CN113780738A - Order allocation method and system - Google Patents
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Abstract
The invention discloses an order distribution method and system, relating to the field of order distribution, which is characterized in that product order information of each order is obtained; generating a product task corresponding to each product according to the order information of each product and adding the product task into a product task set; according to the quantity of the tasks in the product task set, production line information corresponding to each product task and production time required by each product task, obtaining order production positions of distributable product tasks on each production line, and obtaining the production time required by each production line to finish the corresponding product task as completion time; obtaining a re-ordered combination of order production positions on each production line and a score of each combination by using an order ordering model and taking a preset constraint condition as a basis; according to the scores of all the combinations, the combination with the highest score is selected as the target order distribution sequence, and the problems that the existing general production scheduling model cannot efficiently utilize production equipment to shorten the manufacturing period and effectively finish a large number of factory order production scheduling tasks in order are solved.
Description
Technical Field
The invention relates to the field of order allocation, in particular to an order allocation method and system.
Background
For a mechanical manufacturing factory, it is very important to ensure that the utilization of a factory production line and machines is maximized under the condition that the factory normally arranges order production sequence. As the size of such plants becomes increasingly larger, how to ensure the operation of the above-mentioned links becomes a difficult problem requiring an effective solution. In the modern times, production data is greatly improved, so that the maximization of the production utilization rate of various production machines and equipment becomes a key for improving the production efficiency. Today, most of the order scheduling tasks (scheduling, i.e. scheduling the order sequence) of factories are still manually completed by using the production experience of production personnel. For a small-scale factory, manual scheduling can be achieved with low cost and good effect, but under the condition that the scale of the factory is continuously expanded, the scheduling difficulty is exponentially increased, so that a huge workload is caused for production personnel, errors and omission inevitably occur, and therefore, a production task cannot be completed on time or production data is wasted, so that how to make a scheduling plan capable of efficiently utilizing production equipment, shortening the production period and effectively completing a large number of factory orders in order in a short time becomes one of critical problems which are urgently required to be solved by the production manufacturing industry, and meanwhile, because the service of the manufacturing industry is complex, the problem is difficult to be solved by adopting a general scheduling model, a model close to the service of the manufacturing industry is urgently required to solve the order scheduling problem in an actual manufacturing industry factory.
Disclosure of Invention
In order to solve the problems that the existing general scheduling model cannot efficiently utilize production equipment to shorten the manufacturing period and effectively finish a large number of factory order scheduling tasks in order, the invention provides an order allocation method, which comprises the following steps:
s01: acquiring product order information of each order, wherein the product order information comprises: the order priority, the product information corresponding to the order and the production line information corresponding to the product;
s02: generating a product task corresponding to each product according to the order information of each product and adding the product task into a product task set; the product task comprises production time required for completing the product task and corresponding production line information;
s03: according to the quantity of the tasks in the product task set, production line information corresponding to each product task and production time required by each product task, obtaining order production positions of distributable product tasks on each production line, and obtaining the production time required by each production line to finish the corresponding product task as completion time;
s04: obtaining a reordering combination of order production positions on each production line and a score of each combination by using an order sorting model according to the priority of an order corresponding to a product task, the sum of production time of the product task corresponding to the order, completion time of the production line and the number of the production lines and taking a preset constraint condition as a basis;
and S05, selecting the combination with the highest score as the distribution sequence of the target orders according to the scores of all the combinations.
Further, in step S03, the specific method of obtaining the order production location of the assignable product task on each production line according to the number of tasks in the product task set, the production line information corresponding to each product task, and the production time required by each product task is as follows:
s31: dividing the product tasks to corresponding production lines according to the production line information of the product tasks, and acquiring the number of the product tasks on each production line;
s32: and obtaining the order production position of the distributable product task on each production line according to the number of the product tasks on each production line and the production time required by each product task.
Further, the preset constraint conditions in step S04 include:
each product task can only be produced on the corresponding production line;
the order production location on each production line cannot insert other product tasks at the order production location until its corresponding product task is not completed.
Further, after the step S05, the method further includes:
s06: and judging whether the background has a new order, if so, generating a product task corresponding to the product according to the product order information, judging whether the production line corresponding to each product task has an order production position capable of distributing the product task, if so, adding the product task to a product task set, and returning to the step S03.
Further, in step S04, the expression of the order ranking model is:
minOsum∩minMmax；
in the formula (I), the compound is shown in the specification,
Further, the method for acquiring the order priority in step S01 includes: and acquiring order priority by using the corresponding preset priority according to the grade of the user corresponding to the order, the order ending date and the estimated benefit of the order.
Further, in step S04, the score is obtained by:
solving the order sorting model by an OptaPlanner constraint solver according to preset constraint conditions to obtain solution values of all the reordering combinations, and evaluating the solution values by a Drools rule engine to obtain scores of the corresponding reordering combinations.
The invention also provides an order distribution system, comprising:
the order information module is used for acquiring product order information of each order, and the product order information comprises: the order priority, the product information corresponding to the order and the production line information corresponding to the product;
the product task module is used for generating a product task corresponding to each product according to each product order information and adding the product task into the product task set; the product task comprises production time required for completing the product task and corresponding production line information;
the order production position module is used for acquiring order production positions of distributable product tasks on each production line according to the quantity of the tasks in the product task set, production line information corresponding to each product task and production time required by each product task, and acquiring the production time required by each production line for finishing the corresponding product task as completion time;
the production position recombination module is used for acquiring the rearrangement sequence combination of the order production positions on each production line and the score of each combination by utilizing the order sequencing model according to the priority of the order corresponding to the product task, the sum of the production time of the product task corresponding to the order, the completion time of the production line and the number of the production lines and taking a preset constraint condition as a basis;
and the target order distribution sequence module is used for selecting the combination with the highest score as the target order distribution sequence according to the scores of all the combinations.
Further, the order information module further comprises: and the priority determining unit is used for obtaining the order priority by utilizing the corresponding preset priority through the grade of the user corresponding to the order, the order ending date and the estimated benefit of the order.
Further, the production location reconfiguration module further comprises: and the scoring unit is used for solving the order sorting model by using an OptaPlanner constraint solver according to preset constraint conditions to obtain a solution value of each reordering combination, and evaluating each solution value by using a Drools rule engine to obtain a score of the corresponding reordering combination.
Compared with the prior art, the invention at least has the following beneficial effects:
(1) the invention takes the configurable preset constraint condition as the constraint condition of the OptaPlanner constraint solver, improves the expandability of the system and can adjust the parameters and the quantity of the production equipment according to the actual condition;
(2) according to the invention, when a new order is added and the new order product task corresponds to the order production position of the distributable product task on the production line, the product task is added to the product task set and the target order distribution sequence is obtained again, the technical means can process the order which is added in an emergency manner according to the situation of the order production position on the production line, and the flexibility of order distribution is improved;
(3) the invention solves the order ordering model by an OptaPlanner constraint solver according to preset constraint conditions to obtain the solution values of each reordering combination, evaluates each solution value by a Drools rule engine to obtain the score of the corresponding reordering combination, and selects the highest-score combination as the target order distribution sequence according to the score of each combination, thereby solving the problems that the existing general production scheduling model cannot efficiently utilize production equipment to shorten the manufacturing period and effectively finish a large number of factory order production tasks in order.
Drawings
FIG. 1 is a diagram of method steps for an order distribution method and system;
FIG. 2 is a system diagram of an order allocation method and system.
Detailed Description
The following are specific embodiments of the present invention and are further described with reference to the drawings, but the present invention is not limited to these embodiments.
Example one
In order to solve the problem that the conventional general scheduling model cannot efficiently utilize production equipment to shorten the manufacturing period and effectively and orderly complete a large number of factory order scheduling tasks, the invention utilizes an order sequencing model and takes preset constraint conditions as the basis to obtain the sequencing combination of order production positions on each production line and obtain the scores of each combination, and selects the combination with the highest score as the target order distribution sequence, as shown in fig. 1, the method comprises the following steps:
s01: acquiring product order information of each order, wherein the product order information comprises: the order priority, the product information corresponding to the order and the production line information corresponding to the product;
the method for acquiring the order priority in step S01 includes: and obtaining the order priority by using the corresponding preset priority according to the grade of the user corresponding to the order, the order ending date and the estimated benefit of the order.
It should be noted that, the grade of the user corresponding to the order, the order ending date and the estimated benefit of the order are respectively provided with corresponding preset priority weights, and the order priority is obtained through the grade of the user corresponding to the order, the order ending date and the preset priority weight of the estimated benefit of the order.
S02: generating a product task corresponding to each product according to the order information of each product and adding the product task into a product task set; the product task comprises production time required for completing the product task and corresponding production line information;
s03: according to the quantity of the tasks in the product task set, production line information corresponding to each product task and production time required by each product task, obtaining order production positions of distributable product tasks on each production line, and obtaining the production time required by each production line to finish the corresponding product task as completion time;
in step S03, the specific method for obtaining the order production location of the assignable product task on each production line according to the number of tasks in the product task set, the production line information corresponding to each product task, and the production time required by each product task is as follows:
s31: dividing the product tasks to corresponding production lines according to the production line information of the product tasks, and acquiring the number of the product tasks on each production line;
s32: and obtaining the order production position of the distributable product task on each production line according to the number of the product tasks on each production line and the production time required by each product task.
S04: obtaining a reordering combination of order production positions on each production line and a score of each combination by using an order sorting model according to the priority of an order corresponding to a product task, the sum of production time of the product task corresponding to the order, completion time of the production line and the number of the production lines and taking a preset constraint condition as a basis;
in step S04, the expression of the order ranking model is:
minOsum∩minMmax；
in the formula (I), the compound is shown in the specification,
The preset constraint conditions in step S04 include:
each product task can only be produced on the corresponding production line;
the order production location on each production line cannot insert other product tasks at the order production location until its corresponding product task is not completed.
In this embodiment, the preset constraint condition may be configured according to an actual situation, and the configurable preset constraint condition is used as a constraint condition of the OptaPlanner constraint solver, so that the expandability of the system is improved, and the parameters and the number of the production devices may be adjusted according to the actual situation.
In step S04, the score is obtained by:
solving the order sorting model by an OptaPlanner constraint solver according to preset constraint conditions to obtain solution values of all the reordering combinations, and evaluating the solution values by a Drools rule engine to obtain scores of the corresponding reordering combinations.
S05: and selecting the combination with the highest score as the distribution sequence of the target orders according to the scores of all the combinations.
The invention solves the order ordering model by an OptaPlanner constraint solver according to preset constraint conditions to obtain the solution values of each reordering combination, evaluates each solution value by a Drools rule engine to obtain the score of the corresponding reordering combination, and selects the combination with the highest score as the target order distribution sequence according to the score of each combination, thereby solving the problems that the existing general production scheduling model can not efficiently utilize production equipment to shorten the manufacturing period and effectively finish a large number of factory order production scheduling tasks in order.
It should be noted that, after the target order allocation sequence is obtained, the start time and the end time of each production task on the corresponding production line and the order production location of the production line can be obtained according to the product order information of each order and the time required for producing one product.
The method further comprises the following steps after the step S05:
s06: and judging whether the background has a new order, if so, generating a product task corresponding to the product according to the product order information, judging whether the production line corresponding to each product task has an order production position capable of distributing the product task, if so, adding the product task to a product task set, and returning to the step S03.
According to the invention, when a new order is added and the new order product task corresponds to the order production position where the product tasks can be distributed on the production line, the product tasks are added to the product task set and the target order distribution sequence is obtained again.
After the step S06, the method further includes determining whether the program running time is overtime, if yes, returning to step S03 to re-acquire the target order allocation sequence, and if no, ending the process.
In this embodiment, in step S06, when the background has no new order, the judgment of the program running time is entered; and when the background has a new order and the product task of the new order corresponds to the order production position without distributable product tasks on the production line, entering the judgment of the program running time.
Example two
For better understanding of the inventive concept of the present invention, the present embodiment explains the present invention in the form of a system structure, as shown in fig. 2, an order distribution system includes:
the order information module is used for acquiring product order information of each order, and the product order information comprises: the order priority, the product information corresponding to the order and the production line information corresponding to the product;
it should be noted that, in the order information module, there are two ways to obtain product order information, one way is to interface order data of a manufacturing enterprise manufacturing process execution management system (MES) of a factory, and the other way is to manually enter order data according to the needs of a user, and after entering, the order data can be orderly managed to provide basic data for subsequent order distribution.
The order information module further comprises: and the priority determining unit is used for acquiring the order priority by utilizing the corresponding preset priority according to the level of the user corresponding to the order, the order ending date and the estimated benefit of the order.
The product task module is used for generating a product task corresponding to each product according to each product order information and adding the product task into the product task set; the product task comprises production time required for completing the product task and corresponding production line information;
the order production position module is used for acquiring order production positions of distributable product tasks on each production line according to the quantity of the tasks in the product task set, production line information corresponding to each product task and production time required by each product task, and acquiring the production time required by each production line for finishing the corresponding product task as completion time;
the production position recombination module is used for acquiring the rearrangement sequence combination of the order production positions on each production line and the score of each combination by utilizing the order sequencing model according to the priority of the order corresponding to the product task, the sum of the production time of the product task corresponding to the order, the completion time of the production line and the number of the production lines and taking a preset constraint condition as a basis;
the production position recombination module further comprises: and the scoring unit is used for solving the order sorting model by using an OptaPlanner constraint solver according to preset constraint conditions to obtain solution values of each reordering combination, and evaluating each solution value by using a Drools rule engine to obtain a score of the corresponding reordering combination.
The invention takes the configurable preset constraint condition as the constraint condition of the OptaPlanner constraint solver, improves the expandability of the system and can adjust the parameters and the quantity of the production equipment according to the actual condition.
And the target order distribution sequence module is used for selecting the combination with the highest score as the target order distribution sequence according to the scores of all the combinations.
In this embodiment, the system further includes a human-computer interaction module for manually adjusting the distribution order of the target orders and outputting the distribution order of the target orders.
The man-machine interaction module specifically comprises:
(1) an order allocation control unit: for manually adjusting the target order distribution sequence;
(2) an order distribution output unit: for outputting the target order allocation order to the client.
The invention solves the order ordering model by an OptaPlanner constraint solver according to preset constraint conditions to obtain the solution values of each reordering combination, evaluates each solution value by a Drools rule engine to obtain the score of the corresponding reordering combination, and selects the combination with the highest score as the target order distribution sequence according to the score of each combination, thereby solving the problems that the existing general production scheduling model can not efficiently utilize production equipment to shorten the manufacturing period and effectively finish a large number of factory order production scheduling tasks in order.
It should be noted that all the directional indicators (such as upper, lower, left, right, front and rear … …) in the embodiment of the present invention are only used to explain the relative position relationship between the components, the movement situation, etc. in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indicator is changed accordingly.
Moreover, descriptions of the present invention as relating to "first," "second," "a," etc. are for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicit ly indicating a number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the present invention, unless otherwise expressly specified or limited, the terms "connected," "secured," and the like are to be construed broadly, e.g., "secured" may be fixedly connected, releasably connected, or integral; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In addition, the technical solutions in the embodiments of the present invention may be combined with each other, but it must be based on the realization of those skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination of technical solutions should be considered to be absent, and is not within the protection scope of the present invention.
Claims (10)
1. An order allocation method, comprising the steps of:
s01: acquiring product order information of each order, wherein the product order information comprises: the order priority, the product information corresponding to the order and the production line information corresponding to the product;
s02: generating a product task corresponding to each product according to the order information of each product and adding the product task into a product task set; the product task comprises production time required for completing the product task and corresponding production line information;
s03: according to the quantity of the tasks in the product task set, production line information corresponding to each product task and production time required by each product task, obtaining order production positions of distributable product tasks on each production line, and obtaining the production time required by each production line to finish the corresponding product task as completion time;
s04: obtaining a reordering combination of order production positions on each production line and a score of each combination by using an order sequencing model according to the priority of an order corresponding to a product task, the sum of production time of the product task corresponding to the order, completion time of the production line and the number of the production lines and taking a preset constraint condition as a basis;
and S05, selecting the combination with the highest score as the distribution sequence of the target orders according to the scores of all the combinations.
2. The order allocation method according to claim 1, wherein in step S03, the specific method for obtaining the order production location of each assignable product task on each production line according to the number of tasks in the product task set, the production line information corresponding to each product task, and the production time required by each product task is as follows:
s31: dividing the product tasks to corresponding production lines according to the production line information of the product tasks, and acquiring the number of the product tasks on each production line;
s32: and obtaining the order production position of the distributable product task on each production line according to the number of the product tasks on each production line and the production time required by each product task.
3. The order distribution method according to claim 2, wherein the preset constraint conditions in step S04 include:
each product task can only be produced on the corresponding production line;
the order production location on each production line cannot insert other product tasks at the order production location until its corresponding product task is not completed.
4. The order distribution method according to claim 3, further comprising, after said step S05:
s06: and judging whether the background has a new order, if so, generating a product task corresponding to the product according to the product order information, judging whether the production line corresponding to each product task has an order production position capable of distributing the product task, if so, adding the product task to a product task set, and returning to the step S03.
5. The order distribution method according to claim 1, wherein in step S04, the order ranking model is expressed as:
minOsum∩minMmax；
in the formula (I), the compound is shown in the specification,
6. The order distribution method according to claim 1, wherein the order priority in step S01 is obtained by: and obtaining the order priority by using the corresponding preset priority according to the grade of the user corresponding to the order, the order ending date and the estimated benefit of the order.
7. The order distribution method according to claim 3, wherein in step S04, the score is obtained by:
solving the order ordering model by using an OptaPlanner constraint solver according to preset constraint conditions to obtain solution values of all reordering combinations, and evaluating the solution values by using a Drools rule engine to obtain scores of the corresponding reordering combinations.
8. An order distribution system, comprising:
the order information module is used for acquiring product order information of each order, and the product order information comprises: the order priority, the product information corresponding to the order and the production line information corresponding to the product;
the product task module is used for generating a product task corresponding to each product according to each product order information and adding the product task into the product task set; the product task comprises production time required for completing the product task and corresponding production line information;
the order production position module is used for acquiring order production positions of distributable product tasks on each production line according to the quantity of the tasks in the product task set, production line information corresponding to each product task and production time required by each product task, and acquiring the production time required by each production line for finishing the corresponding product task as completion time;
the production position recombination module is used for acquiring the rearrangement sequence combination of the order production positions on each production line and the score of each combination by utilizing the order sequencing model according to the priority of the order corresponding to the product task, the sum of the production time of the product task corresponding to the order, the completion time of the production line and the number of the production lines and taking a preset constraint condition as a basis;
and the target order distribution sequence module is used for selecting the combination with the highest score as the target order distribution sequence according to the score of each combination.
9. The order distribution system of claim 8, wherein the order information module further comprises: and the priority determining unit is used for acquiring the order priority by utilizing the corresponding preset priority according to the grade of the user corresponding to the order, the order ending date and the estimated benefit of the order.
10. The order distribution system of claim 8, wherein said production location reassembly module further comprises: and the scoring unit is used for solving the order sorting model by using an OptaPlanner constraint solver according to preset constraint conditions to obtain solution values of each reordering combination, and evaluating each solution value by using a Drools rule engine to obtain a score of the corresponding reordering combination.
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