CN108346025A - Wisdom logistics computational methods based on cloud - Google Patents
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Abstract
The present invention provides a kind of wisdom logistics computational methods based on cloud, this method includes：The multiple robot terminals being arranged in multiple robots are formed into the Intelligent assembly system based on Internet of Things, minimal path or most fast route planning travelling route are pressed according to the setting terminal of current robot, the robot terminal controls robot according to the parts product information in all parts RF tags to be transported, is transported parts to assembly shop from parts warehouse according to determining route information and parts product information.The present invention proposes a kind of wisdom logistics computational methods based on cloud, and the transport realized in single transportational process is reversible and customizable, reduces logistics cost.
Description
Technical field
The present invention relates to Internet of Things, more particularly to a kind of wisdom logistics computational methods based on cloud.
Background technology
With the development of Internet of Things, Intelligent assembly takes shape gradually, and parts warehouse is transported automatically by the robot of supply chain
Defeated route is transported to assembly shop, at present can be tracked and recorded for transit information and components information.But
Still there is the presence of several defects：Either parts warehouse is shipped to assembly shop or assembly shop and is returned to parts storehouse
Library can only be when parts reach parts warehouse or assembly shop step by step if necessary to cancel, then pass through a transportational process
It returns.And during Enterprise Transportation, at least through extra terminal, lead to the repetition on route.It such as needs high preferential
Grade transport then can not adjust product into Mobile state.
Invention content
To solve the problems of above-mentioned prior art, the present invention proposes a kind of wisdom logistics based on cloud calculating side
Method, including：
The multiple robot terminals being arranged in multiple robots are formed into the Intelligent assembly system based on Internet of Things, according to
The setting terminal of current robot presses minimal path or most fast route planning travelling route, and the robot terminal controls robot
According to the parts product information in all parts RF tags to be transported, according to determining route information and parts product
Information transports parts to assembly shop from parts warehouse.
Preferably, the Intelligent assembly system based on Internet of Things further includes assembly shop cloud cluster, and assembly logistics is converged
Group and parts warehouse cloud cluster, wherein
Each assembly shop cloud cluster is deposited including assembly shop interactive module, assembly shop transmission module and assembly shop
Store up module；Assembly shop interactive module is additionally operable to for inputting assembly shop information to assembly shop information, parts warehouse hair
The information of cloth is shown；Assembly shop transmission module is used for through Industrial Ethernet and assembly logistics cloud cluster or parts storehouse
Library cloud cluster carries out data interaction；Assembly shop memory module is for storing assembly logistics cloud cluster or parts warehouse cloud cluster
The data sent by Industrial Ethernet；
It includes transport end interactive module, transport end transmission module and transport end memory module to assemble logistics cloud cluster；It is described
Transport end interactive module is additionally operable to show the information that transit information, assembly shop are sent for inputting transit information；Fortune
Defeated end transmission module is used to carry out data interaction by Industrial Ethernet and parts warehouse cloud cluster or assembly shop cloud cluster；
Transport end memory module is for storing the number that parts warehouse cloud cluster or assembly shop cloud cluster are sent by Industrial Ethernet
According to；
Parts warehouse cloud cluster includes parts warehouse interactive module, parts warehouse transmission module and parts warehouse
Memory module；Parts warehouse interactive module is additionally operable to send components information, assembly shop for inputting components information
Information shown；Parts warehouse transmission module is used for through Industrial Ethernet and assembly logistics cloud cluster or assembly shop
Cloud cluster carries out data interaction；Parts warehouse memory module is logical for storing assembly logistics cloud cluster or assembly shop cloud cluster
Cross the data packet of Industrial Ethernet transmission.
The present invention compared with prior art, has the following advantages：
The present invention proposes a kind of wisdom logistics computational methods based on cloud, and the transport realized in single transportational process can
It reverses and customizable, reduces logistics cost.
Description of the drawings
Fig. 1 is the flow chart of wisdom logistics computational methods based on cloud according to the ... of the embodiment of the present invention.
Specific implementation mode
Retouching in detail to one or more embodiment of the invention is hereafter provided together with the attached drawing of the diagram principle of the invention
It states.The present invention is described in conjunction with such embodiment, but the present invention is not limited to any embodiments.The scope of the present invention is only by right
Claim limits, and the present invention covers many replacements, modification and equivalent.Illustrate in the following description many details with
Just it provides a thorough understanding of the present invention.These details are provided for exemplary purposes, and without in these details
Some or all details can also realize the present invention according to claims.
An aspect of of the present present invention provides a kind of wisdom logistics computational methods based on cloud.Fig. 1 is implemented according to the present invention
The wisdom logistics computational methods flow chart based on cloud of example.
The Intelligent assembly system based on Internet of Things of the present invention includes assembly shop cloud cluster, assembly logistics cloud cluster and zero
Component warehouse cloud cluster, accesses cloud network.
Each assembly shop cloud cluster is deposited including assembly shop interactive module, assembly shop transmission module and assembly shop
Store up module；Assembly shop interactive module is additionally operable to for inputting assembly shop information to assembly shop information, parts warehouse hair
The information of cloth is shown；Assembly shop transmission module is used for through Industrial Ethernet and assembly logistics cloud cluster or parts storehouse
Library cloud cluster carries out data interaction；Assembly shop memory module is for storing assembly logistics cloud cluster or parts warehouse cloud cluster
The data sent by Industrial Ethernet；
It includes transport end interactive module, transport end transmission module and transport end memory module to assemble logistics cloud cluster；It is described
Transport end interactive module is additionally operable to show the information that transit information, assembly shop are sent for inputting transit information；Fortune
Defeated end transmission module is used to carry out data interaction by Industrial Ethernet and parts warehouse cloud cluster or assembly shop cloud cluster；
Transport end memory module is for storing the number that parts warehouse cloud cluster or assembly shop cloud cluster are sent by Industrial Ethernet
According to；
Parts warehouse cloud cluster includes parts warehouse interactive module, parts warehouse transmission module and parts warehouse
Memory module；Parts warehouse interactive module is additionally operable to send components information, assembly shop for inputting components information
Information shown；Parts warehouse transmission module is used for through Industrial Ethernet and assembly logistics cloud cluster or assembly shop
Cloud cluster carries out data interaction；Parts warehouse memory module is logical for storing assembly logistics cloud cluster or assembly shop cloud cluster
Cross the data packet of Industrial Ethernet transmission；
The Intelligent assembly system based on Internet of Things further includes multiple robot terminals；Multiple robot terminals are set respectively
It sets in multiple robots, each robot terminal includes onboard control module, locating module, robot terminal transmission mould
Block, robot terminal interactive module and robot terminal memory module；Robot terminal transmission module is for wirelessly
Access industrial Ethernet, and data interaction is carried out by Industrial Ethernet and assembly logistics cloud cluster；Robot terminal interacts mould
Block is additionally operable to for inputting robot terminal response message to being shown from the information of assembly logistics cloud cluster；Robot
Terminal storage module is used to store the information from assembly logistics cloud cluster；Locating module is used to acquire the positioning of robot terminal
Information；Onboard control module is used for being handled from the information of assembly logistics cloud cluster, and issues robot terminal interaction
Module is shown；It is additionally operable to robot terminal response message issuing assembly logistics cloud cluster.
Assembly logistics cloud cluster further includes RF tag generation module, route planning module, destination determining module, loads
Computing module, robot tracing module and delivery-scheduling module；The RF tag generation module is for recording each package body
Information, parts product information is generated and label and is attached on package body；By parts product information with RF tag
Form is sent to route planning module and destination determining module；
Route planning module is used to press minimal path according to the setting terminal of current robot or most fast route planning is advanced
Route, and travelling route table is generated, it is sent to destination determining module；Destination determining module is used for according to all to be transported zero
Parts product information in component RF tag presses destination, corresponding travelling route table select destination and travelling route it
Between distance be d parts；Wherein d be less than destination with setting terminal between at a distance from；
Calculation of loading module is used for right by way of sequence by advancing according to travelling route and the parts product chosen
Parts are ranked up, and are generated and are loaded list；Robot tracing module be used for the robot localization information in transportational process into
Row positioning, and the real-time display in map in real time；Delivery-scheduling module is used in transportational process according to assembly shop demand or fortune
Defeated demand for services carries out Real-Time Scheduling to robot or transport product；It is additionally operable to adjust the uninstall process in travelling route
Degree.
The present invention before loading first classifies to parts, is then planned according still further to the distribution of these parts products
Suitable route；After sorting, it will be drawn by way of sequence to being loaded into professional etiquette.In order to find suitable machine in transportational process
People carries out product transhipment, needs that the product of loading is described, to realize that product is retracted and unloaded in real time.
For having according to the method that assembly shop demand or demand for services carry out Real-Time Scheduling to robot in transportational process
Body is：
Step 1: will assembly demand input assembly shop cloud cluster or parts warehouse cloud cluster, assembly shop cloud at this time
Cluster or parts warehouse cloud cluster are as masters；
Step 2: sending demand information to assembly logistics cloud cluster, the demand information includes operation ID and request content；
Step 3: converging pocket transmission authentication instruction, such as authentication to assembly shop cloud cluster or parts warehouse
Failure, then terminate the secondary scheduling；If be proved to be successful, four are thened follow the steps；
Step 4: assembly logistics cloud cluster judges the type of demand information content, refer to when retracting operation for parts, then
Execute step 5；
Step 5: according to the operation ID in the demand information, and inquire operation ID in transport end memory module and correspond to
Planning travelling route product RF tag corresponding with operation ID；
Step 6: inquiry is identical as the planning travelling route in transport end memory module, and the machine that direction of travel is opposite
Device people is as the first candidate collection of bots；Assemble the logistics cloud cluster is calculated and obtained according to location information first candidate machine
The distance between people's set, and according to distance-taxis；
Step 7: the package body information and self ID in RF tag described in assembly logistics cloud cluster extraction step five are beaten
It is bundled into and retracts request data package, and the candidate collection of bots publication of all first respectively into step 6；
Step 8: after the robot terminal of each first candidate collection of bots receives the information, self residual sky is judged
Between whether can accommodate the package body, and whether remaining load-carrying is more than the weight of the package body, if it is judged that be it is yes, then to
Confirmation signal is retracted in assembly logistics cloud cluster reply；If it is judged that being no, then terminate；
Step 9: assembly logistics cloud cluster retracts confirmation signal according to what is received, according to the distance of step 6 sequence, determine
Priority；
Step 10: according to the priority that step 9 determines, judge between current robot and the first candidate collection of bots
Travelling route whether there is available unloading position；If it is judged that being yes, these first candidate collection of bots are denoted as
Second candidate collection of bots, thens follow the steps 11；If it is judged that being no, then terminate；
Step 11: in the second candidate collection of bots, for each first candidate robot, the current machine of selected distance
The available unloading position of the distance between device people and the first candidate collection of bots difference minimum is as optimal available unloading position；
Step 12: choose in the second candidate collection of bots, optimal available unloading position is apart from current robot and the
The candidate collection of bots of minimum corresponding second of the distance between two candidate collection of bots difference, is waited as final first
Select collection of bots；
Step 13: all first candidate collection of bots publications of the assembly logistics cloud cluster into step 6 are chosen most
First candidate collection of bots eventually；And send selected optimal available unloading position to the final first candidate collection of bots；
Step 14: after completing product handing-over, the final first candidate collection of bots has been sent to assembly logistics cloud cluster
At information, end once retracts operation.
Wherein, in step 4, the type of demand information content is judged when for high priority operation, then executes following step
Suddenly：
Step A1, assembly logistics cloud cluster is according to the operation ID in the demand information, and is looked into transport end memory module
Ask the corresponding planning travelling routes of operation ID RF tag corresponding with operation ID；
Step A2, assembly logistics cloud cluster is inquired and the planning travelling route of current robot in transport end memory module
Identical, direction of travel is identical and robot positioned at current robot rear, as third candidate robot；
Step A3, for current robot and all third candidates robot, the average speed of its own is calculated separately, and
The time reached home is chosen earlier than the robot for the time that current robot is reached home as the 4th candidate collection of bots；
And by the arrival time of the 4th candidate collection of bots by being ranked up sooner or later；
Step A4, the time that assembly logistics cloud cluster arranges in the requirement arrival time in information and step A3 according to demand
It is compared, deletion is later than requirement arrival time corresponding robot, using remaining candidate robot as the 4th candidate machine
People gathers；And by the arrival time of the 4th candidate collection of bots by being ranked up sooner or later；
Step A5, judge whether the quantity of the 4th candidate collection of bots is 0, if it is judged that being no, then executes step
Rapid A6；
Step A6, the information and self ID of the package body in assembly logistics cloud cluster extraction RF tag are packaged into high preferential
Grade request data package, and all four candidate collection of bots publications respectively into step A4；
Step A7, after each robot terminal of the 4th candidate collection of bots receives the information, judge self residual sky
Between whether can accommodate the package body and whether remaining load-carrying is more than the weight of the package body, if it is judged that be it is yes, then to
It assembles logistics cloud cluster and replys high priority answer signal；If it is judged that being no, then terminate；
Step A8, assembly logistics cloud cluster is candidate according to the 4th of step A4 the according to the high priority answer signal received
The arrival time of collection of bots by being ranked up sooner or later, determines priority；
Step A9, the priority determined according to step A8 judges between current robot and the 4th candidate collection of bots
Travelling route whether there is available unloading position；Between selected distance current robot and the 4th candidate collection of bots away from
The available unloading position of deviation value minimum is as optimal available unloading position；
Step A10, optimal available unloading position is chosen between current robot and the 4th candidate collection of bots
The corresponding robot of distance difference minimum, as final candidate robot；
Step A11, the final candidate machine that assembly logistics cloud cluster is chosen to all four candidate collection of bots publications
People；And selected optimal available unloading position is sent to final candidate robot, indicate that final candidate robot will correspond to radio frequency
Package body in label is transported to optimal available unloading position.
The route planning module and calculation of loading module of the assembly logistics cloud cluster, further according to the road pre-established
Line model obtains the best route of two intersites, the package body set for meeting constraints is filtered out, according under best route
The transport ratio for having transported ratio calculation package body set of parts to be transported, to calculate logistics cost, and by logistics at
Originally the transport ratio of package body set is adjusted as value of feedback the difference between preset cost threshold value, final
To optimal packing and traffic program, include the following steps：
B1 obtains the best route of two intersites according to the route model pre-established, according to the best route meter
Calculate the traveling cost between the corresponding workshop in described two places；
Wherein, the route model is using each workshop as place, with connect the distance of road in two workshops it is corresponding at
This function is established for route weights, and the cost function is for characterizing the cost generated on the route.
After establishing route model, the route weights are corrected according to the real time information of each route.In school
After positive weights, origin and destination are selected from the place of the route model, is selected from the route after correction
It is connected to the route of total weight value minimum in the origin and the route of destination, and the route of total weight value minimum is set
For the best route between the origin and destination.Wherein, the weights can be the weights of regularization.
After obtaining best route, the traveling cost between described two places can be calculated according to the best route.
B2 generates all parts to be transported by most M kinds types to the parts to be transported of given N kind types
First package body set of composition, filters out the package body constraints for meeting robot from the first package body set
Second package body set；Wherein, M is less than or equal to N；
For each combination variety, traverses each robot and can load to generate in the case of amount of parts and be possible to
Combination, according to zero to be transported of the number of species and each type of parts to be transported in the first package body set
The weight of part calculates the total weight of the first package body set, if the total weight is more than the loading capacity of the robot, deletes
Except corresponding first package body set, not deleted first package body set is set as to meet the third packet of loading capacity constraints
Body set is filled, to filter out the combination for meeting load-carrying constraints.Further according in the second package body set to be transported zero
The size of the parts to be transported of the number of species of component and each type calculates the overall size of the second package body set,
The overall size is compared with the size of the robot, if the overall size is more than the size of the robot, is deleted
Not deleted second package body set is set as meeting the package body collection of size constraint by corresponding second package body set
It closes, to filter out the combination for meeting size constraint.
B3 estimates the best road according to the ratio of transport of various parts to be transported under the best route
The transport ratio of each package body set under line, according to the synthesis useful load described in the transport ratio calculation under best route,
The logistics cost between workshop is corresponded to according to the comprehensive useful load and traveling cost calculation；
In this step, transport ratio Φ is calculated according to following formula：
In formula, K is the total quantity of parts to be transported, and M is the species number of parts to be transported in package body set, xiFor
The lower i-th kind of parts to be transported of best route, aiFor the quantity of i-th kind of parts to be transported in package body set, P (xi)
For xiTransport ratio, 1≤i≤M.
Then comprehensive useful load is calculated according to following formula
In formula, mjFor total useful load of j-th of package body set under the best route, ΦjIt is under the best route
The transport ratio of j package body set.
Finally, in the manner described above calculated comprehensive useful load and traveling cost calculation correspond to the logistics between workshop at
This.Avoid because human factor is affected reduce counting accuracy the problem of.
B4, if the logistics cost is more than preset cost threshold value, calculate the logistics cost and the cost threshold value it
Between difference, adjust the transport ratio of each package body set according to the difference, and return according to the transport ratio calculation
The step of synthesis useful load under the best route；
In this step, using the difference of calculated logistics cost in step B3 and preset cost threshold value as feedback
Value for adjusting the transport ratio of each package body set, and repeats the process of the adjustment, until the logistics cost is less than institute
State preset cost threshold value.
B5 is constrained if the logistics cost is less than the preset cost threshold value according to the best route and package body
Transport ratio after condition and adjustment determines traffic program.
Wherein, after transporting ratio according to the iteration adjustment of step B4, when logistics cost is less than the preset cost threshold
When value, determines that transport ratio at this time is optimal transport ratio, considered transit route and constraint conditional combination, effectively dropped
Low logistics cost.
The delivery-scheduling module of the assembly logistics cloud cluster, using parts assembly assembly sequence as decision-making foundation, base
It by operation fractionation, jobs scheduling, services selection and is combined and result preferably four part groups in the logistics service problem of assembling process
At formalized description is as follows：
C1. assembly logistics cloud cluster first splits assembling work, obtains a series of subjobs, and determines that assembly is made
The assembling process of industry, MT={ ST1, ST2..., STi..., STn}+Constraint.Best subjob assembly sequence is according to dress
Requirement with process is determined in conjunction with the Service Source of dynamic change.Therefore, subjob sequence { ST1, ST2..., STi...,
STnSubscript i only indicate subjob number, it is unrelated with assembly sequence；Constraint is the pact for realizing assembling process demand
Beam,
In formula：Matrix exponent number n is equal to subjob quantity；CijIndicate subjob STiWith subjob STjBetween assembly sequence
Demand, if STi<STjThen Cij=1, if STi>STjThen Cij=-1, if STiWith STjBetween without assembly sequence requirement, Cij=0.
C2. assembly logistics cloud cluster generates subjob assembly sequence PS (ST at random1 p1, ST2 p2..., STi pi..., STn pn),
And carry out Services Composition under the conditions of different assembly sequences.Then assembling process verification is carried out, and changes and is unsatisfactory for requirement
Assembly sequence obtains executable assembly sequence, i.e. EPS (ST1 e1, ST2 e2..., STi ei..., STn en), wherein eiIndicate that son is made
Industry is numbered, and i indicates subjob assembly sequence number.
C3. assembly logistics cloud cluster respectively selects one from meeting in the candidate parts warehouse cloud cluster that each subjob requires
A logistics service, and according to corresponding executable assembly sequence by the Service Assembly chosen at stream composition stream service, obtain
Candidate assembling scheme CPR (ST1 e1,s1, ST2 e2,s2..., STi ei,si..., STn en,sn), wherein siIt indicates to execute subjob STei's
Candidate logistics service-number, sequence (s1, s2..., sn) indicate that is serviced in stream composition stream service executes sequence.Different
Subjob can select identical logistics service, i.e. siRepetition values, m can be taken to indicate candidate logistics service number in section [1, m]
Amount.STi ei,siIt indicates in candidate assembling scheme CPR, i-th of subjob being performed is STei, and by siA parts storehouse
Library provides service.
C4. according to selected objective target, the point value of evaluation of different candidate assembling schemes is calculated, selects the optimal candidate assembly of result
Scheme.The selected objective target includes：Time is most short, cost is minimum and stability highest.
Assembling work information is expressed as：
MT (L, N, W, DL, TC, R).
In formula：L indicates the location of assembly shop；N indicates the amount of parts of job requirements assembly；W indicates to be installed
The parts quality matched；DL indicates that duration is completed in acceptable operation；TC indicates acceptable tip heigh；R is indicated to all
The minimum stability requirement of candidate logistics service.
Parts warehouse information is expressed as：SP (L, R) ＆ (C, T).
In formula：(L, R) indicates the Global Information in parts warehouse；(C, T) indicates the components information in parts warehouse；L
Indicate parts warehouse position；R indicates the stability point value of evaluation in parts warehouse, is the value on section [0,1]
Evaluation index；C indicates the available assembly cost of serving in warehouse；The time required to T indicates that different work is completed in parts warehouse.It is right
The service quality in parts warehouse will calculate the point value of evaluation of time and cost first with weight coefficient when being calculated, then
Multiplied by with stability.Parts warehouse siComplete subjob eiWhen service quality calculation formula it is as follows：
QosEi, si=Rsi×(wT·TMi, si+wC·CMi, si)
In formula：RsiIt is siThe stability point value of evaluation in a parts warehouse；TMi, si、CMi, siIt is s respectivelyiA parts
Complete m in warehouseiTime needed for a subjob and cost；wT、wCIt is the weight coefficient of time and cost, w respectivelyC+wT=1.
When combining one assembling work of completion of logistics service collaboration, due to the incomplete phase in position in each parts warehouse
Together, with the progress of operation, shipping expense will be generated.To simplify the calculation, it is assumed that in combination logistics service, complete first son and make
The parts warehouse of industry provides parts, and position is shipping point of origin；Transportation terminal is assembly shop present position.It is filled by candidate
With scheme CPR it is found that i-th of place on transit route is siThe location of a parts warehouse, on this place
That be performed is eiA subjob.
Evaluation to candidate assembling scheme includes two parts of service quality and shipping expense in parts warehouse.Therefore,
The Services Composition optimal selection problem for considering time and cost and stability is converted into objective optimization function and is solved：
Wherein, i indicates i-th of place of candidate assembling scheme, and LC and LT are respectively haulage time and transportation cost.
According to the objective optimization function based on assembling process, using ant group algorithm, iteration progress each time is not of the same race twice
The search for the first time of the route search of class, each iteration obtains the executable assembly sequence of subjob according to assembly sequence demand
(e1, e2..., ei..., en)；Binary search is then according to can perform assembly sequence, for the candidate that the selection of each subjob is suitable
Stream service obtains combination logistics service (s1, s2..., si..., sn).The basic procedure of ant group algorithm is further depicted as：
It searches for for the first time and two parts are verified by assembly sequences generation and assembling process constitutes.Assembly sequences generation uses basic ant
Group's algorithm；Assembling process verification includes, and when assembly sequence is unsatisfactory for requiring, enables assembly sequence and exchanges, becoming can hold
Row assembly sequence.All subjobs are checked one by one, and whether check in constraint Constraint has and the relevant assembly sequence of subjob
Row demand is handed over if so, then checking whether position of the subjob in assembly sequence meets assembling process demand if being unsatisfactory for
Change the assembly sequence of two subjobs.
In binary search, the object that parts warehouse is accessed as ant can be repeated selection, inspire variable not only by
It is also related with subjob to be assembled to the influence of position between parts warehouse.Pheromones variable quantity is directly proportional to path length.
If parts warehouse quantity is m, the quantity of ant population is s.
Ant k leaves parts warehouse i in t moment and accesses the probability P of parts warehouse jk I, j(t) pass through following formula meter
It calculates：
Pk I, j(t)=[τα I, j(t)×ηβ I, j(t)]/[ΣS ∈ [1, m]τα I, s(t)×ηβ I, s(t)], [1, m] j ∈.
Wherein ηI, jTo inspire variable, indicates that ant is influenced by distance and leaves parts warehouse i, access parts warehouse j
Probability；τI, jFor the pheromone concentration between parts warehouse i and parts warehouse j, α and β indicate pheromones and inspiration respectively
The relative Link Importance of variable.In binary search, variable is inspired to be influenced by the distance between parts warehouse, also by be assembled
The influence of subjob.
As Services Composition (s1, s2..., si..., sn) in, s(i-1)After representative parts warehouse is determined to, the
s(i-1)Inspiration variable between a parts warehouse and other parts warehouses can be calculate by the following formula：
ηS (i-1), si=[Rsi×(wT·TMi, si+wC·CMi, si)]+wC·LCS (i-1), si+wT·LTS (i-1), si；si∈ [1,
m]。
Pheromone concentration variable quantity in binary search is directly proportional to the path length that ant is passed by, and the pheromones of use are dense
It is as follows to spend variable quantity formula：
If ant k leaves parts warehouse i in t moment to t+n moment, parts warehouse j is accessed, then Δ τk I, j(t,
T+n)=Q*Lk, otherwise Δ τk I, j(t, t+n)=0
Wherein Q is pheromones intensity, LkThe path length passed by current iteration for ant k.
After all ants, which have carried out m times, to be accessed, fresh information element：
τI, j(t+n)=ρ τI, j(t)+ΔτI, j(t, t+n).
In formula：ρ indicates pheromones residual coefficients, ρ<1；ΔτI, j(t, t+n) is from parts warehouse i to parts warehouse j
Route on pheromones variable quantity, i.e.,：
In conclusion the present invention proposes a kind of wisdom logistics computational methods based on cloud, realizes and transported in single
The transport of journey is reversible and customizable, reduces logistics cost.
Obviously, it should be appreciated by those skilled in the art, each module of the above invention or each steps can be with general
Computing system realize that they can be concentrated in single computing system, or be distributed in multiple computing systems and formed
Network on, optionally, they can be realized with the program code that computing system can perform, it is thus possible to they are stored
It is executed within the storage system by computing system.In this way, the present invention is not limited to any specific hardware and softwares to combine.
It should be understood that the above-mentioned specific implementation mode of the present invention is used only for exemplary illustration or explains the present invention's
Principle, but not to limit the present invention.Therefore, that is done without departing from the spirit and scope of the present invention is any
Modification, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.In addition, appended claims purport of the present invention
Covering the whole variations fallen into attached claim scope and boundary or this range and the equivalent form on boundary and is repairing
Change example.
Claims (2)
1. a kind of wisdom logistics computational methods based on cloud, which is characterized in that including：
The multiple robot terminals being arranged in multiple robots are formed into the Intelligent assembly system based on Internet of Things, according to current
The setting terminal of robot presses minimal path or most fast route planning travelling route, robot terminal control robot according to
Parts product information in all parts RF tags to be transported, according to determining route information and parts product information
Parts are transported from parts warehouse to assembly shop.
2. according to the method described in claim 1, it is characterized in that, the Intelligent assembly system based on Internet of Things further includes dress
With workshop cloud cluster, logistics cloud cluster and parts warehouse cloud cluster are assembled, wherein
Each assembly shop cloud cluster includes that assembly shop interactive module, assembly shop transmission module and assembly shop store mould
Block；Assembly shop interactive module is additionally operable to issue assembly shop information, parts warehouse for inputting assembly shop information
Information is shown；Assembly shop transmission module is used for through Industrial Ethernet and assembly logistics cloud cluster or parts warehouse cloud
Cluster carries out data interaction；Assembly shop memory module passes through for storing assembly logistics cloud cluster or parts warehouse cloud cluster
The data that Industrial Ethernet is sent；
It includes transport end interactive module, transport end transmission module and transport end memory module to assemble logistics cloud cluster；The transport
End interactive module is additionally operable to show the information that transit information, assembly shop are sent for inputting transit information；Transport end
Transmission module is used to carry out data interaction by Industrial Ethernet and parts warehouse cloud cluster or assembly shop cloud cluster；Transport
End memory module is for storing the data that parts warehouse cloud cluster or assembly shop cloud cluster are sent by Industrial Ethernet；
Parts warehouse cloud cluster includes parts warehouse interactive module, parts warehouse transmission module and the storage of parts warehouse
Module；Parts warehouse interactive module is additionally operable to the letter sent to components information, assembly shop for inputting components information
Breath is shown；Parts warehouse transmission module is used to converge by Industrial Ethernet and assembly logistics cloud cluster or assembly shop
Group carries out data interaction；Parts warehouse memory module passes through work for storing assembly logistics cloud cluster or assembly shop cloud cluster
The data packet that industrial Ethernet is sent.
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