbage collecting and transferring as an example, according to the above method of the embodiment of the present invention, route rule can be carried out using following procedure
It draws:
Garbage collecting and transferring administrative center acquires following information: in city the geographical location of each terminal；Transport column rises
Initial station and terminus；The capacity of each garbage transfer station；The capacity of each cram packer；Current weather (temperature, humidity, light
According to intensity) state；The perimeter data of each terminal, such as the size of population, age distribution, vocational distribution and weather and special thing
The data such as part.
Then, collected weather data, such as temperature, humidity and intensity of illumination etc., to calculate rubbish under same day weather are utilized
The shelf lives (N days) of rubbish.Utilize the perimeter data of the terminal of acquisition: population, age distribution, vocational distribution, weather is special
The data such as event predict each terminal future N days daily Municipal Garbage Yields.
Then, using the position of each terminal, the beginning and end of fleet, the capacity of each garbage transfer station, each
The data such as the prediction Municipal Garbage Yield of the capacity of cram packer, the shelf lives of rubbish and each terminal carry out shortest path
The modeling of model.
Then, using genetic algorithm, the optimization algorithms such as simulated annealing carry out the calculating of optimal solution, and obtaining includes the same day
Route planning in following N days inside.
By above procedure, same day D can be started by following D+N-1 days to consider together for N days, guarantee that rubbish is collected
It is not above rubbish timeliness and under the premise of terminal does not exceed its capacity, route of always sending a car in N days is most short.According to obtaining
Route planning arrangement on the day of send a car.Above procedure can then be repeated within second day, compared with the plan of sending a car that the previous day obtains,
It adjusts since the plan of may more accurately sending a car of the data of acquisition has, but can still be guaranteed by entire optimization process slightly
Path it is most short.
Based on above method, the embodiment of the invention also provides the systems for implementing the above method, referring to figure 3., the present invention
Embodiment provides a kind of route planning system 30 that article is collected, comprising:
Weather obtains module 31, for obtaining the state of weather on the same day, predicts the article under the state of weather
The number of days N of shelf-life；
Production forecast module 32, for obtaining daily article forecast production of each terminal in following N days,
Described following N days including the same day；
Optimization Solution module 33, the target equation of the transport totle drilling cost for establishing in the N days future, in preset limit
Under the conditions of system, the solution of transport the lowest cost is carried out to the target equation, the route obtained in the N days future is always advised
It draws；Wherein, the restrictive condition includes at least: being less than the object in the article that the terminal is collected on the day of the vehicle
The shelf-life of product；And object storing amount and second day article of any terminal on the day of after article collection are predicted to produce
The sum of amount, no more than the capacity of any terminal；
Route output module 34, for exporting the vehicle route rule on the same day according to the route general planning in the N days future
It draws.
Here, the state of weather can specifically include: gas epidemic disaster and intensity of illumination.
The above route planning system 30, during article is collected, it is contemplated that the article shelf-life is in difference in goods transportation
The characteristic of different under weather, improves route optimization model, can more accurately balance shelf-life, terminal capacity and fortune
Defeated cost guarantees the timeliness of goods transportation while reducing transportation cost.
As a kind of implementation, above-mentioned restrictive condition can also include at least one of the following conditions:
The vehicle is daily all from preset initiating station；
In on the same day, each website at most only has a vehicle to collect article；
The vehicle does not overload when leaving the terminal；
Object storing amount of vehicle when from the initiating station and behind the arrival terminus is 0；
Object storing amount of the terminal after the vehicle leaves is 0；And
Object storing amount of the vehicle after leaving the terminal is equal to the vehicle before reaching the terminal
Object storing amount and the terminal the sum of object storing amount.
As a kind of implementation, above-mentioned Optimization Solution module 33 can be passed through according to each vehicle interior daily
Website and website between transportation cost, count the transport totle drilling cost in described following N days, obtain the target equation.
As a kind of implementation, above-mentioned Optimization Solution module 33 is carrying out transport assembly to the target equation
Originally when minimum solution, genetic algorithm, simulated annealing or ant group algorithm be can use, the target equation is carried out optimal
The calculating of solution obtains the route general planning in the N days future.
Referring to FIG. 4, another hardware for the route planning system 400 collected the embodiment of the invention provides another article
Structural schematic diagram, comprising: processor 401, network interface 402, memory 403, user interface 404 and bus interface, in which:
In embodiments of the present invention, route planning system 400 further include: storage on a memory 403 and can be in processor
The computer program run on 401 realizes following steps when computer program is by processor 401, execution:
The state of weather for obtaining the same day, predicts the number of days N of shelf-life of the article under the state of weather；
Daily article forecast production of each terminal in following N days is obtained, described following N days include the same day
Inside；
The target equation for establishing the transport totle drilling cost in the N days future, under preset restrictive condition, to the target
Equation carries out the solution of transport the lowest cost, obtains the route general planning in the N days future；Wherein, the restrictive condition
It includes at least: being less than the shelf-life of the article on the day of the vehicle in the article that the terminal is collected；And it is any
Object storing amount of the terminal on the day of after article collection and second day the sum of article forecast production, are no more than described any
The capacity of terminal；
According to the route general planning in the N days future, the vehicle routing plan on the same day is exported.
Here, the state of weather includes: gas epidemic disaster and intensity of illumination.
In Fig. 4, bus architecture may include the bus and bridge of any number of interconnection, specifically be represented by processor 401
One or more processors and the various circuits of memory that represent of memory 403 link together.Bus architecture can be with
Various other circuits of such as peripheral equipment, voltage-stablizer and management circuit or the like are linked together, these are all these
Well known to field, therefore, it will not be further described herein.Bus interface provides interface.Network interface 402 can be with
It is wired or wireless network card equipment, realizes transmission-receiving function of the data on network.For different user equipmenies, user interface
404 can also be and external the interface for needing equipment can be inscribed, and the equipment of connection includes but is not limited to keypad, display, raises
Sound device, microphone, control stick etc..
Processor 401, which is responsible for management bus architecture and common processing, memory 403, can store processor 401 and is holding
Used data when row operation.
Optionally, the restrictive condition further includes at least one of the following conditions:
The vehicle is daily all from preset initiating station；
In on the same day, each terminal at most only has a vehicle to collect article；
The vehicle does not overload when leaving the terminal；
Object storing amount of vehicle when from the initiating station and behind the arrival terminus is 0；
Object storing amount of the terminal after the vehicle leaves is 0；And
Object storing amount of the vehicle after leaving the terminal is equal to the vehicle before reaching the terminal
Object storing amount and the terminal the sum of object storing amount.
Optionally, following steps be can also be achieved when computer program is executed by processor 401:
According to transportation cost of each vehicle between the interior website and website passed through daily, count described N days following
Interior transport totle drilling cost obtains the target equation.
Optionally, following steps be can also be achieved when computer program is executed by processor 401:
Using genetic algorithm, simulated annealing or ant group algorithm, the calculating of optimal solution is carried out to the target equation, is obtained
Obtain the route general planning in the N days future.
Optionally, following steps be can also be achieved when computer program is executed by processor 401:
Obtain the crowd characteristic in the terminal overlay area, the crowd characteristic include the size of population, age distribution,
One or more of vocational distribution；
Obtain the predeterminable event of state of weather and influence article throughput daily in the N days future；
According to the crowd characteristic in the terminal overlay area, state of weather and shadow daily in the N days future
The predeterminable event for ringing article throughput, predicts daily article forecast production of the terminal in following N days.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In embodiment provided herein, it should be understood that disclosed device and method can pass through others
Mode is realized.For example, the apparatus embodiments described above are merely exemplary, for example, the division of the unit, only
A kind of logical function partition, there may be another division manner in actual implementation, for example, multiple units or components can combine or
Person is desirably integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be through some interfaces, the INDIRECT COUPLING or communication link of device or unit
It connects, can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.Some or all of unit therein can be selected to realize the embodiment of the present invention according to the actual needs
Purpose.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.
It, can be with if the function is realized in the form of SFU software functional unit and when sold or used as an independent product
It is stored in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially in other words
The part of the part that contributes to existing technology or the technical solution can be embodied in the form of software products, the meter
Calculation machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be a
People's computer, server or network equipment etc.) it performs all or part of the steps of the method described in the various embodiments of the present invention.
And storage medium above-mentioned includes: that USB flash disk, mobile hard disk, ROM, RAM, magnetic or disk etc. are various can store program code
Medium.
The route planning method and system of the article collection of the embodiment of the present invention are described in detail above.It can see
Out, the route planning method and system that article provided in an embodiment of the present invention is collected, when carrying out route planning, it is contemplated that article
Shelf-life and weather correlativity, so as to be balanced for transportation cost and article timeliness, reduce transport at
The timeliness of this while guarantee goods transportation.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can easily think of the change or the replacement, and should all contain
Lid is within protection scope of the present invention.Therefore, protection scope of the present invention should be subject to the protection scope in claims.
Claims (11)
1. the route planning method that a kind of article is collected from multiple terminals collection article and is transported applied to by vehicle
It stands to terminal, which is characterized in that the route planning method includes:
The state of weather for obtaining the same day, predicts the number of days N of shelf-life of the article under the state of weather；
Daily article forecast production of each terminal in following N days is obtained, described following N days include existing on the same day
It is interior；
The target equation for establishing the transport totle drilling cost in the N days future, under preset restrictive condition, to the target equation
The solution of transport the lowest cost is carried out, the route general planning in the N days future is obtained；Wherein, the restrictive condition is at least
The shelf-life of the article is less than on the day of including: the vehicle in the article that the terminal is collected；And any transfer
The object storing amount stood on the day of after article collection and second day the sum of article forecast production, are no more than any transfer
The capacity stood；
According to the route general planning in the N days future, the vehicle routing plan on the same day is exported.
2. the method as described in claim 1, which is characterized in that the restrictive condition further includes at least one in the following conditions
Person:
The vehicle is daily all from preset initiating station；
In on the same day, each terminal at most only has a vehicle to collect article；
The vehicle does not overload when leaving the terminal；
Object storing amount of vehicle when from the initiating station and behind the arrival terminus is 0；
Object storing amount of the terminal after the vehicle leaves is 0；And
Object storing amount of the vehicle after leaving the terminal, equal to object of the vehicle before reaching the terminal
The sum of the object storing amount of product storage capacity and the terminal.
3. method according to claim 1 or 2, which is characterized in that described to establish transport totle drilling cost in described following N days
The step of target equation, comprising:
According to transportation cost of each vehicle between the interior website and website passed through daily, count in the N days future
Totle drilling cost is transported, the target equation is obtained.
4. method as claimed in claim 3, which is characterized in that described to carry out transport the lowest cost to the target equation
The step of solution, comprising:
Using genetic algorithm, simulated annealing or ant group algorithm, the calculating of optimal solution is carried out to the target equation, obtains institute
State the route general planning in following N days.
5. the method as described in claim 1, which is characterized in that each terminal of acquisition is every in following N days
The step of it article forecast production, comprising:
The crowd characteristic in the terminal overlay area is obtained, the crowd characteristic includes the size of population, age distribution, occupation
One or more of distribution；
Obtain the predeterminable event of state of weather and influence article throughput daily in the N days future；
According to the crowd characteristic in the terminal overlay area, state of weather daily in the N days future and influence object
The predeterminable event of product yield predicts daily article forecast production of the terminal in following N days.
6. the method as described in claim 1, which is characterized in that the state of weather includes: that gas epidemic disaster and illumination are strong
Degree.
7. the route planning system that a kind of article is collected from multiple terminals collection article and is transported applied to by vehicle
It stands to terminal, which is characterized in that the route planning system includes:
Weather obtains module, for obtaining the state of weather on the same day, predicts shelf-life of the article under the state of weather
Number of days N；
Production forecast module, for obtaining daily article forecast production of each terminal in following N days, it is described not
Came N days including the same day；
Optimization Solution module, the target equation of the transport totle drilling cost for establishing in the N days future, in preset restrictive condition
Under, the solution of transport the lowest cost is carried out to the target equation, obtains the route general planning in the N days future；Wherein,
The restrictive condition includes at least: being less than guaranteeing the quality for the article in the article that the terminal is collected on the day of the vehicle
Phase；And object storing amount and second day article forecast production the sum of of any terminal on the day of after article collection, no
More than the capacity of any terminal；
Route output module, for exporting the vehicle routing plan on the same day according to the route general planning in the N days future.
8. route planning system as claimed in claim 7, which is characterized in that the restrictive condition further includes in the following conditions
At least one:
The vehicle is daily all from preset initiating station；
In on the same day, each website at most only has a vehicle to collect article；
The vehicle does not overload when leaving the terminal；
Object storing amount of vehicle when from the initiating station and behind the arrival terminus is 0；
Object storing amount of the terminal after the vehicle leaves is 0；And
Object storing amount of the vehicle after leaving the terminal, equal to object of the vehicle before reaching the terminal
The sum of the object storing amount of product storage capacity and the terminal.
9. route planning system as claimed in claim 7 or 8, which is characterized in that
The production forecast module, specifically for obtaining the crowd characteristic in the terminal overlay area, the crowd characteristic
Including one or more of the size of population, age distribution, vocational distribution；Obtain state of weather daily in the N days future
And influence the predeterminable event of article throughput；And according to crowd characteristic, the future N in the terminal overlay area
Daily state of weather and the predeterminable event of influence article throughput, predict that the terminal is daily in following N days in it
Article forecast production.
10. the route planning system that a kind of article is collected characterized by comprising memory, processor and be stored in memory
Computer program that is upper and can running on a processor, is realized when the computer program is executed by the processor as right is wanted
The step of route planning method that article described in asking any one of 1 to 6 is collected.
11. a kind of computer readable storage medium, which is characterized in that be stored with computer on the computer readable storage medium
Program realizes the road collected such as article described in any one of claims 1 to 6 when the computer program is executed by processor
The step of line planing method.
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