CN104537503A - Data processing method and system - Google Patents
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Abstract
The invention discloses a data processing method. The method includes the steps that according to analysis of received order form tasks, resource information of resources needed for completing the order form tasks and production constraint conditions are obtained; according to the resource information and the production constraint conditions, feasible production scheduling schemes are generated and put into a preset task feasible solution pond; according to the resource information and a preset optimization objective, the feasible production scheduling schemes are evaluated, and the feasible production scheduling scheme with the highest evaluation value is analyzed and determined as the optimal production scheduling scheme. The invention further discloses a data processing system. With the resources as the leading factor, the feasible production scheduling schemes of the current resources are recursively captured and matched and are evaluated according to the preset optimization objective, finally the feasible production scheduling scheme with the highest evaluation value is determined as the optimal production scheduling scheme, the steps are repeated until resource traversal of all production tasks in the order form tasks is completed, and in this way, the technical problems that as a reasonable production scheduling scheme is selected out, duration is prolonged, and cost is increased are solved.
Description
Technical field
The present invention relates to a kind of data processing method and system.
Background technology
The production scheduling protocol questions of enterprise is very complicated multi-objective optimization question, and subsidiary a lot of constraint condition, situation is more assorted, in prior art, general employing is taken optimization method as the leading factor with production task and is optimized process to production scheduling scheme, namely so that production task can be completed for optimization aim, the production scheduling scheme finally performed is selected during the production scheduling scheme that can realize production task is produced as enterprise practical.But, when the production scheduling scheme that can realize production task has multiple, production scheduling scheme quality inevitable relative to the production task ginseng that can realize production task is secondary uneven, an optional feasible schedule scheme is difficult to choose most suitable feasible production scheduling scheme, can extend the duration needed for production task like this, increase cost needed for production task.
Foregoing, only for auxiliary understanding technical scheme of the present invention, does not represent and admits that foregoing is prior art.
Summary of the invention
Fundamental purpose of the present invention is to provide a kind of data processing method and system, be intended to solve to take as the leading factor with production task and process is optimized to production scheduling scheme is difficult to select reasonable production schedule scheme, easily cause the technical matters that claim for eot, cost increase.
For achieving the above object, a kind of data processing method provided by the invention, described data processing method comprises the following steps:
Resource information and the production constraint condition of described order taking responsibility resource requirement has been obtained according to the order taking responsibility analysis received;
Generate feasible scheduling scheme according to described resource information and production constraint condition, and described feasible scheduling scheme is put into default task feasible solution pond;
According to described resource information and default optimization aim, described feasible scheduling scheme is evaluated, analyze and determine that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
Preferably, describedly according to described resource information and the optimization aim preset, described feasible scheduling scheme to be evaluated, compares and determine that described feasible scheduling scheme that evaluation of estimate is the highest is that the step of optimum scheduling scheme comprises:
According to the resource settings instruction received, from the resource completed needed for described order taking responsibility, select at least one resource settings to be primary resource, all the other resource settings are auxiliary resources;
According to the optimization aim instruction received, corresponding main optimization aim is set for described primary resource and described auxiliary resources arranges corresponding secondary optimization aim;
According to described main optimization aim and secondary optimization aim, twice optimizing evaluation is carried out to described feasible scheduling scheme, compare and determine that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
Preferably, describedly according to main optimization aim and secondary optimization aim, twice optimizing evaluation is carried out to described feasible scheduling scheme, compares and determine that described feasible scheduling scheme that evaluation of estimate is the highest is that the step of optimum scheduling scheme comprises:
The primary weight values of described main optimization aim and the secondary weighted value of secondary optimization aim are set;
Draw the main optimization degree of described feasible scheduling scheme according to described main optimization aim analysis, draw the secondary optimization degree of described feasible scheduling scheme according to described secondary optimization aim analysis;
The main optimization degree calculating described feasible scheduling scheme is multiplied by the long-pending sum that the long-pending of primary weight values and the secondary optimization degree of this feasible scheduling scheme are multiplied by secondary weighted value, and is weighted on average as the evaluation of estimate of feasible scheduling scheme again using sum both this;
Relatively determine that described feasible scheduling scheme that evaluation of estimate is the highest is as optimum scheduling scheme.
Preferably, describedly according to described resource information and the optimization aim preset, described feasible scheduling scheme to be evaluated, compares and determine that described feasible scheduling scheme that evaluation of estimate is the highest is the step of optimum scheduling scheme and is:
According to formula
calculate the evaluation of estimate F (X) of all described feasible scheduling schemes, compare and determine that the feasible scheduling scheme that evaluation of estimate F (X) is the highest is optimum scheduling scheme, wherein, X is present feasible scheduling scheme, Y
i(X) be the optimization degree function of i-th optimization aim of present feasible scheduling scheme, W
ifor the weighted value of i-th optimization aim of present feasible scheduling scheme, N is total number of the optimization aim of present feasible scheduling scheme, and J is the total number comprising resource in present feasible scheduling scheme.
Preferably, described production constraint condition comprises at least one in processing route constraint condition, operation validity constraint condition, instruction validity constraint condition, resource availability constraint condition and production characteristic matching constraint condition.
In addition, for achieving the above object, the present invention also provides a kind of data handling system, and described data handling system comprises:
Acquisition module, for having obtained resource information and the production constraint condition of described order taking responsibility resource requirement according to the order taking responsibility analysis received;
Feasible program generation module, for generating feasible scheduling scheme according to described resource information and production constraint condition, and puts into default task feasible solution pond by described feasible scheduling scheme;
Analyze determination module, for according to described resource information and default optimization aim, described feasible scheduling scheme is evaluated, analyze and determine that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
Preferably, described analysis determination module comprises:
Resource settings unit, for the resource settings instruction according to reception, from the resource completed needed for described order taking responsibility, select at least one resource settings to be primary resource, all the other resource settings are auxiliary resources;
Target arranges instruction, for arranging instruction according to the target received, arranges corresponding main optimization aim and described auxiliary resources arranges corresponding secondary optimization aim for described primary resource;
Comparing unit, for carrying out twice optimizing evaluation according to described main optimization aim and secondary optimization aim to described feasible scheduling scheme, comparing and determining that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
Preferably, described comparing unit also for:
The primary weight values of described main optimization aim and the secondary weighted value of secondary optimization aim are set;
Draw the main optimization degree of described feasible scheduling scheme according to described main optimization aim analysis, draw the secondary optimization degree of described feasible scheduling scheme according to described secondary optimization aim analysis;
The main optimization degree calculating described feasible scheduling scheme is multiplied by the long-pending sum that the long-pending of primary weight values and the secondary optimization degree of this feasible scheduling scheme are multiplied by secondary weighted value, and is weighted on average as the evaluation of estimate of feasible scheduling scheme again using sum both this;
Relatively determine that described feasible scheduling scheme that evaluation of estimate is the highest is as optimum scheduling scheme.
evaluation of estimate F (X), compare and determine that the feasible scheduling scheme that evaluation of estimate F (X) is the highest is optimum scheduling scheme, wherein, X is present feasible scheduling scheme, Y
i(X) be the optimization degree function of i-th optimization aim of present feasible scheduling scheme, W
ifor the weighted value of i-th optimization aim of present feasible scheduling scheme, N is total number of the optimization aim of present feasible scheduling scheme, and J is the total number comprising resource in present feasible scheduling scheme.
Preferably, described production constraint condition comprises at least one in processing route constraint condition, operation validity constraint condition, instruction validity constraint condition, resource availability constraint condition and production characteristic matching constraint condition.
First the present invention has obtained resource information and the production constraint condition of this order taking responsibility resource requirement according to the order taking responsibility analysis received; Then generate feasible scheduling scheme according to resource information and production constraint condition, and feasible scheduling scheme is put into default task feasible solution pond; Finally according to described resource information and default optimization aim, described feasible scheduling scheme is evaluated, analyze and determine that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme, first the scheduling scheme not meeting production constraint condition is like this filtered, and filters out production constraint condition and has had the feasible production scheduling scheme of the resource information of order taking responsibility resource requirement; Then take as the leading factor with resource, recurrence captures the feasible scheduling scheme of coupling Current resource, optimization aim according to presetting is evaluated feasible scheduling scheme, the feasible scheduling scheme that final analysis determination evaluation of estimate is the highest is optimum scheduling scheme, until the resource of all production tasks in order taking responsibility has traveled through, doing so avoids because selecting unreasonable scheduling scheme, causing the technical matters that claim for eot, cost increase.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of data processing method one embodiment of the present invention;
Fig. 2 be in Fig. 1 according to described resource information and the optimization aim preset, described feasible scheduling scheme is evaluated, analyzes and determine that described feasible scheduling scheme that evaluation of estimate is the highest is the refinement schematic flow sheet that the step the first of optimum scheduling scheme is implemented;
Fig. 3 carries out twice optimizing evaluation according to main optimization aim and secondary optimization aim to feasible scheduling scheme in Fig. 2, compares and determines that feasible scheduling scheme that evaluation of estimate is the highest is the refinement schematic flow sheet of optimum scheduling scheme;
Fig. 4 is the high-level schematic functional block diagram of data handling system one embodiment of the present invention;
Fig. 5 is the refinement functional mode schematic diagram analyzing determination module in Fig. 4;
Fig. 6 is the schematic flow sheet of data processing method preferred embodiment of the present invention;
Fig. 7 is the scheduling protocol procedures schematic diagram that data processing method preferred embodiment of the present invention selects evaluation of estimate the highest from feasible solution pond.
The realization of the object of the invention, functional characteristics and advantage will in conjunction with the embodiments, are described further with reference to accompanying drawing.
Embodiment
Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.
The invention provides a kind of data processing method, be mainly used in the optimization aspect of enterprise's scheduling scheme.
With reference to the schematic flow sheet that Fig. 1, Fig. 1 are data processing method one embodiment of the present invention.
In one embodiment, this data processing method comprises the following steps:
Step S10, has obtained resource information and the production constraint condition of order taking responsibility resource requirement according to the order taking responsibility analysis received;
After manufacturing enterprise receives product order, be order taking responsibility by product order decomposition, and be input in the data handling system for Optimal Scheduling scheme, namely before step S10, first receive the order taking responsibility of user's input, then resource information and the production constraint condition of this order taking responsibility resource requirement has been obtained according to the order taking responsibility analysis of user's input, such as order taking responsibility is the product of production injection mo(u)lding, the resource then needed is injection machine and product mold, and corresponding production constraint condition has the production feature such as precision, specification of product.
Step S20, generates feasible scheduling scheme according to resource information and production constraint condition, and feasible scheduling scheme is put into default task feasible solution pond;
The resource needed for order taking responsibility has been determined according to resource information, generate all possible scheduling scheme, then according to production constraint condition, the scheduling scheme not meeting this production constraint condition is got rid of, namely select feasible scheduling scheme, and feasible scheduling scheme is put into default task feasible solution pond.
Step S30, according to resource information and default optimization aim, evaluates feasible scheduling scheme, analyzes and determine that the feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
According to resource information and default optimization aim, one by one the feasible scheduling scheme in task feasible solution pond is evaluated, draw the evaluation of estimate of each feasible scheduling scheme, be defined as optimum scheduling scheme from the feasible scheduling scheme selecting evaluation of estimate the highest.
In addition, optimization aim comprises:
1) exceed the time limit and minimize, the Optimum Matching degree of punctual delivery then this optimization aim is 1, ensures that product completes on time between delivery date as much as possible; If exceeded the time limit, then the Optimum Matching degree of this optimization aim is negative, exceeds the time limit larger, and the Optimum Matching degree of this optimization aim is less;
2) minimize switching time, the switching time occurred between current production scheduling scheme and side task is larger, then the Optimum Matching degree of this optimization aim is more close to 0, and when without setup times, then the Optimum Matching degree of this optimization aim is 1;
3) same item is preferential, and the production task on current production scheduling scheme and side is same product object situation, then the Optimum Matching degree of this optimization aim is 1, otherwise then the Optimum Matching degree of this optimization aim is 0;
4) manufacturing time minimizes, and manufacturing time is larger, then the Optimum Matching degree of this optimization aim is more close to 0, and manufacturing time is less, then the Optimum Matching degree of this optimization aim is more close to 1;
5) resource priority degree, resource priority degree is according to size prioritization;
6) production cost minimizes, and mainly comprises the start cost and human cost etc. of manufacture;
7) stand-by period minimizes, and when the stand-by period is larger, the Optimum Matching degree of this optimization aim is more close to 0, and the stand-by period, more hour then the Optimum Matching degree of this optimization aim was more close to 1;
8) order margin minimizes, the scheduling scheme priority allocation that margin is minimum, and namely margin is less, and the Optimum Matching degree of this optimization aim is higher.
Preferably, production constraint condition comprises at least one in processing route constraint condition, operation validity constraint condition, instruction validity constraint condition, resource availability constraint condition and production characteristic matching constraint condition.
Processing route constraint condition, the processing route referring in feasible production scheduling scheme must be manufacturing enterprise the processing route that has or can use.
Operation validity constraint condition, refers to that the operation in feasible production scheduling scheme must be the presently used effective operation of manufacturing enterprise.
Instruction validity constraint condition: refer to that the instruction used in feasible production scheduling scheme must be the presently used instruction of manufacturing enterprise.
Resource availability constraint condition: refer to that the resource used in feasible production scheduling scheme must be the presently used efficient resource of manufacturing enterprise.
Production characteristic matching constraint condition: refer to that the production feature used in feasible production scheduling scheme must mate the production feature of manufacturing enterprise's Current resource.
In the present embodiment, resource information and the production constraint condition of this order taking responsibility resource requirement has first been obtained according to the order taking responsibility analysis received; Then generate feasible scheduling scheme according to resource information and production constraint condition, and feasible scheduling scheme is put into default task feasible solution pond; Finally according to resource information and default optimization aim, feasible scheduling scheme is evaluated, analyze and determine that the feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme, first the scheduling scheme not meeting production constraint condition is like this filtered, and filters out production constraint condition and has had the feasible production scheduling scheme of the resource information of order taking responsibility resource requirement; Then take as the leading factor with resource, recurrence captures the feasible scheduling scheme of coupling Current resource, optimization aim according to presetting is evaluated feasible scheduling scheme, the feasible scheduling scheme that final analysis determination evaluation of estimate is the highest is optimum scheduling scheme, until the resource of all production tasks in order taking responsibility has traveled through, doing so avoids because selecting unreasonable scheduling scheme, causing the technical matters that claim for eot, cost increase.
Further, reference Fig. 2, Fig. 2 is the refinement schematic flow sheet of step S30 in Fig. 1.
In the present embodiment, step S30 comprises:
Step S301, according to the resource settings instruction received, from the resource completed needed for order taking responsibility, select at least one resource settings to be primary resource, all the other resource settings are auxiliary resources;
User is according to the important level of different types of resource relative to order taking responsibility, to the instruction of data handling system input resource settings, system is according to the resource settings instruction received, from the resource completed needed for order taking responsibility, select at least one resource settings to be that (resource that important level is high is primary resource to primary resource, such as important level is set to level Four, the resource of the first order is primary resource, and the resource of other ranks is auxiliary resources), all the other resource settings are auxiliary resources.
Step S302, according to the optimization aim instruction received, arranges corresponding main optimization aim for primary resource and auxiliary resources arranges corresponding secondary optimization aim;
User can input optimization aim instruction to data handling system, for primary resource arranges corresponding main optimization aim, for auxiliary resources arranges corresponding secondary optimization aim, main optimization aim and auxiliary optimization aim can be the same or different, and mainly arrange optimization aim for resource, such as, optimization aim is that manufacturing time minimizes, Optimized Matching degree is the value between 0 ~ 1, and manufacturing time is more large more close to 0, more little more close to 1.
Step S303, carries out twice optimizing evaluation according to main optimization aim and secondary optimization aim to feasible scheduling scheme, compares and determines that the feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
Preferably, with reference to Fig. 3, step S303 comprises the steps:
Step S3031, arranges the primary weight values of main optimization aim and the secondary weighted value of secondary optimization aim;
User, according to need of production, arranges the weighted value of optimization aim, the instruction that data handling system inputs according to user, and arrange the primary weight values of main optimization aim and the secondary weighted value of secondary optimization aim, such as primary weight values is 0.95, and secondary weighted value is 0.05.
Step S3032, draws the main optimization degree of feasible scheduling scheme according to main optimization aim analysis, draw the secondary optimization degree of feasible scheduling scheme according to secondary optimization aim analysis;
Optimization aim can be the function about optimization degree, the relative optimization aim of resource of each feasible scheduling scheme has corresponding optimization degree, so draw the main optimization degree of feasible scheduling scheme according to main optimization aim analysis, draw the secondary optimization degree of feasible scheduling scheme according to secondary optimization aim analysis.
Step S3033, the main optimization degree calculating feasible scheduling scheme is multiplied by the long-pending sum that the long-pending of primary weight values and the secondary optimization degree of this feasible scheduling scheme are multiplied by secondary weighted value, and is weighted on average as the evaluation of estimate of feasible scheduling scheme again using sum both this;
The main optimization degree that the evaluation of estimate of feasible scheduling scheme equals feasible scheduling scheme is multiplied by the value that long-pending sum that the long-pending of primary weight values and the secondary optimization degree of this feasible scheduling scheme be multiplied by secondary weighted value is weighted average gained again.
Step S3034, compares and determines that feasible scheduling scheme that evaluation of estimate is the highest is as optimum scheduling scheme
In the present embodiment, first the scheduling scheme not meeting production constraint condition is filtered out, and other nonproductive constraint condition is all converted into the optimization aim as optimal conditions, the infeasible scheduling scheme occurring that more how nonproductive constraint causes can be avoided like this, the scheduling scheme that maximum generation is feasible, just its objective optimization degree is different.Such as, the constraint condition at order delivery date, because order delivery date be not production constraint condition, the optimal conditions of optimization aim can be converted to, if can not delivery date be met, can find and exceed the time limit a solution minimum as current scheduling scheme, exceed the time limit more serious, illustrate that optimization degree is lower, but user by the mode of consulting with client, can improve the enforceability of current planning.
Further, step S30 is:
Step S300, according to formula
calculate the evaluation of estimate F (X) of all feasible scheduling schemes, compare and determine that the feasible scheduling scheme that evaluation of estimate F (X) is the highest is optimum scheduling scheme, wherein, X is present feasible scheduling scheme, Y
i(X) be the optimization degree function of i-th optimization aim of present feasible scheduling scheme, W
ifor the weighted value of i-th optimization aim of present feasible scheduling scheme, N is total number of the optimization aim of present feasible scheduling scheme, and J is the total number comprising resource in present feasible scheduling scheme.
In the present embodiment, the invention provides one to dominate based on resource, the data processing method of scheduling scheme optimization can be carried out to selected resource, achieve and produce constraint and the double process of objective optimization, and when there is multiple optimization aim, each evaluation of estimate meeting the scheduling scheme of production constraint condition is gone out according to the weighted value different weights average computation of optimization aim, guarantee the rational feasible scheduling scheme of generation one, simultaneously can by improving the primary weight values of main target of optimization, at utmost preferentially can meet main target of optimization, other secondary optimization aim are also paid close attention to accordingly, thus have laid a good foundation for obtaining an optimum feasible scheduling scheme, the utilization of resources rate of final enterprise inside, reduce production cost, enterprise competitive power.
Preferably, with reference to Fig. 6, the data processing method of the scheduling evaluate alternatives dominated based on resource provided by the present invention and selection, comprises step:
Step one, setting production constraint condition, the weighted value of main optimization aim and secondary optimization aim;
A) the production technology path that the order of scheduling is relevant and technology characteristics are treated in setting
User can according to actual production technique, and the production constraint conditions such as the scheduling key element must considered during setting scheduling and condition for validity, system produces the feasible scheduling scheme of the candidate of each resource automatically according to the matching result of various production constraint condition.A constraint condition decision table is defined for each production constraint condition, as shown in table 1.Constraint condition determination information table comprises code constraint, constrained type, order code, operation code, assignment instructions, and be constrained to the fields such as day-mark will, wherein constrained type is divided into:
A) processing route constraint, whether order meets to use which processing route.
B) operation validity constraint, whether order meets uses current process.
C) instruction validity constraint, whether order meets uses present instruction
D) resource availability constraint, whether order meets uses Current resource condition for validity
E) production characteristic matching constraint, whether the production feature of order mates the production feature of Current resource.
| Sequence number | Field | Type | Length | Major key | Index | Acquiescence | Remarks |
| 1 | Code constraint | varchar | 30 | ||||
| 2 | Constrained type | varchar | 10 | ||||
| 3 | Order code | varchar | 30 | ||||
| 4 | Operation code | varchar | 40 | ||||
| 5 | Assignment instructions | varchar | 50 | ||||
| 6 | Be constrained to day-mark | bool |
Table 1
B) main optimization aim is set
Be directed to primary resource, user selects one or more as main optimization aim in built-in optimization aim, gives the weighted value that it is higher, or self-defined main optimization aim, to primary resource degree of the being optimized evaluation of the feasible scheduling scheme of current candidate.Comment result to arrange an optimization aim optimization degree information table for each optimization degree, as shown in table 2, its main information is: optimization degree code, optimization aim code, order code, operation code, assignment instructions, the information such as optimization degree.
| Sequence number | Field | Type | Length | Major key | Index | Acquiescence | Remarks |
| 1 | Optimization degree code | varchar | 10 | ||||
| 2 | Optimization aim code | varchar | 10 | ||||
| 3 | Order code | varchar | 30 | ||||
| 4 | Operation code | varchar | 40 | ||||
| 5 | Assignment instructions | varchar | 50 | ||||
| 6 | Optimize angle value | float |
Table 2
C) secondary optimization aim is set
Be directed to auxiliary resources, user selects one or more as secondary optimization aim in built-in optimization aim, gives the weighted value that it is lower, or self-defined suboptimization target, to auxiliary resources degree of the being optimized evaluation of the feasible scheduling scheme of current candidate.Comment result to arrange optimization aim optimization degree information table (as shown in table 2) for each optimization degree, its main information is: optimization degree code, optimization aim code, order code, operation code, assignment instructions, optimization degree.
Step 2, carry out constraint condition judgement and the evaluation of optimization degree for scheduling scheme, idiographic flow please refer to Fig. 6, and concrete steps are as follows:
A, feasible scheduling scheme judge, judge, and generate constraint condition determination information table for each item constraint condition;
B, the scheduling scheme all set up for institute's Prescribed Properties, put into feasible solution pond, an order otherwise at least there is a feasible solution, otherwise puts into intangibility pond;
C, in feasible solution pond, first carries out primary resource selection, obtains the feasible scheduling scheme of relevant candidate according to selected primary resource.
The optimization aim calculation optimization angle value that D, basis are preset, exports the optimization angle value of current scheduling scheme, and scheduling scheme judges and evaluate to terminate.
Different optimization aim, optimization degree function is also different, according to optimization degree function calculate institute interior optimization angle value larger, represent more meet current optimization aim, the degree of optimization of optimization aim is better.Be minimised as example to exceed the time limit, its objective optimization degree function representation is:
X<0 is worked as x>=0 or F (x)=x/ (1-x) in F (x)=1/ (1+x)
Wherein, the value of x be order delivery date-planned the moment
E, judgement continue to carry out evaluation scheduling using Current resource as guiding, if so, then go back to D, otherwise go back to B.
Step 3, optimizes angle value to the work of Xie Chi carrying out descending sort according to the optimization aim in step 2;
Step 4, from the scheduling scheme in feasible solution pond, select the scheduling scheme that optimization degree is the highest, process flow diagram refers to Fig. 7, and concrete steps are as follows:
A, be arranged in feasible solution pond and select the individual ratio upper limit threshold values L accounting for the individual sum in feasible solution pond.
B, utilize statistical method, solve by calculate in feasible solution pond all the variances optimizing angle value, the individuality calculated in feasible solution pond optimizes the diversity factor of angle value
C, solution for feasible solution pond, according to the height of optimization degree, select to optimize the less a collection of individuality of angle value diversity factor, individual number demand fulfillment upper limit threshold values L, this collection of individuality is a collection of individuality best in feasible solution pond.
D, give this collection of individuality of the person of choosing in C, select one to optimize the highest work of angle value.
E, select work based in D, in units of working, the evaluation of suboptimum objective optimization is carried out to secondary resource, select the scheduling scheme that suboptimum objective optimization angle value is the highest, generate the scheduling scheme of final optimum.
Step 5, exports optimum scheduling scheme.
The present invention further provides a kind of data handling system, is the high-level schematic functional block diagram of data handling system one embodiment of the present invention with reference to Fig. 4, Fig. 4.
In the present embodiment, data handling system comprises:
Acquisition module 40, for having obtained resource information and the production constraint condition of described order taking responsibility resource requirement according to the order taking responsibility analysis received;
After manufacturing enterprise receives product order, be order taking responsibility by product order decomposition, and be input in the data handling system for Optimal Scheduling scheme, namely before the order taking responsibility of data handling system reception, first receive the order taking responsibility of user's input, then resource information and the production constraint condition of this order taking responsibility resource requirement has been obtained according to the order taking responsibility analysis of user's input, such as order taking responsibility is the product of production injection mo(u)lding, the resource then needed is injection machine and product mold, corresponding production constraint condition has the precision of product, the production features such as specification.
Feasible program generation module 50, for generating feasible scheduling scheme according to described resource information and production constraint condition, and puts into default task feasible solution pond by described feasible scheduling scheme;
The resource needed for order taking responsibility has been determined according to resource information, generate all possible scheduling scheme, then according to production constraint condition, the scheduling scheme not meeting this production constraint condition is got rid of, namely select feasible scheduling scheme, and feasible scheduling scheme is put into default task feasible solution pond.
Analyze determination module 60, for according to described resource information and default optimization aim, described feasible scheduling scheme is evaluated, analyze and determine that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
According to resource information and default optimization aim, one by one the feasible scheduling scheme in task feasible solution pond is evaluated, draw the evaluation of estimate of each feasible scheduling scheme, be defined as optimum scheduling scheme from the feasible scheduling scheme selecting evaluation of estimate the highest.
In addition, optimization aim comprises:
1) exceed the time limit and minimize, the Optimum Matching degree of punctual delivery then this optimization aim is 1, ensures that product completes on time between delivery date as much as possible; If exceeded the time limit, then the Optimum Matching degree of this optimization aim is negative, exceeds the time limit larger, and the Optimum Matching degree of this optimization aim is less;
2) minimize switching time, the switching time occurred between current production scheduling scheme and side task is larger, then the Optimum Matching degree of this optimization aim is more close to 0, and when without setup times, then the Optimum Matching degree of this optimization aim is 1;
3) same item is preferential, and the production task on current production scheduling scheme and side is same product object situation, then the Optimum Matching degree of this optimization aim is 1, otherwise then the Optimum Matching degree of this optimization aim is 0;
4) manufacturing time minimizes, and manufacturing time is larger, then the Optimum Matching degree of this optimization aim is more close to 0, and manufacturing time is less, then the Optimum Matching degree of this optimization aim is more close to 1;
5) resource priority degree, resource priority degree is according to size prioritization;
6) production cost minimizes, and mainly comprises the start cost and human cost etc. of manufacture;
7) stand-by period minimizes, and when the stand-by period is larger, the Optimum Matching degree of this optimization aim is more close to 0, and the stand-by period, more hour then the Optimum Matching degree of this optimization aim was more close to 1;
8) order margin minimizes, the scheduling scheme priority allocation that margin is minimum, and namely margin is less, and the Optimum Matching degree of this optimization aim is higher.
Preferably, production constraint condition comprises at least one in processing route constraint condition, operation validity constraint condition, instruction validity constraint condition, resource availability constraint condition and production characteristic matching constraint condition.
Processing route constraint condition, the processing route referring in feasible production scheduling scheme must be manufacturing enterprise the processing route that has or can use.
Operation validity constraint condition, refers to that the operation in feasible production scheduling scheme must be the presently used effective operation of manufacturing enterprise.
Instruction validity constraint condition: refer to that the instruction used in feasible production scheduling scheme must be the presently used instruction of manufacturing enterprise.
Resource availability constraint condition: refer to that the resource used in feasible production scheduling scheme must be the presently used efficient resource of manufacturing enterprise.
Production characteristic matching constraint condition: refer to that the production feature used in feasible production scheduling scheme must mate the production feature of manufacturing enterprise's Current resource.
In the present embodiment, resource information and the production constraint condition of this order taking responsibility resource requirement has first been obtained according to the order taking responsibility analysis received; Then generate feasible scheduling scheme according to resource information and production constraint condition, and feasible scheduling scheme is put into default task feasible solution pond; Finally according to resource information and default optimization aim, feasible scheduling scheme is evaluated, analyze and determine that the feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme, first the scheduling scheme not meeting production constraint condition is like this filtered, and filters out production constraint condition and has had the feasible production scheduling scheme of the resource information of order taking responsibility resource requirement; Then take as the leading factor with resource, recurrence captures the feasible scheduling scheme of coupling Current resource, optimization aim according to presetting is evaluated feasible scheduling scheme, the feasible scheduling scheme that final analysis determination evaluation of estimate is the highest is optimum scheduling scheme, until the resource of all production tasks in order taking responsibility has traveled through, doing so avoids because selecting unreasonable scheduling scheme, causing the technical matters that claim for eot, cost increase.
Further, with reference to Fig. 5, analyze determination module 60 and comprise:
Resource settings unit 601, for the resource settings instruction according to reception, from the resource completed needed for described order taking responsibility, select at least one resource settings to be primary resource, all the other resource settings are auxiliary resources;
User is according to the important level of different types of resource relative to order taking responsibility, to the instruction of data handling system input resource settings, system is according to the resource settings instruction received, from the resource completed needed for order taking responsibility, select at least one resource settings to be that (resource that important level is high is primary resource to primary resource, such as important level is set to level Four, the resource of the first order is primary resource, and the resource of other ranks is auxiliary resources), all the other resource settings are auxiliary resources.
Target arranges instruction 602, for arranging instruction according to the target received, arranges corresponding main optimization aim and described auxiliary resources arranges corresponding secondary optimization aim for described primary resource;
User can input optimization aim instruction to data handling system, for primary resource arranges corresponding main optimization aim, for auxiliary resources arranges corresponding secondary optimization aim, main optimization aim and auxiliary optimization aim can be the same or different, and mainly arrange optimization aim for resource, such as, optimization aim is that manufacturing time minimizes, Optimized Matching degree is the value between 0 ~ 1, and manufacturing time is more large more close to 0, more little more close to 1.
Comparing unit 603, for carrying out twice optimizing evaluation according to described main optimization aim and secondary optimization aim to described feasible scheduling scheme, comparing and determining that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
Preferably, comparing unit 603 also for:
The primary weight values of described main optimization aim and the secondary weighted value of secondary optimization aim are set;
Draw the main optimization degree of described feasible scheduling scheme according to described main optimization aim analysis, draw the secondary optimization degree of described feasible scheduling scheme according to described secondary optimization aim analysis;
The main optimization degree calculating described feasible scheduling scheme is multiplied by the long-pending sum that the long-pending of primary weight values and the secondary optimization degree of this feasible scheduling scheme are multiplied by secondary weighted value, and is weighted on average as the evaluation of estimate of feasible scheduling scheme again using sum both this;
Relatively determine that described feasible scheduling scheme that evaluation of estimate is the highest is as optimum scheduling scheme.
User, according to need of production, arranges the weighted value of optimization aim, the instruction that data handling system inputs according to user, and arrange the primary weight values of main optimization aim and the secondary weighted value of secondary optimization aim, such as primary weight values is 0.95, and secondary weighted value is 0.05.
Optimization aim can be the function about optimization degree, the relative optimization aim of resource of each feasible scheduling scheme has corresponding optimization degree, so draw the main optimization degree of feasible scheduling scheme according to main optimization aim analysis, draw the secondary optimization degree of feasible scheduling scheme according to secondary optimization aim analysis.
The main optimization degree that the evaluation of estimate of feasible scheduling scheme equals feasible scheduling scheme is multiplied by the value that long-pending sum that the long-pending of primary weight values and the secondary optimization degree of this feasible scheduling scheme be multiplied by secondary weighted value is weighted average gained again.
In the present embodiment, first the scheduling scheme not meeting production constraint condition is filtered out, and other nonproductive constraint condition is all converted into the optimization aim as optimal conditions, the infeasible scheduling scheme occurring that more how nonproductive constraint causes can be avoided like this, the scheduling scheme that maximum generation is feasible, just its objective optimization degree is different.Such as, the constraint condition at order delivery date, because order delivery date be not production constraint condition, the optimal conditions of optimization aim can be converted to, if can not delivery date be met, can find and exceed the time limit a solution minimum as current scheduling scheme, exceed the time limit more serious, illustrate that optimization degree is lower, but user by the mode of consulting with client, can improve the enforceability of current planning.
evaluation of estimate F (X), compare and determine that the feasible scheduling scheme that evaluation of estimate F (X) is the highest is optimum scheduling scheme, wherein, X is present feasible scheduling scheme, Y
i(X) be the optimization degree function of i-th optimization aim of present feasible scheduling scheme, W
ifor the weighted value of i-th optimization aim of present feasible scheduling scheme, N is total number of the optimization aim of present feasible scheduling scheme, and J is the total number comprising resource in present feasible scheduling scheme.
In the present embodiment, the invention provides one to dominate based on resource, the data processing method of scheduling scheme optimization can be carried out to selected resource, achieve and produce constraint and the double process of objective optimization, and when there is multiple optimization aim, each evaluation of estimate meeting the scheduling scheme of production constraint condition is gone out according to the weighted value different weights average computation of optimization aim, guarantee the rational feasible scheduling scheme of generation one, simultaneously can by improving the primary weight values of main target of optimization, at utmost preferentially can meet main target of optimization, other secondary optimization aim are also paid close attention to accordingly, thus have laid a good foundation for obtaining an optimum feasible scheduling scheme, the utilization of resources rate of final enterprise inside, reduce production cost, enterprise competitive power.
These are only the preferred embodiments of the present invention; not thereby the scope of the claims of the present invention is limited; every utilize instructions of the present invention and accompanying drawing content to do equivalent structure or equivalent flow process conversion; or be directly or indirectly used in other relevant technical fields, be all in like manner included in scope of patent protection of the present invention.
Claims (10)
1. a data processing method, is characterized in that, described data processing method comprises the following steps:
Resource information and the production constraint condition of described order taking responsibility resource requirement has been obtained according to the order taking responsibility analysis received;
Generate feasible scheduling scheme according to described resource information and production constraint condition, and described feasible scheduling scheme is put into default task feasible solution pond;
According to described resource information and default optimization aim, described feasible scheduling scheme is evaluated, analyze and determine that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
2. data processing method as claimed in claim 1, it is characterized in that, describedly according to described resource information and the optimization aim preset, described feasible scheduling scheme to be evaluated, compares and determine that described feasible scheduling scheme that evaluation of estimate is the highest is that the step of optimum scheduling scheme comprises:
According to the resource settings instruction received, from the resource completed needed for described order taking responsibility, select at least one resource settings to be primary resource, all the other resource settings are auxiliary resources;
According to the optimization aim instruction received, corresponding main optimization aim is set for described primary resource and described auxiliary resources arranges corresponding secondary optimization aim;
According to described main optimization aim and secondary optimization aim, twice optimizing evaluation is carried out to described feasible scheduling scheme, compare and determine that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
3. data processing method as claimed in claim 2, it is characterized in that, describedly according to main optimization aim and secondary optimization aim, twice optimizing evaluation is carried out to described feasible scheduling scheme, compares and determine that described feasible scheduling scheme that evaluation of estimate is the highest is that the step of optimum scheduling scheme comprises:
The primary weight values of described main optimization aim and the secondary weighted value of secondary optimization aim are set;
Draw the main optimization degree of described feasible scheduling scheme according to described main optimization aim analysis, draw the secondary optimization degree of described feasible scheduling scheme according to described secondary optimization aim analysis;
The main optimization degree calculating described feasible scheduling scheme is multiplied by the long-pending sum that the long-pending of primary weight values and the secondary optimization degree of this feasible scheduling scheme are multiplied by secondary weighted value, and is weighted on average as the evaluation of estimate of feasible scheduling scheme again using sum both this;
Relatively determine that described feasible scheduling scheme that evaluation of estimate is the highest is as optimum scheduling scheme.
4. data processing method as claimed in claim 1, it is characterized in that, describedly according to described resource information and the optimization aim preset, described feasible scheduling scheme to be evaluated, compares and determine that described feasible scheduling scheme that evaluation of estimate is the highest is the step of optimum scheduling scheme and is:
According to formula
calculate the evaluation of estimate F (X) of all described feasible scheduling schemes, compare and determine that the feasible scheduling scheme that evaluation of estimate F (X) is the highest is optimum scheduling scheme, wherein, X is present feasible scheduling scheme, Y
i(X) be the optimization degree function of i-th optimization aim of present feasible scheduling scheme, W
ifor the weighted value of i-th optimization aim of present feasible scheduling scheme, N is total number of the optimization aim of present feasible scheduling scheme, and J is the total number comprising resource in present feasible scheduling scheme.
5. the data processing method as described in Claims 1-4 any one, it is characterized in that, described production constraint condition comprises at least one in processing route constraint condition, operation validity constraint condition, instruction validity constraint condition, resource availability constraint condition and production characteristic matching constraint condition.
6. a data handling system, is characterized in that, described data handling system comprises:
Acquisition module, for having obtained resource information and the production constraint condition of described order taking responsibility resource requirement according to the order taking responsibility analysis received;
Feasible program generation module, for generating feasible scheduling scheme according to described resource information and production constraint condition, and puts into default task feasible solution pond by described feasible scheduling scheme;
Analyze determination module, for according to described resource information and default optimization aim, described feasible scheduling scheme is evaluated, analyze and determine that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
7. data handling system as claimed in claim 6, it is characterized in that, described analysis determination module comprises:
Resource settings unit, for the resource settings instruction according to reception, from the resource completed needed for described order taking responsibility, select at least one resource settings to be primary resource, all the other resource settings are auxiliary resources;
Target arranges instruction, for arranging instruction according to the target received, arranges corresponding main optimization aim and described auxiliary resources arranges corresponding secondary optimization aim for described primary resource;
Comparing unit, for carrying out twice optimizing evaluation according to described main optimization aim and secondary optimization aim to described feasible scheduling scheme, comparing and determining that the described feasible scheduling scheme that evaluation of estimate is the highest is optimum scheduling scheme.
8. data handling system as claimed in claim 7, is characterized in that, described comparing unit also for:
The primary weight values of described main optimization aim and the secondary weighted value of secondary optimization aim are set;
Draw the main optimization degree of described feasible scheduling scheme according to described main optimization aim analysis, draw the secondary optimization degree of described feasible scheduling scheme according to described secondary optimization aim analysis;
The main optimization degree calculating described feasible scheduling scheme is multiplied by the long-pending sum that the long-pending of primary weight values and the secondary optimization degree of this feasible scheduling scheme are multiplied by secondary weighted value, and is weighted on average as the evaluation of estimate of feasible scheduling scheme again using sum both this;
Relatively determine that described feasible scheduling scheme that evaluation of estimate is the highest is as optimum scheduling scheme.
9. data handling system as claimed in claim 6, is characterized in that, described analysis determination module also for:
According to formula
calculate the evaluation of estimate F (X) of all described feasible scheduling schemes, compare and determine that the feasible scheduling scheme that evaluation of estimate F (X) is the highest is optimum scheduling scheme, wherein, X is present feasible scheduling scheme, Y
i(X) be the optimization degree function of i-th optimization aim of present feasible scheduling scheme, W
ifor the weighted value of i-th optimization aim of present feasible scheduling scheme, N is total number of the optimization aim of present feasible scheduling scheme, and J is the total number comprising resource in present feasible scheduling scheme.
10. the data handling system as described in claim 6 to 9 any one, it is characterized in that, described production constraint condition comprises at least one in processing route constraint condition, operation validity constraint condition, instruction validity constraint condition, resource availability constraint condition and production characteristic matching constraint condition.
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