CN109447557A - Logistic Scheduling method and device, computer readable storage medium - Google Patents
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Abstract
A kind of Logistic Scheduling method and device, computer readable storage medium, the Logistic Scheduling method include: to obtain order data and transport power data；According to accessed order data and transport power data, order and transport power are matched, and determine that matched order meets constraint condition detection with corresponding transport power, obtains initial schedule scheme；Target capabilities assessment is carried out to the initial schedule scheme；When the initial schedule scheme is not assessed by the target capabilities, rolling optimization is carried out to the initial schedule scheme, until the scheduling scheme after optimization is assessed by the target capabilities；The scheduling scheme assessed by the target capabilities is exported.Using the above scheme, Logistic Scheduling efficiency can be improved.
Description
Technical field
The present embodiments relate to logistics and transportation technical field more particularly to a kind of Logistic Scheduling method and device, calculate
Machine readable storage medium storing program for executing.
Background technique
The factor that complete vehicle logistics scheduling problem is related to is more, including main engine plants and its warehouse, logistics company and its transfer storage facility, holds
The many aspects such as carrier and its contract driver, dealer and its warehouse, constraint condition are complicated, and target is polynary and mutual restriction.
Traditional complete vehicle logistics scheduling does not fully consider that task object carries out optimal packing, without optimization input order yet
The constraint demand of itself, forms operation plan simply by distributing order in real time to vehicle.The scheduling that this mode generates
Scheme is possible to be unsatisfactory for the constraint that business contract angularly proposes, has damage for the stackholders of task various aspects,
Also due to ignoring the reality factor in some scheduling systems and generating invalid scheme, the normal fortune of whole system is influenced
Make, causes the inefficiency of Logistic Scheduling.
Summary of the invention
The technical issues of embodiment of the present invention solves is how to improve the efficiency of Logistic Scheduling.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of Logistic Scheduling method, comprising: obtain order data
And transport power data；According to accessed order data and transport power data, order and transport power are matched, and determination has matched
Order and corresponding transport power meet constraint condition detection, obtain initial schedule scheme；Mesh is carried out to the initial schedule scheme
Mark Performance Evaluation；When the initial schedule scheme is not assessed by the target capabilities, the initial schedule scheme is carried out
Rolling optimization, until the scheduling scheme after optimization is assessed by the target capabilities；The tune that will be assessed by the target capabilities
The output of degree scheme.
Optionally, described that the initial schedule scheme is optimized, comprising: using genetic algorithm to the initial schedule
Scheme carries out rolling optimization.
Optionally, described that rolling optimization is carried out to the initial schedule scheme using genetic algorithm, comprising: to the order
Data and the transport power data carry out random fit, generate multiple scheduling schemes, and the multiple scheduling scheme is formed first
For scheduling scheme population, wherein each scheduling scheme is the individual in the first generation scheduling scheme population；It calculates each
The fitness of individual, optional one from the individual assessed by the target capabilities, as the scheduling scheme after the optimization.
Optionally, by the highest individual of fitness in the individual assessed by target capabilities as the scheduling after the optimization
Scheme.
Optionally, the Logistic Scheduling method further include: when all individuals in the first generation scheduling scheme population
When fitness is not assessed by the target capabilities, at least two individuals are picked out from the i-th generation scheduling scheme population, i is
Positive integer；Constrained individual intersection operation and mutation operation are carried out to the individual picked out, obtain i+1 for scheduling scheme
Population；Fitness calculating is carried out for the individual in scheduling scheme population to the i+1, and is carried out according to fitness calculated result
Target capabilities assessment；It is commented when target capabilities are not satisfied for the fitness of all individuals in scheduling scheme population in the i+1
When estimating, continue to carry out crossover operation and mutation operation for the individual in scheduling scheme population to the i+1, until being met
The individual of target capabilities assessment.
Optionally, described that constrained individual intersection operation and mutation operation are carried out to the individual picked out, obtain i-th
+ 1 generation scheduling scheme population, comprising: transport power corresponding with order all in the individual picked out are formed into a set, meter
Calculate the fitness value of each transport power；Filter out the transport power that fitness value is higher than preset threshold；It is higher than default threshold for what is filtered out
The transport power of value is ranked up from high in the end according to fitness value, is retained since the highest transport power of fitness value, and described in removal
The transport power and its corresponding order that are removed are put into the set being affected by same transport power present in set；Recalculate by
The fitness value of transport power in the set of influence, and the judgement of preset threshold and the screening of transport power are carried out, until fitness is not present
Value is higher than the preset threshold and not retained transport power exists；To in the set being affected transport power and order re-start
Match, and form new individual with the transport power retained, obtains i+1 for scheduling scheme population.
Optionally, described that at least two individuals are picked out from the i-th generation scheduling scheme population, comprising: using roulette
Mode picks out at least two individuals from the i-th generation scheduling scheme population.
Optionally, described that random fit is carried out to the accessed order data and the transport power data, it generates more
A scheduling scheme, and by the multiple scheduling scheme form first generation scheduling scheme population, comprising: from the order data with
Machine extracts an order, and the order being drawn into is matched on corresponding transport power；Determine that be drawn into order and institute are right
The transport power answered meets the constraint condition；It detects whether that there are part-load transport power, and when there are part-load transport power, discharges
All orders loaded on the part-load transport power, until all transport power for carrying order are fully loaded；Determine the number of fully loaded transport power
Mesh is not more than the transport power number after last iteration, completes kind of a population spikes, obtains the first generation scheduling scheme population.
Optionally, after obtaining order data and transport power data, further includes: cleaned the order data to remove
Invalid order；The transport power data are cleaned to remove invalid transport power.
Optionally, described that target capabilities assessment is carried out to the initial schedule scheme, comprising: to the initial schedule scheme
Carry out the target capabilities assessment of multiple target components.
Optionally, the target capabilities for carrying out multiple target components to the initial schedule scheme are assessed, comprising: are determined
The target capabilities of each target component assess corresponding weight；To each corresponding target of the initial schedule scheme
Parameter carries out target capabilities assessment；Corresponding weight is assessed according to the target capabilities of identified each target component, it is right
The target capabilities assessment for obtaining the corresponding each target component of the initial schedule scheme is weighted summation, obtains described initial
The target capabilities of multiple target components of scheduling scheme are assessed.
Optionally, the target component comprises at least one of the following: maximizing shipped quantity, maximizes to load and specify commodity
Urgency level maximizes to load and specifies commodity amount, minimize strange land share-car quantity, minimize dealer's share-car quantity, minimum
Change share-car reservoir area quantity.
Optionally, the constraint condition comprises at least one of the following: loading constraint, the constraint of intention direction, can spell city number
Amount constrains, can spell dealer's number constraint, transport power uses time-constrain, the constraint of transport power access times, share-car constraint, specified order
It is loaded constraint, reservoir area number constraint, business constraint can be spelled.
The embodiment of the present invention also provides a kind of Logistic Scheduling device, comprising: acquiring unit is suitable for obtaining order data and fortune
Force data；Initial schedule schemes generation unit, suitable for according to accessed order data and transport power data, to order and transport power
It is matched, and determines that matched order meets constraint condition detection with corresponding transport power, obtain initial schedule scheme；Target
Performance Evaluation unit is suitable for carrying out target capabilities assessment to the initial schedule scheme；Optimize unit, is suitable for working as the initial tune
When degree scheme is not assessed by the target capabilities, rolling optimization is carried out to the initial schedule scheme, until the tune after optimization
Degree scheme is assessed by the target capabilities；Output unit, suitable for that will be exported by the scheduling scheme that the target capabilities are assessed.
Optionally, the optimization unit is suitable for carrying out rolling optimization to the initial schedule scheme using genetic algorithm.
Optionally, the optimization unit is suitable for carrying out random fit to the order data and the transport power data, generate
Multiple scheduling schemes, and the multiple scheduling scheme is formed into first generation scheduling scheme population, wherein each scheduling scheme is institute
State the individual in first generation scheduling scheme population；The fitness for calculating each individual, is assessed from by the target capabilities
Individual in optional one, as the scheduling scheme after the optimization.
Optionally, the optimization unit, suitable for that will be made by the highest individual of fitness in the individual of target capabilities assessment
For the scheduling scheme after the optimization.
Optionally, the optimization unit is further adapted for the adaptation when all individuals in the first generation scheduling scheme population
When degree is not assessed by the target capabilities, at least two individuals are picked out from the i-th generation scheduling scheme population, i is positive whole
Number；Constrained individual intersection operation and mutation operation are carried out to the individual picked out, obtain i+1 for scheduling scheme kind
Group；Fitness calculating is carried out for the individual in scheduling scheme population to the i+1, and mesh is carried out according to fitness calculated result
Mark Performance Evaluation；When target capabilities assessment is not satisfied for the fitness of all individuals in scheduling scheme population in the i+1
When, continue to carry out crossover operation and mutation operation for the individual in scheduling scheme population to the i+1, until obtaining meeting mesh
Mark the individual of Performance Evaluation.
Optionally, the optimization unit, suitable for forming transport power corresponding with order all in the individual picked out
One set, calculates the fitness value of each transport power；Filter out the transport power that fitness value is higher than preset threshold；By what is filtered out
It higher than the transport power of preset threshold, is ranked up according to fitness value, retains since the highest transport power of fitness value from high in the end,
And same transport power present in the set is removed, the transport power and its corresponding order that are removed are put into the set being affected；
The fitness value of transport power in the set being affected is recalculated, and carries out the judgement of preset threshold and the screening of transport power, until not
It is higher than the preset threshold there are fitness value and not retained transport power presence；To the transport power and order in the set being affected
Matching is re-started, and forms new individual with the transport power retained, obtains i+1 for scheduling scheme population.
Optionally, the optimization unit, suitable for being selected from the i-th generation scheduling scheme population by the way of roulette
At least two individual out.
Optionally, the optimization unit suitable for randomly selecting an order from the order data, and will be drawn into
Order be matched on corresponding transport power；Determine that be drawn into order and corresponding transport power meet the constraint condition；Inspection
It surveys and whether there is part-load transport power, and when there are part-load transport power, discharge the institute loaded on the part-load transport power
There is order, until all transport power for carrying order are fully loaded；Determine the number of fully loaded transport power no more than the transport power number after last iteration
Mesh completes kind of a population spikes, obtains the first generation scheduling scheme population.
Optionally, the Logistic Scheduling device further include: cleaning unit is suitable for obtaining order data and transport power data
Afterwards, the order data is cleaned to remove invalid order；The transport power data are cleaned to remove invalid transport power.
Optionally, the target capabilities assessment unit, suitable for carrying out multiple target components to the initial schedule scheme
Target capabilities assessment.
Optionally, the target capabilities assessment unit is adapted to determine that the target capabilities assessment of each target component is right respectively
The weight answered；Target capabilities assessment is carried out to each corresponding target component of the initial schedule scheme；According to determining
The target capabilities of each target component assess corresponding weight, to obtaining the corresponding each mesh of the initial schedule scheme
The target capabilities assessment of mark parameter is weighted summation, obtains the target capabilities of multiple target components of the initial schedule scheme
Assessment.
Optionally, target component comprises at least one of the following: maximizing shipped quantity, maximizes to load and specify commodity urgent
Degree maximizes to load and specifies commodity amount, minimize strange land share-car quantity, minimize dealer's share-car quantity, minimizing and spell
Garage area quantity.
Optionally, the constraint condition comprises at least one of the following: loading constraint, the constraint of intention direction, can spell city number
Amount constrains, can spell dealer's number constraint, transport power uses time-constrain, the constraint of transport power access times, share-car constraint, specified order
It is loaded constraint, reservoir area number constraint, business constraint can be spelled.
The embodiment of the present invention also provides a kind of Logistic Scheduling device, including memory and processor, deposits on the memory
The computer instruction that can be run on the processor is contained, the processor executes above-mentioned when running the computer instruction
The step of any described Logistic Scheduling method.
The embodiment of the present invention also provides a kind of computer readable storage medium, is stored thereon with computer instruction, the meter
The step of any of the above-described described Logistic Scheduling method is executed when the instruction operation of calculation machine.
Compared with prior art, the technical solution of the embodiment of the present invention has the advantages that
Initial schedule scheme is obtained according to order data and transport power data, by carrying out target capabilities to initial schedule scheme
Assessment carries out rolling optimization to the initial schedule scheme when initial scheduling scheme is not assessed by target capabilities, until
Scheduling scheme to after the optimization for meeting target capabilities assessment, and exported as final scheduling scheme.By to initial schedule side
Case carries out constraint condition detection and rolling optimization, the degree of optimization of exported scheduling scheme can be improved, namely in logistics
Optimal packing is realized in scheduling process, so as to improve the efficiency of Logistic Scheduling.
Detailed description of the invention
Fig. 1 is a kind of flow chart of Logistic Scheduling method in the embodiment of the present invention；
Fig. 2 is a kind of scheduling scheme principle of optimality figure based on genetic algorithm in the embodiment of the present invention；
Fig. 3 is a kind of product process figure of first generation scheduling scheme population in the embodiment of the present invention；
Fig. 4 is a kind of structural schematic diagram of Logistic Scheduling device in the embodiment of the present invention.
Specific embodiment
As described above, traditional complete vehicle logistics scheduling does not fully consider that task object carries out optimal packing, it is also unexcellent
The constraint demand for changing input order itself, forms operation plan simply by distributing order in real time to vehicle.This mode
The scheduling scheme of generation is possible to be unsatisfactory for the constraint that business contract angularly proposes, for the interest relations of task various aspects
There is damage in side, also due to ignoring the reality factor in some scheduling systems and generating invalid scheme, influences whole system
Normal operation, cause the inefficiency of Logistic Scheduling.
To solve the above problems, in embodiments of the present invention, obtaining initial schedule side according to order data and transport power data
Case determines the degree of optimization of obtained scheduling scheme, adjusts when initial by carrying out target capabilities assessment to initial schedule scheme
When degree scheme is not assessed by target capabilities, rolling optimization is carried out to the initial schedule scheme, until obtaining meeting Objective
Scheduling scheme after the optimization that can be assessed, and exported as final scheduling scheme.By carrying out constraint item to initial schedule scheme
Part detection and rolling optimization, can be improved the degree of optimization of exported scheduling scheme, namely during Logistic Scheduling in fact
Existing optimal packing, so as to improve the efficiency of Logistic Scheduling.
It is understandable to enable the above-mentioned purpose, feature and beneficial effect of the embodiment of the present invention to become apparent, below with reference to attached
Figure is described in detail specific embodiments of the present invention.
Referring to Fig.1, a kind of flow chart of Logistic Scheduling method in the embodiment of the present invention is given, below with reference to specific steps
It is described in detail.
Step 11, order data and transport power data are obtained.
In specific implementation, the order data may include following at least one: the type of merchandise, commodity amount, commodity
Place of acceptance, the dealer of commodity etc..The transport power data may include following at least one: intention direction, struck capacity, can
It spells city, dealer, transport power can be spelled using time, transport power access times etc..
It is understood that order data can also include other parameters relevant to commodity to be transported.Transport power data are also
It may include other parameters relevant to means of transport, details are not described herein again.
Step 12, according to accessed order data and transport power data, order and transport power are matched, and determined
Matched order meets constraint condition detection with corresponding transport power, obtains initial schedule scheme.
In specific implementation, according to accessed order data and transport power data, order and transport power are matched,
It i.e. will be on order corresponding commercial loading to corresponding transport power.
In order to improve the matching degree of order and loaded transport power and improve the efficiency of Logistic Scheduling, in specific implementation,
Constraint condition detection can be carried out to matched order and corresponding transport power.Determine the matched order with it is corresponding
After transport power meets constraint condition detection, initial schedule scheme is obtained；Determining the matched order and corresponding transport power
When being unsatisfactory for constraint condition detection, order and transport power can be matched again, and constraint condition is carried out after the completion of matching
Detection, until obtained matched order and transport power meet constraint condition detection.
In specific implementation, the constraint condition may include following at least one: prestowage constraint, intention direction constraint,
Can spell city numbers constraint, can spell dealer's number constraint, transport power using time-constrain, transport power access times constraint, share-car about
Beam, specified order are shipped constraint, can spell reservoir area number constraint, business constraint, wherein business constraint be often referred to it is fully loaded constrain,
Order only transports primary constraint etc..
In specific implementation, it when carrying out constraint condition detection with corresponding transport power to matched order, can be set
One constraint condition.
For example, the constraint condition set is shipped as specified order.For another example, when the constraint condition set is transport power use
Between.
In specific implementation, it when carrying out constraint condition detection with corresponding transport power to matched order, can also set
Set multiple constraint conditions.Only when matched order meets set multiple constraint conditions with corresponding transport power simultaneously,
Determine that matched order and transport power are detected by constraint condition, just so as to fully consider delivered payload capability, the intention of transport power
The constraint conditions such as direction, share-car cost, rush order, specialty goods order limitation, avoid generate failure scheduling, improve order with
The matching degree of transport power, namely the degree of optimization of obtained scheduling scheme can be improved, to be established to improve Logistic Scheduling efficiency
Fixed basis.Further, it is also possible to make full use of transport power, the mileage travelled number of transport power is reduced, reduces Logistic Scheduling cost.
Step 13, target capabilities assessment is carried out to the initial schedule scheme.
In specific implementation, target component may include it is following at least one: the maximization useful load of order, maximum makeup
The urgency level of loading product maximizes the quantity for loading specified article, minimum strange land share-car quantity, minimizes dealer's share-car
Quantity, minimum share-car reservoir area quantity etc..
In specific implementation, it can comment the business evaluating index in a period of time is optimal as set target capabilities
The target component estimated, the ratio that order can also be loaded reaches preset threshold or transport power utilization rate reaches set threshold value and makees
The target component assessed for set target capabilities.
In specific implementation, the target capabilities that single target parameter can be carried out to the initial schedule scheme are assessed,
The target capabilities assessment of multiple target components can be carried out to the initial schedule scheme.
For example, the target capabilities for minimize strange land share-car quantity to initial schedule scheme are assessed.For another example, it is adjusted to initial
Degree scheme maximize the target capabilities assessment for the quantity for loading specified article.
When the target capabilities for carrying out multiple target components to obtained initial schedule scheme are assessed, gained can be improved
The degree of optimization of the scheduling scheme arrived and the efficiency of Logistic Scheduling.
In the present invention is implemented, the Objective of multiple target components can be carried out to initial schedule scheme in the following way
It can assess:
Determine that the target capabilities of each target component assess corresponding weight；To the correspondence of the initial schedule scheme
Each target component carry out target capabilities assessment；It is right respectively to be assessed according to the target capabilities of identified each target component
The weight answered assesses the target capabilities for obtaining the corresponding each target component of the initial schedule scheme and is weighted summation,
Obtain the target capabilities assessment of multiple target components of the initial schedule scheme.
For example, target component may include: the maximization useful load of order, maximize the urgency level, most for loading article
Smallization strange land share-car quantity and minimum dealer's share-car quantity.The target of multiple target components is carried out to initial schedule scheme
Performance Evaluation, namely the target capabilities for carrying out the maximization useful load of order to initial schedule scheme are assessed, and tote is maximized
The target capabilities of the urgency level of product are assessed, and are minimized the target capabilities assessment of strange land share-car quantity and are minimized dealer and spell
The target capabilities of vehicle quantity are assessed.
It is assessed by the constrained target capabilities for carrying out multiple target parameter to scheduling scheme, multiple target ginsengs can be weighed
Number, and global planning's optimization is carried out to scheduling scheme from multiple target components, improve the efficiency of Logistic Scheduling.
Below by taking complete vehicle logistics are dispatched as an example, each target component is illustrated:
(1) shipped quantity Q is maximizedcapacity。
Wherein, Nv,orderThe Commercial Vehicle quantity concentrated for the order loaded on transport power v；V is transport power set.
(2) it maximizes and loads Commercial Vehicle urgency level.
From on-time-delivery rate (OTD) angle,if ts≤t's；
Wherein, Pri indicates priority, tsFor order s residue sending time, t'sFor the remaining sending time of order s '.
It maximizes and loads Commercial Vehicle urgency level QpriorityIt is accomplished by the following way:
Wherein, OvFor the order collection on transport power v, V is transport power collection, order o, Nv,orderOrder to load on transport power v is concentrated
Commercial Vehicle quantity.
(3) it maximizes and loads large and medium-sized Commercial Vehicle quantity.
The vehicle of Commercial Vehicle is divided into super-huge Commercial Vehicle, special small goods vehicle, large scale commercial product vehicle, medium-sized according to physical size
Commercial Vehicle, small goods vehicle, carrier is to the delivered payload capability of vehicle according to large, medium and small backward compatible, it is contemplated that large scale commercial product vehicle
It is subsequent to will be unable to quickly deliver if there is overstocking, it is therefore desirable to take away large and medium-sized Commercial Vehicle as far as possible in each load.
(4) strange land share-car quantity Q is minimizedmix-location。
When carrying out strange land share-car, cost will increase, therefore to reduce strange land share-car.
Wherein, Nv,o,mix-locationFor strange land city numbers involved in order o on transport power v.
(5) dealer's share-car quantity Q is minimizedmix-dealer。
Wherein, Nv,o,mix-dealerFor the quantity of dealer involved in order o on transport power v.
(6) share-car reservoir area quantity Q is minimizedmix-warehouse。
Wherein, Nv,o,mix-warehouseFor warehouse quantity involved in order o on transport power v.
Step 14, when the initial schedule scheme is not assessed by the target capabilities, to the initial schedule scheme
Rolling optimization is carried out, until the scheduling scheme after optimization is assessed by the target capabilities.
In specific implementation, when carrying out target capabilities assessment to initial schedule scheme, when initial scheduling scheme does not pass through
When the target capabilities are assessed, rolling optimization can be carried out to the initial schedule scheme, until the scheduling scheme after optimization is logical
Cross the target capabilities assessment.
For example, do not assessed after carrying out the 1st rolling optimization to initial schedule scheme, then continued by target capabilities
2nd rolling optimization continues the 3rd rolling if the scheduling scheme of the 2nd rolling optimization is not assessed by target capabilities still
Dynamic optimization, scheduling scheme after the 3rd rolling optimization are assessed by target capabilities, then complete the rolling to initial schedule scheme
Optimization process.
In an embodiment of the present invention, rolling optimization can be carried out to the initial schedule scheme using genetic algorithm.
Step 15, the scheduling scheme assessed by the target capabilities is exported.
In specific implementation, after the scheduling scheme for obtaining meeting target capabilities assessment, it can will meet the Objective
The scheduling scheme output that can be assessed.
By above scheme it is found that initial schedule scheme is obtained according to order data and transport power data, by initial schedule
Scheme carries out target capabilities assessment, the degree of optimization of obtained scheduling scheme is determined, when initial scheduling scheme does not pass through target
When Performance Evaluation, rolling optimization is carried out to the initial schedule scheme, until obtaining after meeting the optimization of target capabilities assessment
Scheduling scheme, and exported as final scheduling scheme.By carrying out constraint condition detection to initial schedule scheme and rolling excellent
Change, the degree of optimization of exported scheduling scheme can be improved, namely realize optimal packing during Logistic Scheduling, so as to
To improve the efficiency of Logistic Scheduling.
Below with reference to the principle of optimality figure of the scheduling scheme given by Fig. 2 based on genetic algorithm, to using genetic algorithm
The detailed process optimized to the initial schedule scheme is described in detail.
Step 21, random fit is carried out to the order data and the transport power data, multiple scheduling schemes is generated, by institute
State multiple scheduling scheme composition first generation scheduling scheme populations.
In specific implementation, each scheduling scheme is the individual in the first generation scheduling scheme population.
Step 22, the fitness of each individual is calculated.
Step 23, judge in the first generation scheduling scheme population with the presence or absence of optimum individual.
In specific implementation, the optimum individual can refer to the individual assessed by target capabilities.
When determining in first generation scheduling scheme population to execute step 24 there are when optimum individual；When judgement first generation scheduling
Optimum individual is not present in scheme population, executes step 25.
Step 24, optimum individual is exported.
In specific implementation, can be optional one from the individual assessed by target capabilities, it, can also as optimum individual
With will by the highest individual optimum individual the most of fitness in individual that target capabilities are assessed, using obtained optimum individual as
Scheduling scheme after the optimization.
Step 25, individual is selected.
In specific implementation, when the fitness of all individuals in the first generation scheduling scheme population is not by described
When target capabilities are assessed, at least two individuals are picked out from the i-th generation scheduling scheme population, i is positive integer.
In an embodiment of the present invention, in order to avoid algorithm falls into local optimum, from the i-th generation tune by the way of roulette
Two individuals are picked out in degree scheme population.When the individual in first generation scheduling scheme population is not assessed by target capabilities,
Individual is carried out from first generation scheduling scheme population to select.When the individual in second generation scheduling scheme population does not pass through target capabilities
When assessment, individual is carried out from second generation scheduling scheme population and is selected.
Step 26, constrained individual intersection operation and mutation operation are carried out to the individual picked out.
In specific implementation, intersection is that two individual inputs are obtained the process of a new individual.That will be picked out
All transport power corresponding with order form a set in body, at this point, some transport power are likely to occur twice.Calculate each transport power
Fitness value.Filter out fitness value be higher than preset threshold transport power, by the transport power higher than preset threshold filtered out according to
Fitness value is ranked up from high to low, is retained since the highest transport power of fitness value, one transport power of every reservation, will be collection
Same transport power removal present in conjunction, and the transport power and its corresponding order that are removed are put into the set being affected.For
All transport power in the set being affected recalculate fitness value, repeat fitness value sequence, threshold decision and screening
Process, until being higher than threshold value there is no fitness value and not retained transport power presence.
Mutation operation can occur the step for retaining fitness value highest transport power before, general with preset one
Rate morphs, and variation shows as the highest transport power of fitness and is not preserved, and the transport power and the corresponding all orders of transport power are direct
Into in the set for needing to plan again.The mode of convergence inspection is to record best individual in every generation scheduling scheme population
Target value, and sliding average is calculated, the judgement convergence when the amplitude of variation of the average value is less than pre-set parameter.
Step 27, i+1 is obtained for scheduling scheme population.
In specific implementation, in the set being affected transport power and order re-start scheduling, and with the fortune that is retained
Power forms new individual, obtains i+1 for scheduling scheme population.
In specific implementation, the product process figure of the first generation scheduling scheme population referring to given by Fig. 3, in step 21
The detailed process for obtaining first generation scheduling scheme population is described in detail.
Step 301, an order is randomly selected from order data.
Step 302, the order being drawn into is matched on corresponding transport power.
Step 303, judge whether be drawn into order and corresponding transport power meet constraint condition.
In specific implementation, when the judgment result is yes, step 304 is executed；When the judgment result is no, step is re-executed
Rapid 302.
Step 304, judge whether order is assigned.
When the judgment result is yes, step 305 is executed；When the judgment result is no, 301 are re-execute the steps.
Step 305, part-load transport power is judged whether there is.
When the judgment result is yes, that is, there is part-load transport power, execute step 306；When the judgment result is no, it executes
Step 307.
Step 306, all orders on discontented carrying power are discharged.
Step 307, judge whether the number of fully loaded transport power is greater than the transport power number after last iteration.
When the judgment result is yes, step 301 is continued to execute；When the judgment result is no, step 308 is executed.
Step 308, scheduling scheme kind population spikes are completed, first generation scheduling scheme population is obtained.
In specific implementation, node data and context data can also be obtained, wherein node data refers mainly to originate
The data information of the intermediate points such as point, terminal and warehouse, contextual data is mainly some requirement descriptions, for example, the demand in warehouse
Description etc..Accessed order data, transport power data, node data and contextual data are cleaned, removal is ordered in vain
Single and invalid transport power retains valid order and effective transport power as accessed order data and transport power data.Invalid order
Refer to that order information is imperfect, for example, the incomplete order of the data such as address is unclear, merchandise news.Invalid transport power refers to and transport power
Relevant information is unclear, such as intention direction it is indefinite, without the incomplete transport power of prestowage capacity data.
By the cleaning to order data, transport power data, the validity of scheduled order and transport power can be improved, reduce
The probability dispatched in vain is generated, so as to improve the efficiency of Logistic Scheduling.
In specific implementation, Logistic Scheduling method provided in an embodiment of the present invention can be used for the Logistic Scheduling of vehicle,
The Logistic Scheduling that can be used for components can be also used for the scheduling of other articles such as Agricultural trade products, and details are not described herein again.
Better understand and realize that the embodiment of the present invention, the embodiment of the present invention also mention for the ease of those skilled in the art
For a kind of Logistic Scheduling device.
Referring to Fig. 4, a kind of structural schematic diagram of Logistic Scheduling device in the embodiment of the present invention is given.The Logistic Scheduling
Device 40 may include: acquiring unit 401, initial schedule schemes generation unit 402, target capabilities assessment unit 403, optimization list
First 404, output unit 405, in which:
The acquiring unit 401 may be adapted to obtain order data and transport power data；
The initial schedule schemes generation unit 402 may be adapted to according to accessed order data and transport power data,
Order and transport power are matched, and determine that matched order meets constraint condition detection with corresponding transport power, is obtained initial
Scheduling scheme；
In specific implementation, the constraint condition comprises at least one of the following: loading constraint, the constraint of intention direction, can spell
City numbers constrain, can spell dealer's number constraint, transport power is constrained using time-constrain, the constraint of transport power access times, share-car, referred to
Determine order to be loaded constraint, reservoir area number constraint, business constraint can be spelled.
The target capabilities assessment unit 403 may be adapted to carry out target capabilities assessment to the initial schedule scheme；
The optimization unit 404 may be adapted to when the initial schedule scheme is not assessed by the target capabilities, right
The initial schedule scheme carries out rolling optimization, until the scheduling scheme after optimization is assessed by the target capabilities；
The output unit 405 may be adapted to export by the scheduling scheme that the target capabilities are assessed.
In an embodiment of the present invention, the optimization unit 404 may be adapted to using genetic algorithm to the initial schedule
Scheme carries out rolling optimization.
In specific implementation, the optimization unit 404 may be adapted to carry out the order data and the transport power data
Random fit generates multiple scheduling schemes, and the multiple scheduling scheme is formed first generation scheduling scheme population, wherein every
A scheduling scheme is the individual in the first generation scheduling scheme population；The fitness for calculating each individual, from passing through
Optional one is stated in the individual of target capabilities assessment, as the scheduling scheme after the optimization.
In specific implementation, the optimization unit 404, may be adapted to will be by fitness in the individual of target capabilities assessment
Highest individual is as the scheduling scheme after the optimization.
In specific implementation, the optimization unit 404 can be adapted to when the institute in the first generation scheduling scheme population
When having the fitness of individual not assess by the target capabilities, at least two are picked out from the i-th generation scheduling scheme population
Individual, i are positive integer；Constrained individual intersection operation and mutation operation are carried out to the individual picked out, obtain i+1 generation
Scheduling scheme population；Fitness calculating is carried out for the individual in scheduling scheme population to the i+1, and is calculated according to fitness
As a result target capabilities assessment is carried out；When mesh is not satisfied for the fitness of all individuals in scheduling scheme population in the i+1
When marking Performance Evaluation, continue to carry out crossover operation and mutation operation for the individual in scheduling scheme population to the i+1, until
Obtain the individual for meeting target capabilities assessment.
In specific implementation, the optimization unit 404 may be adapted to all in the individual picked out and order pair
The transport power answered forms a set, calculates the fitness value of each transport power；Filter out the transport power that fitness value is higher than preset threshold；
The transport power higher than preset threshold that will be filtered out is ranked up from high in the end according to fitness value, highest from fitness value
Transport power starts to retain, and removes same transport power present in the set, and the transport power and its corresponding order that are removed are put into
The set being affected；The fitness value of transport power in the set being affected is recalculated, and carries out judgement and the transport power of preset threshold
Screening, until being higher than the preset threshold there is no fitness value and retained transport power exists；To the set being affected
In transport power and order re-start matching, and form new individual with the transport power retained, obtain i+1 for scheduling scheme kind
Group.
In the present invention one is implemented, the optimization unit 404 may be adapted to by the way of roulette from i-th generation
At least two individuals are picked out in scheduling scheme population.
In specific implementation, the optimization unit 404 may be adapted to from the order data to randomly select one and order
It is single, and the order being drawn into is matched on corresponding transport power；Determine that be drawn into order and corresponding transport power meet
The constraint condition；It detects whether that there are part-load transport power, and when there are part-load transport power, discharges described part-load
All orders loaded on transport power, until all transport power for carrying order are fully loaded；Determine that the number of fully loaded transport power is not more than last time
Transport power number after iteration completes kind of a population spikes, obtains the first generation scheduling scheme population.
In specific implementation, the Logistic Scheduling device 40 can also include cleaning unit (Fig. 4 is not shown).The cleaning
Unit is suitable for after obtaining order data and transport power data, is cleaned to the order data to remove invalid order；To institute
Transport power data are stated to be cleaned to remove invalid transport power.
In specific implementation, the target capabilities assessment unit 403 may be adapted to carry out the initial schedule scheme more
The target capabilities of a target component are assessed.
In specific implementation, the target capabilities assessment unit 403 may be adapted to the Objective for determining each target component
Corresponding weight can be assessed；Target capabilities are carried out to each corresponding target component of the initial schedule scheme to comment
Estimate；Corresponding weight is assessed according to the target capabilities of identified each target component, to obtaining the initial schedule side
The target capabilities assessment of the corresponding each target component of case is weighted summation, obtains multiple targets of the initial schedule scheme
The target capabilities of parameter are assessed.
In specific implementation, target component may include following at least one: maximize shipped quantity, maximization loads and refers to
Determine commodity urgency level, maximize to load and specify commodity amount, minimize strange land share-car quantity, minimize dealer's share-car number
Amount minimizes share-car reservoir area quantity.
In specific implementation, the working principle and workflow of the Logistic Scheduling device 40 can be above-mentioned with reference to the present invention
The description of the Logistic Scheduling method provided in any embodiment, details are not described herein again.
The embodiment of the present invention also provides a kind of Logistic Scheduling device, including memory and processor, deposits on the memory
The computer instruction that can be run on the processor is contained, the processor executes this hair when running the computer instruction
The step of Logistic Scheduling method that bright any of the above-described embodiment provides.
The embodiment of the present invention also provides a kind of computer readable storage medium, and computer readable storage medium is non-volatile
Storage medium or non-transitory storage media, are stored thereon with computer instruction, and the computer instruction executes the present invention when running
The step of Logistic Scheduling method that any of the above-described embodiment provides.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of above-described embodiment is can
It is completed with instructing relevant hardware by program, which can be stored in a computer readable storage medium, storage
Medium may include: ROM, RAM, disk or CD etc..
Although present disclosure is as above, present invention is not limited to this.Anyone skilled in the art are not departing from this
It in the spirit and scope of invention, can make various changes or modifications, therefore protection scope of the present invention should be with claim institute
Subject to the range of restriction.
Claims (28)
1. a kind of Logistic Scheduling method characterized by comprising
Obtain order data and transport power data；
According to accessed order data and transport power data, order and transport power are matched, and determine matched order
Meet constraint condition detection with corresponding transport power, obtains initial schedule scheme；
Target capabilities assessment is carried out to the initial schedule scheme；
When the initial schedule scheme is not assessed by the target capabilities, the initial schedule scheme roll excellent
Change, until the scheduling scheme after optimization is assessed by the target capabilities；
The scheduling scheme assessed by the target capabilities is exported.
2. Logistic Scheduling method according to claim 1, which is characterized in that described excellent to initial schedule scheme progress
Change, comprising:
Rolling optimization is carried out to the initial schedule scheme using genetic algorithm.
3. Logistic Scheduling method according to claim 2, which is characterized in that described to use genetic algorithm to the initial tune
Degree scheme carries out rolling optimization, comprising:
Random fit is carried out to the order data and the transport power data, generates multiple scheduling schemes, and by the multiple tune
Degree scheme forms first generation scheduling scheme population, wherein each scheduling scheme is one in the first generation scheduling scheme population
Individual；
The fitness for calculating each individual, optional one from the individual assessed by the target capabilities, as the optimization
Scheduling scheme afterwards.
4. Logistic Scheduling method according to claim 3, which is characterized in that will be fitted in the individual assessed by target capabilities
The highest individual of response is as the scheduling scheme after the optimization.
5. Logistic Scheduling method according to claim 3, which is characterized in that further include:
When the fitness of all individuals in the first generation scheduling scheme population is not assessed by the target capabilities, from
At least two individuals are picked out in i-th generation scheduling scheme population, i is positive integer；
Constrained individual intersection operation and mutation operation are carried out to the individual picked out, obtain i+1 for scheduling scheme kind
Group；
Fitness calculating is carried out for the individual in scheduling scheme population to the i+1, and is carried out according to fitness calculated result
Target capabilities assessment；
When target capabilities assessment is not satisfied for the fitness of all individuals in scheduling scheme population in the i+1, continue
Crossover operation and mutation operation are carried out for the individual in scheduling scheme population to the i+1, until obtaining meeting target capabilities
The individual of assessment.
6. Logistic Scheduling method according to claim 5, which is characterized in that described to be had about to the individual picked out
The individual intersection of beam operates and mutation operation, obtains i+1 for scheduling scheme population, comprising:
Transport power corresponding with order all in the individual picked out are formed into a set, calculate the fitness of each transport power
Value；
Filter out the transport power that fitness value is higher than preset threshold；
The transport power higher than preset threshold that will be filtered out is ranked up, most from fitness value from high in the end according to fitness value
High transport power starts to retain, and removes same transport power present in the set, the transport power and its corresponding order removed
It is put into the set being affected；
The fitness value of transport power in the set being affected is recalculated, and carries out the judgement of preset threshold and the screening of transport power, directly
To the transport power presence for being higher than the preset threshold there is no fitness value and not being retained；
To in the set being affected transport power and order re-start matching, and form new individual with the transport power retained, obtain
I+1 is for scheduling scheme population.
7. Logistic Scheduling method according to claim 5, which is characterized in that described to be chosen from the i-th generation scheduling scheme population
Select at least two individuals, comprising:
At least two individuals are picked out from the i-th generation scheduling scheme population by the way of roulette.
8. Logistic Scheduling method according to claim 3, which is characterized in that described to the accessed order data
And the transport power data carry out random fit, generate multiple scheduling schemes, and the multiple scheduling scheme is formed first generation tune
Degree scheme population, comprising:
An order is randomly selected from the order data, and the order being drawn into is matched on corresponding transport power；
Determine that be drawn into order and corresponding transport power meet the constraint condition；
It detects whether that there are part-load transport power, and when there are part-load transport power, discharges and filled on the part-load transport power
All orders carried, until all transport power for carrying order are fully loaded；
Determine that the number of fully loaded transport power no more than the transport power number after last iteration, completes kind of a population spikes, obtains the first generation
Scheduling scheme population.
9. Logistic Scheduling method according to claim 1, which is characterized in that after obtaining order data and transport power data,
Further include:
The order data is cleaned to remove invalid order；
The transport power data are cleaned to remove invalid transport power.
10. Logistic Scheduling method according to claim 1, which is characterized in that described to be carried out to the initial schedule scheme
Target capabilities assessment, comprising:
The target capabilities assessment of multiple target components is carried out to the initial schedule scheme.
11. Logistic Scheduling method according to claim 10, which is characterized in that described to be carried out to the initial schedule scheme
The target capabilities of multiple target components are assessed, comprising:
Determine that the target capabilities of each target component assess corresponding weight；
Target capabilities assessment is carried out to each corresponding target component of the initial schedule scheme；
Corresponding weight is assessed according to the target capabilities of identified each target component, to obtaining the initial schedule side
The target capabilities assessment of the corresponding each target component of case is weighted summation, obtains multiple targets of the initial schedule scheme
The target capabilities of parameter are assessed.
12. Logistic Scheduling method according to claim 11, which is characterized in that the target component includes following at least one
Kind:
Shipped quantity, the specified commodity urgency level of maximization loading are maximized, maximizes to load and specifies commodity amount, minimum different
Share-car quantity in ground minimizes dealer's share-car quantity, minimizes share-car reservoir area quantity.
13. Logistic Scheduling method according to claim 1, which is characterized in that the constraint condition includes following at least one
Kind:
Load constraint, intention direction constrains, can spell city numbers constraint, can spell dealer's number constraint, transport power uses the time about
Beam, transport power access times constrain, share-car constrains, specified order is loaded constraint,
Reservoir area number constraint, business constraint can be spelled.
14. a kind of Logistic Scheduling device characterized by comprising
Acquiring unit is suitable for obtaining order data and transport power data；
Initial schedule schemes generation unit, suitable for according to accessed order data and transport power data, to order and transport power into
Row matching, and determine that matched order meets constraint condition detection with corresponding transport power, obtain initial schedule scheme；
Target capabilities assessment unit is suitable for carrying out target capabilities assessment to the initial schedule scheme；
Optimize unit, suitable for when the initial schedule scheme not by the target capabilities assess when, to the initial schedule side
Case carries out rolling optimization, until the scheduling scheme after optimization is assessed by the target capabilities；
Output unit, suitable for that will be exported by the scheduling scheme that the target capabilities are assessed.
15. Logistic Scheduling device according to claim 14, which is characterized in that the optimization unit is suitable for using heredity
Algorithm carries out rolling optimization to the initial schedule scheme.
16. Logistic Scheduling device according to claim 15, which is characterized in that the optimization unit, suitable for being ordered to described
Forms data and the transport power data carry out random fit, generate multiple scheduling schemes, and by the multiple scheduling scheme composition the
Generation scheduling scheme population, wherein each scheduling scheme is the individual in the first generation scheduling scheme population；It calculates every
The fitness of individual, optional one from the individual assessed by the target capabilities, as the dispatching party after the optimization
Case.
17. Logistic Scheduling device described in claim 16, which is characterized in that the optimization unit, suitable for Objective will be passed through
The highest individual of fitness is as the scheduling scheme after the optimization in the individual that can be assessed.
18. Logistic Scheduling device according to claim 16, which is characterized in that the optimization unit is further adapted for when described
When the fitness of all individuals in first generation scheduling scheme population is not assessed by the target capabilities, dispatched from the i-th generation
At least two individuals are picked out in scheme population, i is positive integer；Constrained individual intersection behaviour is carried out to the individual picked out
Work and mutation operation, obtain i+1 for scheduling scheme population；The i+1 is fitted for the individual in scheduling scheme population
Response calculates, and carries out target capabilities assessment according to fitness calculated result；When the i+1 is for the institute in scheduling scheme population
Have individual fitness be not satisfied target capabilities assessment when, continue to the i+1 in scheduling scheme population individual into
Row crossover operation and mutation operation, until obtaining the individual for meeting target capabilities assessment.
19. Logistic Scheduling device according to claim 18, which is characterized in that the optimization unit, suitable for being chosen described
All transport power corresponding with order form a set in the individual selected, and calculate the fitness value of each transport power；It filters out suitable
Angle value is answered to be higher than the transport power of preset threshold；The transport power higher than preset threshold that will be filtered out, from high in the end according to fitness value
It is ranked up, retains since the highest transport power of fitness value, and remove same transport power present in the set, being removed
Transport power and its corresponding order be put into the set being affected；The fitness value of transport power in the set being affected is recalculated, and
The judgement of preset threshold and the screening of transport power are carried out, until there is no fitness values to be higher than the preset threshold and retained
Transport power exists；To in the set being affected transport power and order re-start matching, and form new individual with the transport power retained,
I+1 is obtained for scheduling scheme population.
20. Logistic Scheduling device according to claim 18, which is characterized in that the optimization unit is suitable for using wheel disc
The mode of gambling picks out at least two individuals from the i-th generation scheduling scheme population.
21. Logistic Scheduling device according to claim 16, which is characterized in that the optimization unit, suitable for being ordered from described
An order is randomly selected in forms data, and the order being drawn into is matched on corresponding transport power；What determination was drawn into
Order and corresponding transport power meet the constraint condition；Detect whether that there are part-load transport power, and when there are part-load
When transport power, all orders loaded on the part-load transport power are discharged, until all transport power for carrying order are fully loaded；It determines full
The number of carrying power is not more than the transport power number after last iteration, completes kind of a population spikes, obtains the first generation scheduling scheme kind
Group.
22. Logistic Scheduling device according to claim 14, which is characterized in that further include: cleaning unit, suitable for obtaining
After order data and transport power data, the order data is cleaned to remove invalid order；The transport power data are carried out
Cleaning is to remove invalid transport power.
23. Logistic Scheduling device according to claim 14, which is characterized in that the target capabilities assessment unit is suitable for
The target capabilities assessment of multiple target components is carried out to the initial schedule scheme.
24. Logistic Scheduling device according to claim 23, which is characterized in that the target capabilities assessment unit is suitable for
Determine that the target capabilities of each target component assess corresponding weight；
Target capabilities assessment is carried out to each corresponding target component of the initial schedule scheme；According to identified each
The target capabilities of target component assess corresponding weight, to obtaining the corresponding each target component of the initial schedule scheme
Target capabilities assessment be weighted summation, obtain multiple target components of the initial schedule scheme target capabilities assess.
25. Logistic Scheduling device according to claim 24, which is characterized in that target component comprises at least one of the following:
Shipped quantity, the specified commodity urgency level of maximization loading are maximized, maximizes to load and specifies commodity amount, minimum different
Share-car quantity in ground minimizes dealer's share-car quantity, minimizes share-car reservoir area quantity.
26. Logistic Scheduling device according to claim 14, which is characterized in that the constraint condition includes following at least one
Kind:
Load constraint, intention direction constrains, can spell city numbers constraint, can spell dealer's number constraint, transport power uses the time about
Beam, the constraint of transport power access times, share-car constraint, specified order are loaded constraint, can spell reservoir area number constraint, business constraint.
27. a kind of Logistic Scheduling device, including memory and processor, being stored on the memory can be in the processor
The computer instruction of upper operation, which is characterized in that perform claim requires 1 to 14 when the processor runs the computer instruction
The step of described in any item Logistic Scheduling methods.
28. a kind of computer readable storage medium, is stored thereon with computer instruction, which is characterized in that the computer instruction
Perform claim requires the step of 1 to 14 described in any item Logistic Scheduling methods when operation.
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