CN109164763A - A kind of Optimization Scheduling of industrial robot automatic production line - Google Patents
A kind of Optimization Scheduling of industrial robot automatic production line Download PDFInfo
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- CN109164763A CN109164763A CN201810826418.6A CN201810826418A CN109164763A CN 109164763 A CN109164763 A CN 109164763A CN 201810826418 A CN201810826418 A CN 201810826418A CN 109164763 A CN109164763 A CN 109164763A
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- 238000004519 manufacturing process Methods 0.000 title claims abstract description 46
- 238000005457 optimization Methods 0.000 title claims abstract description 28
- 238000000034 method Methods 0.000 claims abstract description 23
- 238000011112 process operation Methods 0.000 claims abstract description 5
- 239000003016 pheromone Substances 0.000 claims description 19
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000003754 machining Methods 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 230000007115 recruitment Effects 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 abstract description 3
- 230000009286 beneficial effect Effects 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32252—Scheduling production, machining, job shop
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The present invention relates to a kind of Optimization Schedulings of industrial robot automatic production line, belong to industrial automation production of intelligent Optimum Scheduling Technology field.The present invention passes through the scheduling model and optimization aim for determining industrial robot automatic production line, and proposes that a kind of Optimization Scheduling of hybrid ant colony optimizes target；Wherein, the process time of the scheduling model process operation number and corresponding operating to be passed through according to each product and establish, while determine optimization aim be minimizes Maximal Makespan.The present invention can obtain within a short period of time the approximate optimal solution of industrial robot automatic production line scheduling problem, to reduce the production cost of enterprise, improve the economic benefit of enterprise.
Description
Technical field
The present invention relates to a kind of Optimization Schedulings of industrial robot automatic production line, belong to industrial automation production
Intelligent optimization dispatching technique field.
Background technique
Industrial robot automatic production line is integrated with the new and high technology of modern manufacturing industry, by numerically-controlled machine tool, industrial machine
The technologies such as people, intelligent control are fused together well, have met requirement of the social development to industry.Industry 4.0 and China
The it is proposed for manufacturing 2025 policies, modern development trend and the future of industry will be become by represent industrial robot automatic production line
Leading force.Therefore, by industrial robot, traditional flow production line design optimization, Product Process method these manufacturing industry skills
Automatic production line caused by the mixing together of art will have an immense impact on to the production efficiency of enterprise.
Industrial robot automatic production line greatly reduces labour's investment, shortens the life cycle of product, improves
The production efficiency and quality of product.Industrial robot automatic production line develops while also saving the inventory of factory, i.e.,
Zero buffer characteristics: when workpiece is after completing certain process operation, but the machine of its next operation (adds still in not-ready state
Work state or blocked state), then the workpiece can be blocked on a current machine, until the machine of next operation is in ready shape
State can just make industrial robot be transported to next machine to be processed；Since the machine integrated level of automatic production line is higher,
Therefore the haulage time of industrial robot can be ignored.Since the efficiency of automatic production line is very high, the production of enterprise is advised
Often very big and product is relatively abundant for mould.It is so very big for the scheduling production difficulty of industrial robot automatic production line, it is difficult to
Production scheduling is carried out by the experience of worker to be therefore of great significance for the research and solution of problems.
Industrial robot automatic production line generally according to Product Process and specification difference so that workpiece is in each operation
Production time it is different.Especially constraint of the automatic production line for zero buffer area of workpiece, different arrangements is to this batch
The completion date of workpiece has tremendous influence.Therefore, seem particularly important for producing the scheduling of sequence, good scheduling scheme
The production cycle that enterprise can largely be shortened, reduce the production cost of enterprise, to improve the economic benefit of enterprise.
The present invention establishes a kind of scheduling model for industrial robot automatic production line, designs a kind of based on mixing ant colony
The Optimization Scheduling of algorithm can obtain the near-optimization arrangement of problems within a short period of time, shorten the production week of enterprise
Phase reduces the production cost of enterprise.
Summary of the invention
The purpose of the present invention is being directed to the scheduling problem of industrial robot automatic production line, propose a kind of based on mixing ant
The Optimization Scheduling of group's algorithm shortens the production cycle of enterprise by way of acquiring near-optimization sequence, reduces enterprise
Production cost, to improve the economic benefit of enterprise.
The technical scheme is that a kind of Optimization Scheduling of industrial robot automatic production line, passes through determination
The scheduling model and optimization aim of industrial robot automatic production line, and propose a kind of Optimized Operation side of hybrid ant colony
Method optimizes target；Wherein, scheduling model to be passed through according to each product process operation number and corresponding operating plus
It is established between working hour, while determining that optimization aim is minimizes Maximal Makespan, i.e. f=Cmax(π)
In formula, the number of workpiece is n, the operand of needs is m, π={ π1,π2,…,πnIndicate the Optimal Scheduling
One solution, πiThe workpiece being processed for i-th in job sequence π,For workpiece πiMachine where leaving j-th of operation
Time, because can not still process next workpiece when workpiece is blocked on machine,Represent workpiece πiIt is operating required for j
Process time, whereinRepresent workpiece πiLeave the time of pseudo operation 0, that is, represent workpiece first operate start plus
Between working hour, workpiece meets following constraint condition when processed: a workpiece at a time can only by a machining, one
Platform machine can only at a time process a workpiece；
The Optimization Scheduling based on hybrid ant colony specifically:
Step1, initialization of population: generating initialization population using the method generated at random and calculates the target of corresponding individual
Value, until the quantity of initial solution reaches the population scale of requirement, population scale popsize；The value of initialization information element, information
Plain τijThe information strength that workpiece i appears in position j is represented, is initialized
Step2, it updates pheromones: pheromones being updated according to target value individual in population, more new formula are as follows:
Wherein ρ is the volatilization factor of pheromones,For the target value of current individual,For all individuals of current population
The mean value of target value；
Step3, population recruitment: new individual is generated according to updated pheromones, the sequence of new individual is according to following public affairs
Formula generates, and taboo list will be added after some workpiece is selected, and new individual then calculates the target value of corresponding sequence after generating and empties
Taboo list, to generate next individual,
Wherein p0For the parameter in algorithm, value range is [0,1], and p is that the value of (0,1) is randomly generated, if meeting item
Part then selects the maximum row number of pheromone concentration in Pheromone Matrix in the i-th row, and the row number is not in taboo list, such as discontented
Sufficient condition then randomly chooses a workpiece, probability calculation formula according to probability from unselected workpiece are as follows:
S indicates the set of all non-selected workpiece, carries out protecting excellent operation to the old and new's individual of population, i.e. merging the old and new
Individual population is worth lesser the first half individual according to the size selection target of target value and forms current population；
Step4, local search: to optimum individual in current population, i.e. the smallest individual of target value carries out the part Insert
Search operation, if the target value for newly generating individual after operation replaces the individual better than the individual；
Step5, termination condition: setting termination condition as algorithm iteration number T, if algorithm meets condition, output is worked as
An individual in preceding population, i.e. optimum individual；Otherwise go to step Step2, iterates, and is up to meeting termination condition
Only.
The beneficial effects of the present invention are: the present invention for industrial robot automatic production line establish a kind of scheduling model and
Optimization method can obtain within a short period of time the approximate optimal solution of industrial robot automatic production line scheduling problem, to drop
The production cost of low enterprise improves the economic benefit of enterprise.
Detailed description of the invention
Fig. 1 is whole design flow chart of the invention；
Fig. 2 is dispatching method flow chart of the invention；
Fig. 3 is the expression schematic diagram of solution in the present invention；
Fig. 4 is local search " Insert " operation chart.
Specific embodiment
Embodiment 1: as shown in Figs 1-4, a kind of Optimization Scheduling of industrial robot automatic production line passes through determination
The scheduling model and optimization aim of industrial robot automatic production line, and propose a kind of Optimized Operation side of hybrid ant colony
Method optimizes target；Wherein, scheduling model to be passed through according to each product process operation number and corresponding operating plus
It is established between working hour, while determining that optimization aim is minimizes Maximal Makespan, i.e. f=Cmax(π)
In formula, the number of workpiece is n, the operand of needs is m, π={ π1,π2,…,πnIndicate the Optimal Scheduling
One solution, πiThe workpiece being processed for i-th in job sequence π,For workpiece πiMachine where leaving j-th of operation
Time, because can not still process next workpiece when workpiece is blocked on machine,Represent workpiece πiIt is operating required for j
Process time, whereinRepresent workpiece πiLeave the time of pseudo operation 0, that is, represent workpiece first operate start plus
Between working hour, workpiece meets following constraint condition when processed: a workpiece at a time can only by a machining, one
Platform machine can only at a time process a workpiece；
The Optimization Scheduling based on hybrid ant colony specifically:
Step1, initialization of population: generating initialization population using the method generated at random and calculates the target of corresponding individual
Value, until the quantity of initial solution reaches the population scale of requirement, population scale popsize；The value of initialization information element, information
Plain τijThe information strength that workpiece i appears in position j is represented, is initialized
Step2, it updates pheromones: pheromones being updated according to target value individual in population, more new formula are as follows:
Wherein ρ is the volatilization factor of pheromones,For the target value of current individual,For all individuals of current population
The mean value of target value；
Step3, population recruitment: new individual is generated according to updated pheromones, the sequence of new individual is according to following public affairs
Formula generates, and taboo list will be added after some workpiece is selected, and new individual then calculates the target value of corresponding sequence after generating and empties
Taboo list, to generate next individual,
Wherein p0For the parameter in algorithm, value range is [0,1], and p is that the value of (0,1) is randomly generated, if meeting item
Part then selects the maximum row number of pheromone concentration in Pheromone Matrix in the i-th row, and the row number is not in taboo list, such as discontented
Sufficient condition then randomly chooses a workpiece, probability calculation formula according to probability from unselected workpiece are as follows:
S indicates the set of all non-selected workpiece, carries out protecting excellent operation to the old and new's individual of population, i.e. merging the old and new
Individual population is worth lesser the first half individual according to the size selection target of target value and forms current population；
Step4, local search: to optimum individual in current population, i.e. the smallest individual of target value carries out the part Insert
Search operation, if the target value for newly generating individual after operation replaces the individual better than the individual；
Step5, termination condition: setting termination condition as algorithm iteration number T, if algorithm meets condition, output is worked as
An individual in preceding population, i.e. optimum individual；Otherwise go to step Step2, iterates, and is up to meeting termination condition
Only.
Population scale popsize is set as 100, and maximum number of iterations T=300, volatilization factor ρ are 0.6, p0 0.8.
Above in conjunction with attached drawing, the embodiment of the present invention is explained in detail, but the present invention is not limited to above-mentioned
Embodiment within the knowledge of a person skilled in the art can also be before not departing from present inventive concept
Put that various changes can be made.
Claims (1)
1. a kind of Optimization Scheduling of industrial robot automatic production line, it is characterised in that: by determining industrial robot
The scheduling model and optimization aim of automatic production line, and propose the Optimization Scheduling of hybrid ant colony a kind of to target into
Row optimization；Wherein, the process time of the scheduling model process operation number and corresponding operating to be passed through according to each product and build
It is vertical, while determining that optimization aim is minimizes Maximal Makespan, i.e. f=Cmax(π)
In formula, the number of workpiece is n, the operand of needs is m, π={ π1,π2,…,πnIndicate the one of the Optimal Scheduling
A solution, πiThe workpiece being processed for i-th in job sequence π,For workpiece πiLeave machine where j-th of operation when
Between, because can not still process next workpiece when workpiece is blocked on machine,Represent workpiece πiAdd required for j operating
Between working hour, whereinRepresent workpiece πiLeave the time of pseudo operation 0, that is, represent workpiece first operate start process
Time, workpiece meet following constraint condition when processed: a workpiece at a time can only be by a machining, and one
Machine can only at a time process a workpiece；
The Optimization Scheduling based on hybrid ant colony specifically:
Step1, initialization of population: generating initialization population using the method generated at random and calculates the target value of corresponding individual,
Until the quantity of initial solution reaches the population scale of requirement, population scale popsize；The value of initialization information element, pheromones
τijThe information strength that workpiece i appears in position j is represented, is initialized
Step2, it updates pheromones: pheromones being updated according to target value individual in population, more new formula are as follows:
Wherein ρ is the volatilization factor of pheromones,For the target value of current individual,For all individual goals of current population
The mean value of value；
Step3, population recruitment: generating new individual according to updated pheromones, and the sequence of new individual is given birth to according to the following formula
At taboo list will be added in some workpiece after being selected, new individual then calculates the target value of corresponding sequence after generating and empties taboo
Table, to generate next individual,
Wherein p0For the parameter in algorithm, value range is [0,1], and p is the value that (0,1) is randomly generated, and is selected if meeting condition
The maximum row number of pheromone concentration in Pheromone Matrix in the i-th row is selected, and the row number is such as unsatisfactory for item not in taboo list
Part then randomly chooses a workpiece, probability calculation formula according to probability from unselected workpiece are as follows:
S indicates the set of all non-selected workpiece, carries out protecting excellent operation to the old and new's individual of population, i.e. merging the old and new individual
Population is worth lesser the first half individual according to the size selection target of target value and forms current population；
Step4, local search: to optimum individual in current population, i.e. the smallest individual of target value carries out Insert local search
Operation, if the target value for newly generating individual after operation replaces the individual better than the individual；
Step5, termination condition: termination condition is set as algorithm iteration number T and exports current kind if algorithm meets condition
An individual, i.e. optimum individual in group；Otherwise go to step Step2, iterates, until meeting termination condition.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114063584A (en) * | 2021-11-19 | 2022-02-18 | 江苏科技大学 | Scheduling control method, device and system for integrated processing of ship weight-related parts |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114063584A (en) * | 2021-11-19 | 2022-02-18 | 江苏科技大学 | Scheduling control method, device and system for integrated processing of ship weight-related parts |
| CN114063584B (en) * | 2021-11-19 | 2024-04-26 | 江苏科技大学 | Scheduling control method, device and system for integrated processing of ship weight closing parts |
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