CN110134985A - The modeling of Multilayer shuttle car system conveyer buffer storage length and optimization method - Google Patents
The modeling of Multilayer shuttle car system conveyer buffer storage length and optimization method Download PDFInfo
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- CN110134985A CN110134985A CN201910238472.3A CN201910238472A CN110134985A CN 110134985 A CN110134985 A CN 110134985A CN 201910238472 A CN201910238472 A CN 201910238472A CN 110134985 A CN110134985 A CN 110134985A
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Abstract
The invention discloses a kind of modeling of Multilayer shuttle car system conveyer buffer storage length and optimization methods, on the basis of analysing in depth to Multilayer shuttle car system Delivery process, establish conveyer caching input and output balance model；In the case where conveyer caching meets sorting operation and operates normally, the optimal conditions and critical condition of the buffer storage length are proposed.Hopper Delivery process is analyzed with Open queuing network modeling method, hopper is established and is averaged outbound time model, and according to hopper Delivery flow distribution and the artificial relationship for sorting efficiency, establishes the Optimized model of conveyer buffer storage length；The library time is averaged out to shorten hopper, storage space is optimized using k-means clustering algorithm and storage area queueing discipline, reduces conveyer buffer storage length.
Description
Technical field
This disclosure relates to a kind of Multilayer shuttle car system conveyer buffer storage length modeling and optimization method.
Background technique
With significantly improving for logistic industry intelligence, automation level, Multilayer shuttle car storage and distribution integrated system is in electricity
Quotient and manufacturing are widely applied.The system is in input work out, to prevent job interruption, improves order and sorts effect
Rate is provided with the conveyer of certain length for caching out the hopper being put in storage in elevator and the artificial switching phase for sorting platform.
Conveyer caching is mainly used for temporary outbound hopper to be selected, reduces the time mutually waited between equipment.
Inventor has found that hopper reaches the speed of conveyer caching by product item storage position and appoints in actual job in the course of the research
The factors such as business scheduling influence, and are a discrete random processes.In this case, if conveyer caching is too long, beyond most
Theoretical buffer memory under big outbound efficiency, then cause equipment that can occupy excessive space, result in waste of resources；If conveyer is slow
Too short, to be unsatisfactory under maximum outbound efficiency theoretical buffer memory is deposited, then when leading to that hopper cannot be replenished in time in the short time, out
Existing shortage of goods phenomenon, influences picking efficiency.It to sum up analyzes, conveyer caches reasonable length mentioning to the picking efficiency of whole system
It is high most important.
Currently, being concentrated mainly on for the research for improving Multilayer shuttle car system (hereinafter referred to as to wear system) picking efficiency more
Storage space optimization and task schedule optimization aspect.The optimization of existing storage space and buffer storage length optimization method is selected to have: (1) to wear more system into
Row modeling optimization method optimizes storage space using ant colony clustering, while optimizing using genetic algorithm to task schedule,
To improve system effect.(2) by cargo Similarity measures, Clustering Model is constructed, and application heuritic approach solves optimal storage
Picking efficiency is improved to balance picking person works amount in position.(3) Multilayer shuttle car warehousing system Task Scheduling Model is proposed,
System effectiveness under parallel picking, serial outbound strategy is studied by genetic algorithm.(4) by research order cluster allocation strategy come
System effectiveness is improved, propose four kinds of improvement K-means clustering algorithms and carries out verifying analysis in conjunction with true order data, to four kinds
Clustering algorithm optimization efficiency is ranked up.(5) SOQN Method Modeling is used, and is solved with edman degradation Edman and analyzes more automatic vehicle tasks
The performance of system under switch instances.(6) buffer storage length that replenishes is sorted in automatic Cigarette Sorting System and carry out modeling optimization, using opening
Hairdo clustering algorithm optimizes product item storage space, shortens the cargo outbound time, to reduce buffer storage length, improves and sorts effect
Rate.
It is still to be solved in conclusion how to optimize the adaptability of conveying equipment size in Multilayer shuttle car system
Technical problem.
Summary of the invention
In order to overcome the above-mentioned deficiencies of the prior art, present disclose provides a kind of Multilayer shuttle car system conveyer cachings to grow
Degree modeling and optimization method establish conveying by caching the detailed analysis of operation process and Multilayer shuttle car system to conveyer
Machine buffer storage length model simultaneously optimizes, and provides theoretical foundation for the rational design of Multilayer shuttle car system.
Technical solution used by the disclosure is:
A kind of Multilayer shuttle car system conveyer buffer storage length modeling method, this method include establishing conveyer caching respectively
Input and output balance model, hopper are averaged outbound time model and conveyer buffer storage length model；Wherein:
The conveyer caches input and output balance model are as follows:
Wherein, β is 0 to any time in the t period；τ is that banked cache section is entered out from first cargo to leaving
The time of banked cache section out；L (t) is the length that t moment pressed density reaches maximum compression density.
The hopper is averaged outbound time model are as follows:
Wherein,For the average latency of shuttle,For the average latency of elevator；Indicate shuttle
The unidirectional horizontal movement time,Indicate that elevator unidirectionally moves vertically the time.
When conveyer caching hopper is less than, it is constantly in undersaturated condition in entire picking transmission process, then conveyer is slow
Deposit length model are as follows:
Wherein, I (β) is the input quantity of conveyer caching, and d (β) is the pressed density that the conveyer at the β moment caches.
When conveyer caching can reach maximal density, then conveyer buffer storage length model are as follows:
The lowest critical value of conveyer buffer storage length are as follows:
Wherein, T0For the average outbound time of an order；λ is order taking responsibility arrival rate；L0Minimum is cached for conveyer to face
Dividing value；vlFor the driving speed of conveyer；μmDistribution function is obeyed for artificial picking speed.
A kind of Multilayer shuttle car system conveyer buffer storage length optimization method, method includes the following steps:
Moment mean difference is completed using product item outbound task, establishes product item correlation matrix；
Product item is clustered using k-means algorithm is improved, forms multiple storage areas；
According to similar storage area permutation and combination principle, the total moment matrix of storage area and storage area correlation matrix are established；
Component item in storage area is ranked up according to outbound amount size, the big product item of outbound amount is deposited in apart from every layer of head
It arranges in nearest storage space, determines the optimal storage space of product item.
Through the above technical solutions, the beneficial effect of the disclosure is:
(1) disclosure conveyed the hopper of conveyer for research object with conveyer caching in Multilayer shuttle car system
Cheng Jinhang analysis, establishes the input and output balance model cached based on conveyer, and proposes that conveyer caching meets sorting operation
Critical condition and optimal conditions and proved.
(2) disclosure establishes Open queuing network, caches input flow rate distribution by analytical calculation conveyer, establishes defeated
Machine buffer storage length model is sent, the planning for Multilayer shuttle car system provides design considerations.
(3) disclosure is in Multilayer shuttle car system, product item stock's allocation be influence hopper outbound speed critical factor it
One, therefore devise k-means algorithm and product item is clustered, determining storage area is obtained, and according to certain principle of optimality pair
Slotting optimization is carried out inside storage area and storage area, the system outbound time is reduced, so as to shorten conveyer buffer storage length.
(4) the storage space optimization method based on k-means that the disclosure proposes can reduce conveyer buffer storage length 12% or so,
To demonstrate the feasibility of conveyer buffer storage length model and the superiority of product item distribution optimization method.
Detailed description of the invention
The Figure of description for constituting a part of this disclosure is used to provide further understanding of the disclosure, and the disclosure is shown
Meaning property embodiment and its explanation do not constitute the improper restriction to the disclosure for explaining the application.
Fig. 1 is the Multilayer shuttle car system job model schematic according to one or more embodiments；
Fig. 2 is the different conveyer buffer storage length schematic diagrames according to one or more embodiments；
Fig. 3 is the Multilayer shuttle car system conveyer buffer storage length modeling method process according to one or more embodiments
Figure；
Fig. 4 is to cache input and output schematic diagram according to the conveyer of one or more embodiments；
Fig. 5 is that do not occur the overstocked phenomenon schematic diagram of cargo in output end according to one or more embodiments；
Fig. 6 is the Multilayer shuttle car system Delivery flow diagram according to one or more embodiments；
Fig. 7 is schemed according to the Multilayer shuttle car system open loop queueing network of one or more embodiments；
Fig. 8 is the equipment moving curve graph according to one or more embodiments；
Fig. 9 is the Multilayer shuttle car system conveyer buffer storage length optimization method process according to one or more embodiments
Figure.
Figure 10 is to change over time figure according to three conveying buffer storage lengths of one or more embodiments.
Specific embodiment
The disclosure is described further with embodiment with reference to the accompanying drawing.
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the disclosure.Unless another
It indicates, all technical and scientific terms that the disclosure uses have logical with disclosure person of an ordinary skill in the technical field
The identical meanings understood.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
One or more embodiments provide a kind of Multilayer shuttle car system conveyer buffer storage length modeling method and optimization side
Method, for improve Multilayer shuttle car system work efficiency, reduce conveying equipment input cost, to Multilayer shuttle car system outbound
On the basis of work flow is analysed in depth, conveyer caching input and output balance model is established；It caches and meets in conveyer
In the case that sorting operation operates normally, the optimal conditions and critical condition of the buffer storage length are proposed.With Open queuing network
Modeling method analyzes hopper Delivery process, establishes hopper and is averaged outbound time model, and is made according to hopper outbound
Industry flow distribution and the artificial relationship for sorting efficiency, establish the Optimized model of conveyer buffer storage length；It is averaged out to shorten hopper
The library time optimizes storage space using k-means clustering algorithm and storage area queueing discipline, further decreases conveyer buffer storage length.
Simulation result shows that the product item after optimization distributes compared with being randomly assigned, and the buffer storage length that replenishes reduces about 12%.
In Multilayer shuttle car system, then every layer of access and horizontal transport by shuttle progress hopper is transferred to
Elevator, then hopper vertical transport is carried out by elevator, it is finally handed off to conveyer input terminal, hopper is transported people by conveyer
Work picking platform is sorted, as shown in Figure 1.In Multilayer shuttle car system, the parallel picking of shuttle is serially transported with elevator
Defeated efficient cooperation improves the picking efficiency of whole system.
More wear system carry out Delivery when, order radio frequency answer precise and high efficiency by hopper outbound, for manually picking
Choosing.It is interrupted to prevent from sorting, applies conveyer caching and keep in hopper to be selected.Due to the distribution of, storage space and task schedule
It influences, after outbound task is assigned, can have equipment room waiting during shuttle and elevator cooperation conveying hopper, so material
The process that case reaches conveyer entrance is a discrete random process.It is random that the time of conveyer caching is reached in hopper
In the case of, it will appear following three kinds of problems if the design of conveyer buffer storage length is unreasonable, as shown in Figure 2.
If conveyer buffer storage length is too short, it will appear and replenish not in time, cause picking personnel idle, reduce picking effect
Rate, in Fig. 2 shown in (a).If conveyer buffer storage length is too long, it will appear the discontented situation of conveyer caching, from cost
Investment and space utilization angle are seen, the waste of equipment investment and space resources is caused, in Fig. 2 shown in (b).If set on software
Fixed theoretical buffer memory is greater than the practical amount of storage of caching, that is, caches in the saturated condition, still issues and wears system outbound instruction more,
Then since artificial busy and conveyer caching is without vacancy, elevator is caused to occupy, hopper cannot join in time, and outbound occurs and appoints
The case where business blocking, in Fig. 2 shown in (c), so that reducing system sorts efficiency.
In conclusion hopper reaches the speed of conveyer caching, the length of conveyer caching (or number of packages of storage hopper)
It plays an important role to the normal operation of artificial picking operation.The setting of theoretical buffer memory must be cached with conveyer actually can amount of storage
It is consistent, to ensure under the situation for meeting each picking platform normal operation, elevator normally joins with conveyer, does not influence
The normal Delivery of other hoppers improves the entire sorting efficiency for wearing system more.
Please refer to attached drawing 3, the Multilayer shuttle car system conveyer buffer storage length modeling method that the present embodiment proposes include with
Lower step:
S101 analyses in depth Multilayer shuttle car system picking operation process, establishes conveyer caching input and output
Balance model, and provide the optimal conditions and critical condition of buffer storage length.
S101-1 analyses in depth Multilayer shuttle car system picking operation process, and it is defeated to establish conveyer caching input
Balance model out.
In the present embodiment, the Delivery for only considering hopper, it is defeated for the single conveying equipment that replenishes for sorting platform
It is as shown in Figure 4 to enter output.Input is the process that hopper enters that conveyer is cached from elevator, if input flow rate is I (t)；Assuming that
The case where not considering back library obstruction, exports the process for being chosen for hopper and finishing Hui Ku, if output flow is O (t), if practical defeated
The driving speed for sending machine is vl, length L.The sorting of hopper is influenced by the artificial speed that sorts, and is a discrete random mistake
Journey, if manually sorting speed obeys distribution function φ (t).
It can be concluded that is, under the situation of-O (t) > 0 I (t), hopper is from conveying when input flow rate is greater than output flow
Machine output end starts to generate extruding, it is assumed that the maximal density of hopper compression is dmax.Indicate that t moment pressed density reaches with l (t)
dmaxLength, the pressed density d of the frontl(t) it indicates.
According to conveying operation process of the hopper on conveyer caching it is found that the reality output flow of conveyer can indicate
Are as follows:
O (t)=min (φ (t), vl×d0(t)) (1)
Wherein, φ (t) is that the artificial speed that sorts obeys distribution function；vlFor the driving speed of conveyer；d0It (t) is not reach
General pressed density when to maximum compression density.
By conveyer cache in hopper density dl(t) it is expressed as follows:
Wherein, I (t) is the input flow rate of Multilayer shuttle car system；O (t) is the output flow of Multilayer shuttle car system；vl
For the driving speed of conveyer；L is the length of conveyer；dmaxFor the maximal density of hopper compression.
Since during normal hopper sorting operation, the input and output of conveyer caching are in equilibrium state, then
Conveyer caching input and output balance model is as follows out:
Wherein, β is 0 to any time in the t period；τ is that banked cache section is entered out from first cargo to leaving
The time of banked cache section out；L (t) is that t moment pressed density reaches dmaxLength.
S101-2 provides the optimal item of buffer storage length in the case where conveyer caching meets sorting operation and operates normally
Part and critical condition.
The operation process of conveyer caching is counted since first time input flow rate is greater than zero, is ended at all hoppers and is picked
Choosing completion, if entire conveying caching period activity duration is T, in the present embodiment, discussion analysis τ≤t≤in the T- τ period
Operation process.
In the operation process of conveyer caching, the optimal conditions and critical condition of the buffer storage length provided are as follows:
(1) assume hopper length be ω, conveying be buffered in any τ≤t≤T- τ moment, be manually in idle condition and
When φ (t) > 0, the optimal conditions for meeting sorting operation is l (t)=ω.
As φ (t)>0, indicate that sorting platform has picking demand, if l (t)<ω, then it represents that do not occur cargo in output end
Phenomenon is overstock, as shown in Figure 5.
It is analyzed for the hopper K1 on conveyer, K1 is in t- τ+a/vlMoment enters conveyer, and a indicates cargo distance
The distance of picking personnel, indicates picking demand as φ (t) > 0, and O (t+a/vl)=0, therefore in a/vlIn period, people
Work is in idle condition, and picking stops carrying out.
(2) at t (τ < t≤T) moment, the critical condition that sorting personnel continuously sort is d0(t)≥φ(t)/vl。
Assuming that working as d0(t)<φ(t)/vlWhen, sorting work can be carried out continuously, i.e. d0(t)×vl< φ (t), by formula O (t)=
min(φ(t),vl×d0(t)) it is found that O (t)=vl×d0(t), i.e. O (t) < φ (t).Thus, being picked when sorting platform
When selecting demand, hopper cannot be reached normally, continuously sorted contradiction with sorting personnel, therefore assumed invalid.It follows that entire defeated
The process of caching is sent to must satisfy following constraint
d0(t)>0(τ<t≤T) (4)
During entire hopper outbound sorts, if conveying caching does not influence the normal operation sorted, and l is always existed
(t) < L, then it represents that conveyer buffer storage length is excessive, to reduce equipment input cost, should suitably reduce conveyer buffer storage length.
S102 analyzes hopper Delivery process using Open queuing network, establishes hopper and be averaged the outbound time
Model.
For convenient for the analytical calculation to system hopper Delivery, the present embodiment is according to the operation ring of Multilayer shuttle car system
Following hypothesis is done first in border:
(1) system obeys arbitrary access strategy.
(2) shuttle obeys first armed bit strategy.
(3) shuttle, elevator service follow first-come-first-serviced (FCFS) principle.
It (4) is the generation for preventing from striving case phenomenon, if hopper and product item correspond, and hopper storage quantity is enough, avoids
The task that replenishes is carried out while sorting.
(5) shuttle, elevator can only load a hopper every time, and the not loaded ghost image of equipment operation is rung, constant airspeed.
The Delivery process of system hopper is as shown in Figure 6.The shuttle of corresponding goods layer is issued in outbound instruction by system first
Vehicle, shuttle, to corresponding outbound goods yard, fork hopper according to access rule horizontal movement, transport first and complete to expect with elevator
Hopper is finally transported to corresponding I/O platform by elevator, completes outbound task by case handover.
Specifically, in the step 102, hopper Delivery process is divided using Open queuing network modeling method
Analysis establishes hopper and is averaged outbound time model, and specific implementation is as follows:
S102-1 establishes Open queuing network, and solves to it, obtains service systems at different levels in Open queuing network
Average latency.
When analyzing conveyer caching optimization length, the input flow rate distribution of conveyer caching need to be calculated, that is, is directed to multilayer
Shuttle system calculates the average outbound time T each when material picking case reaches conveyer buffer inlet according to indent structureo。
In Multilayer shuttle car system, by establishing Open queuing network, the average queue for calculating each service organization is long
Degree and average latency, if task arrival rate is λ, device service rate is μ, then can establish Open queuing network as shown in Figure 7,
It include shuttle service system and elevator service system in network.
Method for solving solves this in " queuing network and the Markov chain: modeling and Performance Evaluation " proposed according to Bolch
Open queuing network obtains the queue length Q of each queuing network subsystemn,r(r=1,2 ..., H；N=S1,S2,…SH) table
Show, the average latency of each service node is finally found out according to Arthur D. Little solution formula.
The average latency of shuttleAre as follows:
Wherein,The order taking responsibility arrival rate arranged for i-th layer of jth in shuttle system；It is in shuttle system i-th
Layer jth column device service rate.
The average latency of elevatorAre as follows:
Wherein, Qn,rFor the queue length of elevator service system；The order arranged for i-th layer of jth in shuttle system
Task arrival rate；H is that shuttle system shares H layers of shelf, i.e. the maximum lift number of plies of elevator.
S102-2 establishes hopper and is averaged outbound time model.
Reach under order taking responsibility hopper be sent to conveyer buffer inlet time be equal to each equipment hopper is put down
Equal activity duration and the mutual sum of waiting times of each equipment, ifIndicate in service systems at different levels that " customer " waits
The average latency of service organization,Indicate the average service time of each equipment.Then hopper is averaged the outbound time
Model may be expressed as:
Wherein,For the average latency of shuttle,For the average latency of elevator；Indicate shuttle
Activity duration,Indicate the elevator activity duration.
For Multilayer shuttle car system, the activity duration of shuttleTaken by shuttle horizontal movement time and hugging,
The time composition for unloading hopper, may be expressed as:
Wherein,Indicate shuttle unidirectional horizontal movement time, tpTo hug the time for taking, unloading hopper.
It can similarly obtain, the activity duration of elevatorBy the vertical movement time and hugs and take, unload the time of hopper to form, it can
It indicates are as follows:
Wherein,Indicate that elevator unidirectionally moves vertically the time, tpTo hug the time for taking, unloading hopper.
Under the premise of considering kinetic characteristic, the equipment moving time is analyzed, if ε, σ are respectively single storage goods yard
Width, height, vS、vLRespectively indicate shuttle maximum travelling speed, elevator maximum travelling speed；aS、aLIt respectively indicates and wears
Shuttle car acceleration, elevator acceleration；tpIndicate that equipment hugs the time for taking, unloading hopper.Then worn according in above-mentioned assumed condition
Shuttle car anchor point strategy, under outbound state, one subtask of the every completion of shuttle all rest in the layer first, the movement of equipment is bent
Line is as shown in Figure 8.
In Fig. 8, Y indicates that shuttle reaches the runing time in goods yard, according to kinematics formula, it is assumed that i-th of outbound goods yard
Coordinate is (Hi,Ai), then:
The shuttle unidirectional horizontal movement timeAre as follows:
Elevator unidirectionally moves vertically the timeAre as follows:
S103 establishes conveyer buffer storage length according to hopper Delivery flow distribution and the artificial relationship for sorting efficiency
Model.
Sorting personnel sort in conveyer end, and according to Human Engineering, shelf setting is sorting workbench setting together
Side, and height of table is reasonable, and it is substantially stationary and consistent to sort personnel's unit time picking quantity.Except particular case, big portion
Conveying operation is continuous between timesharing and sorting operation is normal, and the artificial efficiency that sorts obeys general distribution phi (t).
For Multilayer shuttle car system, the primary condition that can be carried out continuously picking is when a hopper has sorted
At later, there is new hopper to reach artificial picking platform.Assuming that μ is obeyed in artificial pickingmGeneral distribution, separately below from the energy that replenishes
Power and two aspect of sorting ability model conveyer buffer storage length.
(1) when conveyer caching hopper it is less than, i.e. cargo density dl(t)<dmaxWhen, hopper will continue to from wearing in system more
Outbound, until the hopper cached on conveyer reaches maximal density.
Assuming that conveyer buffer storage length is larger, be constantly in undersaturated condition in entire picking transmission process, i.e., it is to wear more
The outbound ability of system is unable to satisfy the picking ability for sorting platform, then establishes conveyer caching according to system outbound abilities of wearing more
Length model are as follows:
Wherein, I (β) is the input quantity of conveyer caching, and Annual distribution obeys formula (7)；D (β) is the conveyer at the β moment
The pressed density of caching.
(2) when conveyer caching can reach maximal density, indicate that period conveyer caching has been expired.
A hopper is manually sorted, the more system of wearing could go out a hopper and not lack to be carried out continuously sorting operation
Goods phenomenon, then conveyer buffer storage length model are as follows:
The lowest critical value of conveyer buffer storage length are as follows:
Wherein, T0For the average outbound time of an order；λ is order taking responsibility arrival rate；vlFor the driving speed of conveyer
Degree；μmDistribution function is obeyed for artificial picking speed.
Since the position of n-th of product item is uncertain, for the normal operation for guaranteeing the entire picking period, all satisfactions need to be calculated
Caching density is dmaxTime point, it is assumed that there is c to meet the time points of condition, then the critical value for corresponding to conveyor lengths is
Meanwhile conveyer caching must satisfy the principle of one integral piece storage, it is assumed that L ' is to calculate resulting optimal conveying captain
The critical value of degree, the then length for the caching that actually replenishes are as follows:
The present embodiment also proposes a kind of Multilayer shuttle car system conveyer buffer storage length optimization method, poly- using k-means
Class algorithm and storage area queueing discipline optimize product item storage space, can reduce conveyer buffer storage length.
By conveyer buffer storage length Optimized model set forth above it is found that being thrown not changing Multilayer shuttle car system equipment
Under the premise of entering, not improving plant machinery performance, conveyer can be reduced by reducing the time of hopper arrival conveyer entrance
Buffer storage length, the present embodiment reduce this time by the method for optimization product item storage space, shorten conveyer caching length to reach
The purpose of degree.
Product item has larger impact to the whole travel distance of shuttle and elevator in the storage rule more worn in system, from
And the time for making hopper reach conveyer is different, affects conveyer buffer storage length.Traditional vertical library is under single instrction circulation pattern
Picking task can only be sequentially completed, in order to shorten the outbound time, product item is generally based on weight and turnover rate stores classifiedly.
But for Multilayer shuttle car system, which has the characteristics that the parallel picking of shuttle, the serial outbound of elevator, so being
The access edge for giving full play to the system, carry out storage space optimization when, the present embodiment passes through k- according to cargo relevance principle
Means clustering algorithm determines multiple storage areas, then carries out permutation and combination to storage area according to the principle of similar storage area layer distributed,
It is ranked up inside storage area according to product item outbound amount size simultaneously, it is final to determine the optimal storage space of product item, improve the outbound of system entirety
Efficiency reduces conveyer buffer storage length.
Please refer to attached drawing 9, the Multilayer shuttle car system conveyer buffer storage length optimization method that the present embodiment proposes include with
Lower step:
S201 clusters product item using k-means clustering algorithm, determines multiple storage areas.
The specific implementation of the step 201 is as follows:
S201-1 completes moment mean difference using product item outbound task, establishes product item correlation matrix.
The smaller product item of outbound task deadline mean difference, outbound correlation is stronger, and one should be more placed on when analysis
In a cluster, the specific steps are as follows:
(1) the product Xiang Jihe, S={ 1,2,3 ..., j+1 ..., n } that S is n pending clusterings are set, for any
Two product item SiAnd Sj, outbound quantity difference QiAnd Qj, sequence at the time of outbound task reachesWithAssuming that Qi<Qj, then product item outbound time difference mean difference two-by-two are as follows:
(2) according to outbound product item sum n, n × n product item correlation matrix is constructed.
S201-1 is clustered using k-means algorithm is improved, forms multiple storage areas.
K-means clustering algorithm is the stock's allocation strategy based on fixed product item correlation matrix, by the phase between product item
Pass value regards " distance " in cluster algorithm between product item as, be substituted common Euclidean distance when clustering, Manhattan away from
From etc..
Suitable k cluster reference point is determined first as interim cluster centre, then according to product item correlation matrix,
It finds out with these cluster centres apart from shortest product item, and is assigned in suitable k cluster.Calculate the weight or equal of each cluster
Value, as new cluster centre, then recalculates other each product items to the distance of this cluster centre, then each product item is added
Enter into the cluster of the cluster centre nearest from it, re-forms k cluster.Iteration, until the mean value of k cluster no longer changes,
Obtain k storage area.
S202 carries out permutation and combination to storage area according to the principle of similar storage area permutation and combination, while to component item in storage area
It is ranked up according to outbound amount size, it is final to determine the optimal storage space of product item.
The specific implementation of the step 202 is as follows:
S202-1, according to the analysis of Open queuing network as a result, obtained storage area will be optimized by cluster, according to following original
Then carry out permutation and combination:
(1) the bigger storage area of total outbound amount is closer to I/O point.
(2) two high storage areas of storage similarity between intervals, arrange according to vertical direction, can efficiently use Multilayer shuttle car system
Parallel picking characteristic, reduces the waiting time.
(3) two smaller storage areas of total outbound amount difference between storage area, need to be arranged by diagonal, and wherein outbound amount is high
Storage area be placed on low layer, keep elevator free time shorter.
According to mentioned above principle, the total moment matrix of storage area and storage area correlation matrix are established.
Storage area total amount value θwFor the total outbound number of all product items of the storage area unit time, to establish the total moment matrix of storage area
GTotalAre as follows:
GTotal[θ1 θ2 θw…θm] (18)
Wherein,θiFor storage area i total amount value.
After multiple product items are assigned to same storage area, using the mean value of product items all in the storage area product item new as one, by
The distance of each central point, i.e. storage area relevance values can be calculated in this, establish storage area correlation matrix.Pass through the storage area established
Total moment matrix and storage area correlation matrix, successively utilize three above-mentioned storage area permutation and combination principles, realize storage area global optimization.
S202-2 handles component item sequence in storage area.
Specifically, component item in storage area is ranked up according to outbound amount size, by the big product item of outbound amount deposit in away from
From every layer in first close storage space, the optimal storage space of product item is determined.
After optimizing by storage space, the elevator waiting time, which can minimize, to be ignored, and passes through the layering point of similar cargo
After cloth, shuttle utilization rate can be greatly improved, it is therefore prevented that more shuttles apply for elevator scheduling simultaneously in the short period
Situation minimizes the shuttle waiting time also.
Assuming that after optimization, the elevator normal operation and waiting time ignores；M hopper of every outbound, appearance are once worn
Shuttle car waits, then hopper outbound time that is averaged after optimizing may be expressed as:
One or more embodiments also proposed to Multilayer shuttle car system conveyer buffer storage length modeling method and excellent
The Case Simulation of change method, specific as follows:
This instance data derives from random one day in a practical outbound task of vapour logistics Co., Ltd outbound list information.Make
Solution is programmed with MATLAB software.This wears system there are three tunnel altogether, stores 102 product items, average each tunnel goes out
34, library product item, i.e. ni=34 (i=1,2,3), if conveyer caching initial length be 4m, task arrival rate λ=12 (case/
Min), artificial picking efficiency is μm=10 (casees/min), duty cycle T=480min, device parameter and characteristic are shown in Table 1.
1 Multilayer shuttle car system equipment parameter of table and characteristic
The optimization distribution of product item is carried out according to the storage space optimization method clustered based on k-means, then calculates separately three points
Critical value after picking the corresponding conveyer buffer storage length of platform before optimizationBy can be calculated, three
Critical length when conveyer cache lines reach maximal density and the relational graph at corresponding time point, as shown in Figure 10.Pass through storage
Pipeline buffer storage length after bit optimization is obviously reduced and length variation tends to be steady.
For the first time are reached the time of maximal density to three conveyers separately below, reaches the number of maximal density and replenishes
Caching critical length is analyzed.
Three conveyers reach the time point for caching maximal density for the first time and storage space optimization context is as shown in table 2,
From Table 2, it can be seen that the time that every conveyer reaches caching maximal density for the first time has obviously after storage space optimizes
It reduces, illustrates in the case where roughly equal outbound amount, product item optimizes by storage space, and the speed that hopper reaches conveyer caching is bright
It is aobvious to improve.
2 conveyer of table reaches the time point min of maximal density for the first time
The relationship that three sorting lines reach between the number of maximal density and the distribution of product item is as shown in table 3, can obtain from table 3
Out, the number that the conveyer caching after storage space optimizes reaches maximal density increased significantly.Product item storage space after illustrating optimization
It is stronger with the outbound task correlation of more wearing system, improve conveyer input efficiency.
3 conveyer of table caches the number for reaching maximal density
It is as shown in table 4 by the three points of conveyer buffer storage length critical values and actual value that are calculated, it can be deduced that excellent
Product item distribution method after change is due to improving the arrival rate of hopper, to reduce conveyer buffer storage length.
4 conveyer buffer storage length m of table
In conclusion the conveyer buffer storage length after the storage space optimization clustered based on k-means is than random storage space point
With averagely reducing 12.5%, 12.5%, 11.1% respectively, to demonstrate the validity of conveyer buffer storage length modeling and be based on
K-means clusters the superiority of storage space optimization.
The present embodiment is with conveyer caching is research object in Multilayer shuttle car system, to the hopper transmission process of conveyer
It is analyzed, establishes the input and output balance model cached based on conveyer, and propose that conveyer caching meets sorting operation
Critical condition and optimal conditions are simultaneously proved.
The present embodiment establishes Open queuing network, caches input flow rate distribution by analytical calculation conveyer, establishes defeated
Machine buffer storage length Optimized model is sent, the planning for Multilayer shuttle car system provides design considerations.
The present embodiment in Multilayer shuttle car system, product item stock's allocation be influence hopper outbound speed critical factor it
One, therefore devise k-means algorithm and product item is clustered, determining storage area is obtained, and according to certain principle of optimality pair
Slotting optimization is carried out inside storage area and storage area, the system outbound time is reduced, so as to shorten conveyer buffer storage length.
By case verification, the storage space optimization method based on k-means can reduce conveyer buffer storage length 12% or so, from
And demonstrate the feasibility of conveyer buffer storage length model and the superiority of product item distribution optimization method.
Although above-mentioned be described in conjunction with specific embodiment of the attached drawing to the disclosure, model not is protected to the disclosure
The limitation enclosed, those skilled in the art should understand that, on the basis of the technical solution of the disclosure, those skilled in the art are not
Need to make the creative labor the various modifications or changes that can be made still within the protection scope of the disclosure.
Claims (10)
1. a kind of Multilayer shuttle car system conveyer buffer storage length modeling method, characterized in that slow including establishing conveyer respectively
Deposit input and output balance model, hopper is averaged outbound time model and conveyer buffer storage length model；Wherein,
The conveyer caches input and output balance model are as follows:
Wherein, β is 0 to any time in the t period；τ is that banked cache section is entered out from first cargo to leaving outbound
Cache the time of section；L (t) is the length that t moment pressed density reaches maximum compression density；
The hopper is averaged outbound time model are as follows:
Wherein,For the average latency of shuttle,For the average latency of elevator；Indicate the unidirectional water of shuttle
Flat run duration,Indicate that elevator unidirectionally moves vertically the time.
2. Multilayer shuttle car system conveyer buffer storage length modeling method according to claim 1, characterized in that described defeated
Send the method for building up of machine caching input and output balance model are as follows:
Multilayer shuttle car system picking operation process is analyzed, conveyer caching input and output balance model is established；
In the case where conveyer caching meets sorting operation and operates normally, the optimal conditions and critical item of buffer storage length are provided
Part.
3. Multilayer shuttle car system conveyer buffer storage length modeling method according to claim 2, characterized in that described right
The step of Multilayer shuttle car system picking operation process is analyzed include:
Obtain the driving speed and length of hopper input flow rate, output flow, conveyer；
According to hopper, the driving speed of conveyer sorts speed with artificial in the conveying operation process on conveyer caching, calculates
The reality output flow of conveyer；
By hopper input flow rate compared with the driving speed of conveyer, the hopper density in conveyer caching is obtained；
Calculate the length that per moment pressed density reaches maximum compression density.
4. Multilayer shuttle car system conveyer buffer storage length modeling method according to claim 2, characterized in that described slow
The optimal conditions for depositing length is l (t)=ω, wherein ω is the length of hopper, and l (t) is that t moment pressed density reaches maximum pressure
The length of contracting density；The critical condition d of the buffer storage length0(t)≥φ(t)/vl, d0(t) to be not up to maximum compression density when
General pressed density；vlFor the driving speed of conveyer；φ (t) is that the artificial speed that sorts obeys distribution function.
5. Multilayer shuttle car system conveyer buffer storage length modeling method according to claim 1, characterized in that the material
Case is averaged the method for building up of outbound time model are as follows:
Establish Open queuing network, including shuttle service system and elevator service system；
The Open queuing network is solved, when obtaining the average waiting of shuttle service system and elevator service system
Between；
The runing time and outbound goods yard coordinate that goods yard is reached using shuttle, when calculating separately the unidirectional horizontal movement of shuttle
Between and elevator unidirectionally move vertically the time；
By the shuttle horizontal movement time with and hug and take, unload the temporal summation of hopper, obtain the activity duration of shuttle；
By elevator vertical movement the time with hug take, unload hopper when group summation, the activity duration for the machine that gets a promotion；
The average latency of average latency, elevator service system based on shuttle service system, shuttle operation
Time and elevator activity duration establish hopper and are averaged outbound time model.
6. Multilayer shuttle car system conveyer buffer storage length modeling method according to claim 1, characterized in that described defeated
Send the method for building up of machine buffer storage length model are as follows:
When conveyer caching hopper it is less than, be constantly in undersaturated condition in entire picking transmission process, then conveyer caching length
Spend model are as follows:
Wherein, I (β) is the input quantity of conveyer caching, and d (β) is the pressed density that the conveyer at the β moment caches.
7. Multilayer shuttle car system conveyer buffer storage length modeling method according to claim 1, characterized in that described defeated
Send the method for building up of machine buffer storage length model are as follows:
When conveyer caching can reach maximal density, then conveyer buffer storage length model are as follows:
The lowest critical value of conveyer buffer storage length are as follows:
Wherein, T0For the average outbound time of an order；λ is order taking responsibility arrival rate；L0Minimum critical is cached for conveyer
Value；vlFor the driving speed of conveyer；μmDistribution function is obeyed for artificial picking speed.
8. a kind of Multilayer shuttle car system conveyer buffer storage length optimization method, characterized in that method includes the following steps:
Moment mean difference is completed using product item outbound task, establishes product item correlation matrix；
Product item is clustered using k-means algorithm is improved, forms multiple storage areas；
According to similar storage area permutation and combination principle, the total moment matrix of storage area and storage area correlation matrix are established；
Component item in storage area is ranked up according to outbound amount size, by the big product item of outbound amount deposit in apart from every layer first most
In close storage space, the optimal storage space of product item is determined.
9. Multilayer shuttle car system conveyer buffer storage length optimization method according to claim 8, characterized in that the product
The method for building up of item correlation matrix are as follows:
Establish the product item collection being made of multiple product items to be clustered；
According to the outbound quantity of any two product item, the sequence at the time of outbound task of the two product items reaches is determined；
Calculate the mean difference at any two product item outbound moment；
Product item correlation matrix is constructed using the mean difference at any two product item outbound moment according to outbound product item sum.
10. Multilayer shuttle car system conveyer buffer storage length optimization method according to claim 8, characterized in that described
The method for building up of the total moment matrix of storage area and storage area correlation matrix are as follows:
According to the total outbound number of all product items of each storage area unit time, the total moment matrix G of storage area is establishedTotalAre as follows:
GTotal=[θ1 θ2 θw … θm]
Wherein,θiFor storage area i total amount value；
Using the mean value of product items all in the storage area product item new as one, the distance of each central point is calculated, i.e. storage area is related
Property value；
According to each storage area relevance values, storage area correlation matrix is established.
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