CN108357848A - Modeling optimization method based on Multilayer shuttle car automated storage and retrieval system - Google Patents
Modeling optimization method based on Multilayer shuttle car automated storage and retrieval system Download PDFInfo
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- CN108357848A CN108357848A CN201810213876.2A CN201810213876A CN108357848A CN 108357848 A CN108357848 A CN 108357848A CN 201810213876 A CN201810213876 A CN 201810213876A CN 108357848 A CN108357848 A CN 108357848A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
- B65G1/02—Storage devices
- B65G1/04—Storage devices mechanical
- B65G1/137—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
- B65G1/1373—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed for fulfilling orders in warehouses
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
- B65G1/02—Storage devices
- B65G1/04—Storage devices mechanical
- B65G1/0478—Storage devices mechanical for matrix-arrangements
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
- B65G1/02—Storage devices
- B65G1/04—Storage devices mechanical
- B65G1/0492—Storage devices mechanical with cars adapted to travel in storage aisles
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Abstract
The invention discloses a kind of modeling optimization methods based on Multilayer shuttle car automated storage and retrieval system, including：Determine the characteristics of motion of elevator and shuttle and the respective services time of elevator and shuttle operation process；The velocity and acceleration of the number of plies, the depth in tunnel, the height of single layer shelf, the width of single goods lattice, the velocity and acceleration of elevator, shuttle of extraction Multilayer shuttle car automated storage and retrieval system respectively, single picks and places ETCD estimated time of commencing discharging and outbound Task Details parameter, establishes the mathematical model of Multilayer shuttle car automated storage and retrieval system；Structure is to obtain shortest picking total time as the mixed-integer programming model of target；Mixed-integer programming model is solved using GUROBI linear programming for solution devices, obtains the picking sequence of shortest total picking time and system optimal.The present invention can quickly estimate the performance of system under various shelf and device configuration, and decision support is provided for the careful design and raising capacity utilization of system, saving operating cost.
Description
Technical field
The present invention relates to automatic stereowarehouse technical fields, more particularly to one kind being based on the automatic stored system of Multilayer shuttle car
The modeling optimization method of system.
Background technology
In traditional automatic stereowarehouse, piler is responsible for the access of cargo, therefore to conventional automated three-dimensional storehouse
The modeling in library need to only analyze piler single equipment.
As order is to small lot, multiple batches of development, Multilayer shuttle car automated storage and retrieval system gradually comes into operation.With tradition
Automatic stereowarehouse compare, Multilayer shuttle car automated storage and retrieval system picking, working efficiency with elevator and shuttle
It greatly promotes.As shown in Figure 1, Multilayer shuttle car automated storage and retrieval system at each access adit, is equipped with an elevator for bearing
Blame the movement of the vertical direction of the tunnel cargo, and by goods handling to I/O platforms；It is negative that every layer of shelf are designed with a shuttle
Blame the movement of this layer of cargo horizontal direction.Obviously, the modeling method of traditional automatic stereo storage is set just for piler one kind
It is standby, be not suitable for the pattern of this complexity of Multilayer shuttle car system.Before this, have for Multilayer shuttle car automated storage and retrieval system many
Modeling method, but being all based on queueing theory scheduling theory establishes approximate appraising model greatly, models the result levels of precision of acquisition also
Have to be hoisted.
Therefore, it is necessary to which the modeling method of Multilayer shuttle car automated storage and retrieval system outbound task is furtherd investigate and is changed
Into finding the higher modeling method of levels of precision.How the modeling method of in the prior art conventional automated stereo garage is solved not
How the problem of modeling suitable for the outbound task of Multilayer shuttle car automated storage and retrieval system solves multilayer shuttle in the prior art
How the not high problem of the modeling method accuracy of vehicle automated storage and retrieval system, assess Multilayer shuttle car automated storage and retrieval system performance
Problem, becomes at this stage that there is an urgent need for technical problems to be solved.
Invention content
The purpose of the present invention is exactly to solve the above-mentioned problems, to provide a kind of based on Multilayer shuttle car automated storage and retrieval system
Modeling optimization method, this method by establish mixed-integer programming model accurately describe based on Multilayer shuttle car it is automatic stored
The practical outbound task process of system rapidly calculates automatic stored based on Multilayer shuttle car under various shelf and device configuration
The performance of system, for based on Multilayer shuttle car automated storage and retrieval system careful design and improve capacity utilization, save operation at
This offer decision support.
To achieve the above object, concrete scheme of the invention is as follows：
The invention discloses a kind of modeling optimization methods based on Multilayer shuttle car automated storage and retrieval system, including following step
Suddenly：
(1) when determining the characteristics of motion and the respective services of elevator and shuttle operation process of elevator and shuttle
Between；The extraction number of plies of Multilayer shuttle car automated storage and retrieval system, the depth in tunnel, the height of single layer shelf, single goods lattice respectively
The velocity and acceleration of width, the velocity and acceleration of elevator, shuttle, single picks and places ETCD estimated time of commencing discharging and outbound task is detailed
Information parameter establishes the mathematical model of Multilayer shuttle car automated storage and retrieval system；
(2) structure is to obtain shortest picking total time as the mixed-integer programming model of target；
(3) mixed-integer programming model is solved using GUROBI linear programming for solution devices, acquisition is shortest always to be taken
The value condition of ETCD estimated time of commencing discharging and each state variable, to judge the picking sequence of system optimal.
Further, the characteristics of motion of the determining elevator and shuttle, specially：
Assuming that current elevator determines elevator from I/O platforms to this layer in xth layer according to the height of single layer shelf
Travel distance；
The acceleration and maximum speed for considering elevator, determine the travel time of elevator；
Assuming that current shuttle is in tunnel, first according to the width of single goods lattice determines that it reaches q-th depth location
Travel distance；
The acceleration and maximum speed for considering shuttle, determine the travel time of shuttle.
Further, the respective services time of the determining elevator and shuttle operation process, specially：
Elevator is by cargo from i-th layer of transport to I/O platforms and the service time of release；
Elevator discharges cargo from i-th layer of transport to I/O platforms, is subsequently returning to the service time of jth layer picking；
Shuttle takes out the service time of the outbound task positioned at i-th layer of q-th of depth location；
Elevator is from initial conditions, i.e., to i-th layer of service time at I/O platforms.
Further, the structure is specific as the mixed-integer programming model of target to obtain shortest picking total time
For：
Wherein, tMIt is to be carved at the beginning of elevator executes the last one outbound task, N is the number collection of all shelf numbers of plies
It closing, M is the outbound total task number of system,Indicate elevator by cargo from i-th layer of transport to when the service of I/O platforms and release
Between, yMiOutbound task that whether the last one elevator task is i-th layer is identified (if the last one elevator task is i-th layer
Outbound task, the value of the variable is 1；Otherwise, 0) value of the variable is
Further, the uniqueness for the corresponding outbound layer of each outbound task of guarantee, picking order, goods yard position is established
The constraints of mixed-integer programming model, specially：
1) the outbound total task number on i-th layer of shelf is equal to the elevator total task number of i-th layer of shelf；And ensure arbitrary
The uniqueness of outbound layer where one elevator task；
2) it is that the number of certain layer of n-th of outbound task is equal to the outbound number of tasks of all shelf in all elevator tasks
Number more than n；And ensure any one elevator task its corresponding outbound layer outbound order uniqueness；
3) ensure any one outbound task its corresponding outbound layer outbound order uniqueness；
And ensure any one outbound task its corresponding outbound layer goods yard depth uniqueness.
Further, the constraint between each elevator task, tool are determined according to the contact between each elevator task
Body is：
First elevator task reaches the time of any one layer of shelf more than elevator at the time of beginning；
Also, the time difference that the continuous elevator task of any two is separated by be more than round-trip two layers of the shelf of elevator between need
The time wanted.
Further, determined according to the contact waited in every layer of shelf between outbound task waited in every layer of shelf outbound task it
Between constraint, specially：
First outbound task dispatching machine to be hoisted of any layer is later than goods yard where shuttle reaches it at the time of scheduling complete
The time required to being operated at picking；
Also, the continuous outbound task of two of any layer completes the when that time difference at moment is more than that shuttle walking needs
Between.
Further, carved at the beginning of elevator being executed m-th of outbound task is tm, shuttle is completed i-th layer
N-th of outbound task is denoted as r at the time of waiting for elevator responsein, according to tmAnd rinInner link, establish constraint part such as
Under：
At the time of first elevator task is later than first at the time of beginning and waits for that the cargo of outbound is removed；
And, it is assumed that m-th of elevator task is i-th layer of n-th of outbound task, what m-th of elevator task started
At the time of n-th of task that moment is later than i-th layer is completed；
And, it is assumed that m-th of elevator task is i-th layer of (n-1)th outbound task, and i-th layer of n-th of task is completed
At the time of be later than the sum of time and the shuttle travel time that m-th of elevator task starts；
And, it is assumed that m-th of elevator task is i-th layer of n-th of outbound task, and the m-1 elevator task is jth
The outbound task of layer, i-th layer of n-th of task are later than the time and promotion that the m-1 elevator task starts at the time of completion
The sum of machine travel time.
Further, to ensure the nonnegativity of mixed-integer programming model, establishing constraint part is specially：
Elevator is carved at the beginning of executing m-th of outbound task is not less than zero；
Also, shuttle completes i-th layer of n-th of outbound task, is not less than zero at the time of waiting for elevator response.
Further, the picking sequence of the acquisition system optimal is specially：
By the value for each state variable that solver calculates, the picking sequence in mark system, specific picking is suitable
The method of sequence judgement：
And if only if ymi=1, zmn=1, xinqIndicate that m-th of cargo being removed is located at i-th layer of q-th of depth when=1
It is n-th of cargo being removed on this layer of shelf on position, i.e. m-th of Delivery is i-th layer of n-th of Delivery, together
When the Delivery on q-th of depth location；
According to the above rule, every outbound task uniquely corresponding outbound layer, picking order, goods yard position are judged successively
Information further obtains the picking sequence of system optimal；
Wherein, ymiIdentify m-th elevator task whether the outbound task for being i-th layer, zmnM-th of elevator is identified to appoint
Business whether be a certain layer n-th of outbound task, xinqWhether n-th of Delivery of i-th layer of mark be in q-th of depth location
On.
Beneficial effects of the present invention：
The integer programming model that the present invention establishes can the accurate practical outbound task process of the simulation system, can be quick
The performance for estimating system under various shelf and device configuration, be system careful design and improve capacity utilization, save
Operating cost provides decision support.
Modeling method provided by the invention, which solves the result obtained, can accurately position the sequence of each outbound task,
Compared with random picking sequence required total picking time, the total duration of picking is greatly reduced.
Inner link between outbound task is abstracted as accurate mathematics part by the present invention, establishes Multilayer shuttle car system
Outbound task integer programming model and its derivation algorithm, overcoming the modeling in traditional library, can not to adapt to Multilayer shuttle car automatic
The characteristics of warehousing system multiple servers, the performance of system is fast and accurately calculated using tool.
Using model of the present invention and derivation algorithm, best shuttle, elevator configuration combination can be quickly and effectively found out,
System operation cost is not only saved, also can provide theoretical direction for logistic storage system designer.
Description of the drawings
Fig. 1 is Multilayer shuttle car automated storage and retrieval system schematic diagram；
Fig. 2 is outbound mission flow diagram.
Specific implementation mode：
The present invention is described in detail below in conjunction with the accompanying drawings：
In the outbound task of single, task asks the response of respective layer shuttle first.According to system call, shuttle
It is first moved horizontally at the outbound goods yard of system distribution, is taken out cargo using pallet fork, then shuttle runs to the head of this layer
Row, ask the response of the tunnel elevator.Equally, elevator goes to respective layer to complete cargo with shuttle according to system call
Handing-over, outbound flow of task is as shown in Figure 2.
Based on this, the invention discloses a kind of modeling optimization methods based on Multilayer shuttle car automated storage and retrieval system, including
Following steps：
(1) to Multilayer shuttle car automated storage and retrieval system model, extraction the number of plies, columns, elevator velocity and acceleration, wear
The velocity and acceleration of shuttle car picks and places the parameters such as ETCD estimated time of commencing discharging, and is abstracted as every input in mathematical model.
The basic input that (1-1) analysis model needs；It specifically includes：
The height D of the number of plies N of Multilayer shuttle car automated storage and retrieval system, the depth C in tunnel, single layer shelfh, single goods lattice
Width Dw, shuttle maximum speed Vw, shuttle acceleration aw, elevator maximum speed Vh, elevator acceleration ah, shuttle list
It is secondary to pick and place ETCD estimated time of commencing discharging tw, elevator single pick and place ETCD estimated time of commencing discharging th, solve scale constant T, include all outbound Task Details
The dictionary Q of (layer, place depth location where task).
(1-2) analyzes the characteristics of motion of elevator and shuttle, specially：
Assuming that current elevator is in xth layer, travel distance of the elevator from I/O platforms to this layer is
H=(x-1) × Dh
Consider that the acceleration and maximum speed of elevator, the travel time of elevator are：
Similarly, it is assumed that current shuttle tunnel first, the travel distance for reaching q-th of depth location is
W=q × Dw
Consider that the acceleration and maximum speed of shuttle, the travel time of shuttle are：
(1-3) calculates the respective services time of elevator and shuttle operation process, specially：
Elevator is calculated by cargo from i-th layer of transport to I/O platforms and the service time of release
It calculates elevator to discharge cargo from i-th layer of transport to I/O platforms, is subsequently returning to the service time of jth layer picking
Calculate the service time for the outbound task that shuttle takes out positioned at i-th layer of q-th of depth location
Elevator is calculated from initial conditions, i.e., to i-th layer of service time at I/O platforms
(2) to the dynamic picking process model building of Multilayer shuttle car automated storage and retrieval system, to obtain shortest picking total time
For target, mixed-integer programming model is established.
The object function of (2-1) model：
Wherein, tmIt is to be carved at the beginning of elevator executes m-th of outbound task, N is the number set of all shelf numbers of plies.
When object function obtains minimum value, total picking time of Multilayer shuttle car automated storage and retrieval system is most short.
(2-2) be ensure the corresponding outbound layer of each outbound task, picking order, goods yard position uniqueness establish about
Beam, specially：
∑i∈Nymi=1 i ∈ N, m ∈ 1,2 ..., M }；
Wherein, SiIdentify the outbound task quantity on i-th layer of shelf, variable ymiIdentify m-th elevator task whether be
I-th layer of outbound task, ymiValue rule be：
Wherein, SmaxIndicate the maximum value of single layer shelf outbound task, ZnThe outbound number of tasks for identifying all shelf is more than n
A number, variable zmnIdentify m-th elevator task whether be a certain layer n-th of outbound task, zmnValue rule
For：
Wherein, QiIndicate the set of the depth number composition of outbound task on i-th layer of shelf, variable xinqI-th layer of mark
Whether n-th of outbound task be on q depth locations, xinqValue rule be：
(2-3) analyzes the contact between each elevator task, and it is as follows to establish constraint part：
First elevator task reaches the time of any one layer of shelf more than elevator at the time of beginning, i.e.,
Assuming that the m-1 elevator task is located at i-th layer of shelf, m-th of elevator task is located at jth layer shelf, arbitrarily
The time difference that two continuous elevator tasks are separated by must be more than the time needed between round-trip two layers of the shelf of elevator, i.e.,
(2-4) analyzes the contact waited in every layer of shelf between outbound task, and it is as follows to establish constraint part：
First outbound task dispatching machine to be hoisted of any layer must be later than shuttle at the time of scheduling and reach goods yard where its
The time required to completing picking operation, i.e.,
The time difference that the continuous outbound task of two of any layer completes the moment must be more than shuttle walkingThe time wanted, i.e.,
Shuttle is completed the outbound task on i-th layer of n-th of depth location by (2-5), at the time of waiting for elevator response
It is denoted as rin, analyze tmAnd rinInner link, it is as follows to establish constraint part：
At the time of first elevator task is later than first at the time of beginning and waits for that the cargo of outbound is removed, i.e.,
t1≥ri1-T(3-y1,i-zm1-xi1q)；m∈{1,2,…,M},q∈{1,2,…,C}；
Assuming that m-th of elevator task is i-th layer of n-th of outbound task, evening at the time of m-th of elevator task starts
At the time of i-th layer of n-th of task is completed, i.e.,
tm≥rin-T(2-ymi-zmn), i ∈ N, n ∈ { 1,2 ..., Smax},m∈{1,2,…,M}；
Assuming that m-th of elevator task is i-th layer of (n-1)th outbound task, then i-th layer of n-th of task is completed
At the time of be later than the sum of time and the shuttle travel time that m-th of elevator task starts, i.e.,
i∈N,n∈{2,…,Smax},m∈{2,…,M}；
Assuming that m-th of elevator task is i-th layer of n-th of outbound task, the m-1 elevator task is jth layer
Outbound task, then i-th layer of n-th of task is later than the time and promotion that the m-1 elevator task starts at the time of completion
The sum of machine travel time, i.e.,
i,j∈N,n∈{1,…,Smax},m∈{2,…,M}。
(2-6) is the nonnegativity for ensureing model, adds other necessary Simple constraints, tm≥0,rin≥0。
(3) it uses Python to program, designed model is generated into configuration using GUROBI linear programming for solution devices
File solves the picking sequence of shortest total picking time and system optimal, and thus further statistics obtains various configuration items
Result of calculation under part obtains the allocation optimum of Multilayer shuttle car automated storage and retrieval system convenient for analysis.
Obtain system optimal picking sequence be specially：
By the value for each state variable that solver calculates, the picking sequence in mark system, specific picking is suitable
The method of sequence judgement：
And if only if ymi=1, zmn=1, xinqIndicate that m-th of cargo being removed is located at i-th layer of q-th of depth when=1
It is n-th of cargo being removed on this layer of shelf on position, i.e. m-th of Delivery is i-th layer of n-th of Delivery, together
When the Delivery on q-th of depth location；
According to the above rule, every outbound task uniquely corresponding outbound layer, picking order, goods yard position are judged successively
Information further obtains the picking sequence of system optimal；
Wherein, ymiIdentify m-th elevator task whether the outbound task for being i-th layer, zmnM-th of elevator is identified to appoint
Business whether be a certain layer n-th of outbound task, xinqWhether n-th of Delivery of i-th layer of mark be in q-th of depth location
On.
In order to verify the validity of model, the simulated scenario such as table 1 of 6 kinds of Multilayer shuttle car systems is set, using above-mentioned
The quick result of calculation of model exact method.Under every group of scene, total picking time under 4 kinds of random picking sequences is recorded respectively,
It is compared with the result of calculation of model, the data record obtained is as shown in table 2.
1 scene setting table of table
2 the model calculation of table is analyzed
Obviously, substantially reduced than total picking time under random picking sequence using model calculated total picking time,
The as best picking sequence of the calculated picking sequence of model.
Table 3 is the most common basic configuration of Multilayer shuttle car automated storage and retrieval system, and the above results are under the configuration condition
It is calculated.
3 Multilayer shuttle car automated storage and retrieval system basic configuration of table
Above-mentioned, although the foregoing specific embodiments of the present invention is described with reference to the accompanying drawings, not protects model to the present invention
The limitation enclosed, those skilled in the art should understand that, based on the technical solutions of the present invention, those skilled in the art are not
Need to make the creative labor the various modifications or changes that can be made still within protection scope of the present invention.
Claims (10)
1. the modeling optimization method based on Multilayer shuttle car automated storage and retrieval system, which is characterized in that include the following steps：
(1) characteristics of motion of elevator and shuttle and the respective services time of elevator and shuttle operation process are determined；
The width of the number of plies, the depth in tunnel, the height of single layer shelf, single goods lattice of extraction Multilayer shuttle car automated storage and retrieval system respectively
The velocity and acceleration of degree, the velocity and acceleration of elevator, shuttle, single picks and places ETCD estimated time of commencing discharging and outbound task is believed in detail
Parameter is ceased, the mathematical model of Multilayer shuttle car automated storage and retrieval system is established；
(2) structure is to obtain shortest picking total time as the mixed-integer programming model of target；
(3) mixed-integer programming model is solved using GUROBI linear programming for solution devices, when obtaining shortest total picking
Between and system optimal picking sequence.
2. the modeling optimization method based on Multilayer shuttle car automated storage and retrieval system as described in claim 1, which is characterized in that institute
The characteristics of motion of determining elevator and shuttle is stated, specially：
Assuming that current elevator determines walking of the elevator from I/O platforms to this layer in xth layer according to the height of single layer shelf
Distance；
The acceleration and maximum speed for considering elevator, determine the travel time of elevator；
Assuming that current shuttle is in tunnel, first according to the width of single goods lattice determines that it reaches the walking of q-th of depth location
Distance；
The acceleration and maximum speed for considering shuttle, determine the travel time of shuttle.
3. the modeling optimization method based on Multilayer shuttle car automated storage and retrieval system as described in claim 1, which is characterized in that institute
The respective services time of determining elevator and shuttle operation process is stated, specially：
Elevator is by cargo from i-th layer of transport to I/O platforms and the service time of release；
Elevator discharges cargo from i-th layer of transport to I/O platforms, is subsequently returning to the service time of jth layer picking；
Shuttle takes out the service time of the outbound task positioned at i-th layer of q-th of depth location；
Elevator is from initial conditions, i.e., to i-th layer of service time at I/O platforms.
4. the modeling optimization method based on Multilayer shuttle car automated storage and retrieval system as described in claim 1, which is characterized in that institute
State structure is specially as the mixed-integer programming model of target to obtain shortest picking total time：
Wherein, tMIt is to be carved at the beginning of elevator executes the last one outbound task, N is the number set of all shelf numbers of plies, M
For the outbound total task number of system,Indicate that elevator transports cargo to I/O platforms and the service time of release from i-th layer,
yMiIdentify the last one elevator task whether the outbound task for being i-th layer, go out if the last one elevator task is i-th layer
The value of library task, the variable is 1；Otherwise, the value of the variable is 0.
5. the modeling optimization method based on Multilayer shuttle car automated storage and retrieval system as described in claim 1, which is characterized in that be
Ensure the corresponding outbound layer of each outbound task, picking order, goods yard position uniqueness, establish mixed-integer programming model
Constraints, specially：
1) the outbound total task number on i-th layer of shelf is equal to the elevator total task number of i-th layer of shelf；And ensure any one
The uniqueness of outbound layer where elevator task；
2) be in all elevator tasks certain layer of n-th of outbound task number be equal to all shelf outbound number of tasks be more than
N numbers；And ensure any one elevator task its corresponding outbound layer outbound order uniqueness；
3) ensure any one outbound task its corresponding outbound layer outbound order uniqueness；
And ensure any one outbound task its corresponding outbound layer goods yard depth uniqueness.
6. the modeling optimization method based on Multilayer shuttle car automated storage and retrieval system as described in claim 1, which is characterized in that root
The constraint between each elevator task is determined according to the contact between each elevator task, specially：
First elevator task reaches the time of any one layer of shelf more than elevator at the time of beginning；
Also, the time difference that the continuous elevator task of any two is separated by, which is more than between elevator round-trip two layers of shelf, to be needed
Time.
7. the modeling optimization method based on Multilayer shuttle car automated storage and retrieval system as described in claim 1, which is characterized in that root
The constraint waited in every layer of shelf between outbound task is determined according to the contact waited in every layer of shelf between outbound task, specially：
First outbound task dispatching machine to be hoisted of any layer is later than goods yard where shuttle reaches it at the time of scheduling completes to take
The time required to goods operation；
Also, the time difference that the continuous outbound task of two of any layer completes the moment is more than the time that shuttle walking needs.
8. the modeling optimization method based on Multilayer shuttle car automated storage and retrieval system as described in claim 1, which is characterized in that will
It is t that elevator is carved at the beginning of executing m-th of outbound taskm, shuttle is completed into i-th layer of n-th of outbound task, waiting carries
It is denoted as r at the time of the response of the machine of literin, according to tmAnd rinInner link, it is as follows to establish constraint part：
At the time of first elevator task is later than first at the time of beginning and waits for that the cargo of outbound is removed；
And, it is assumed that m-th of elevator task is i-th layer of n-th of outbound task, at the time of m-th of elevator task starts
At the time of being later than i-th layer of n-th of task completion；
And, it is assumed that m-th of elevator task is i-th layer of (n-1)th outbound task, i-th layer of n-th of task complete when
Quarter is later than the sum of time and the shuttle travel time that m-th of elevator task starts；
And, it is assumed that m-th of elevator task is i-th layer of n-th of outbound task, and the m-1 elevator task is jth layer
Outbound task, i-th layer of n-th of task are later than the time and elevator row that the m-1 elevator task starts at the time of completion
Walk the sum of time.
9. the modeling optimization method based on Multilayer shuttle car automated storage and retrieval system as described in claim 1, which is characterized in that be
Ensure the nonnegativity of mixed-integer programming model, establishing constraint part is specially：
Elevator is carved at the beginning of executing m-th of outbound task is not less than zero；
Also, shuttle completes the outbound task on i-th layer of q-th of depth location, is not less than at the time of waiting for elevator response
Zero.
10. the modeling optimization method based on Multilayer shuttle car automated storage and retrieval system as described in claim 1, which is characterized in that
The acquisition system optimal picking sequence be specially：
By the value for each state variable that solver calculates, the picking sequence in mark system, specific picking sequence is sentenced
Fixed method：
And if only if ymi=1, zmn=1, xinqIndicate that m-th of cargo being removed is located at i-th layer of q-th of depth location when=1
On, it is n-th of cargo being removed on this layer of shelf, i.e. m-th of Delivery is i-th layer of n-th of Delivery, simultaneously should
Delivery is on q-th of depth location；
According to the above rule, every outbound task uniquely corresponding outbound layer, picking order, goods yard position letter are judged successively
Breath further obtains the picking sequence of system optimal；
Wherein, ymiIdentify m-th elevator task whether the outbound task for being i-th layer, zmnWhether identify m-th elevator task
For n-th of outbound task of a certain layer, xinqWhether n-th of Delivery of i-th layer of mark be on q-th of depth location.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
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| CN109081030A (en) * | 2018-09-28 | 2018-12-25 | 陕西科技大学 | A kind of method for optimizing configuration of the intensive warehousing system of primary and secondary shuttle vehicle type |
| CN109230142A (en) * | 2018-10-22 | 2019-01-18 | 陕西科技大学 | A kind of scheduling method for optimizing route of intensive warehousing system multiple working |
| CN109677830A (en) * | 2019-02-28 | 2019-04-26 | 陕西科技大学 | A kind of intensive warehousing system method for optimizing resource allocation of four-way shuttle vehicle type |
| CN109896217A (en) * | 2019-04-19 | 2019-06-18 | 广州豪坤工业自动化控制技术有限公司 | A kind of Dual-channel type steering shuttle automatic material flow device of variable-ratio |
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