CN115564358A - Cabinet arrangement method and system for conveying raw materials on production line based on heuristic algorithm - Google Patents
Cabinet arrangement method and system for conveying raw materials on production line based on heuristic algorithm Download PDFInfo
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Abstract
The invention provides a method and a system for arranging cabinets for conveying raw materials on a production line based on a heuristic algorithm, and belongs to the field of logistics transportation. The method for arranging the containers comprises the steps of firstly obtaining the daily upper limit of transport capacity, material requirements and currently-drawable containers; then, calculating the required coverage rate of each container according to the material requirement list, and arranging the containers in the sequence from large to small of the required coverage rate to generate a list of the containers to be pulled; creating a corresponding number of transportation capacity vacant positions according to the daily transportation capacity upper limit, generating an initial container arrangement scheme according to the number of vehicles waiting for the containers to be distributed, which are in an empty initial state, and calculating the fraction of the initial container arrangement scheme according to a preset container arrangement rule; and then changing schemes from two aspects of material matching and transportation capacity saving, and comparing the schemes to finally obtain an optimal cabinet arrangement scheme. The invention reduces the number of the pull cabinets to the maximum extent while matching the bill of materials, saves the cost of the pull cabinets and simultaneously arranges the conveying of the raw materials of the production line more reasonably.
Description
Technical Field
The invention belongs to the field of logistics transportation, and particularly relates to a method and a system for arranging conveying raw materials in a production line based on a heuristic algorithm.
Background
In a production and manufacturing enterprise, production raw materials need to be conveyed to a production line at regular time and quantity every day, more than one production raw material is involved, a plurality of containers in a plurality of warehouses are possibly involved, and the problem of arranging the containers is involved in how to finish a container pulling plan with the minimum transportation cost on the premise of meeting the production requirement of the production line. The problem of arranging the containers is that a person arranging the containers obtains a pull-able container list, the materials in the containers are detailed, and the containers are selectively pulled from a plurality of warehouses to a production line.
In the prior art, the cabinet arrangement problem is solved by two modes, namely manual operation and modeling. The manual cabinet arrangement is to manually match the cabinets one by one according to a material demand list provided by a production line until all demands are met, and a multi-day cabinet pulling plan is completed, so that the mode is low in efficiency, long in time consumption, incapable of reasonably utilizing daily transport capacity and causing waste of transport resources; the traditional modeling mode is to solve the optimal arrangement of the row cabinets by building a model, but along with the increase of data volume, the time consumption of solution is continuously increased, and the solution cannot be terminated in advance.
Disclosure of Invention
In view of the above-mentioned drawbacks and deficiencies of the prior art, the present invention is directed to a method and system for arranging cabinets for transporting materials in a production line based on heuristic algorithms, wherein the solving process is time-consuming. When matching the bill of materials, furthest's reduction draws cabinet quantity, saves and draws the cabinet cost, considers the priority of material simultaneously, arranges production raw materials more rationally and carries, satisfies the production demand.
In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:
in a first aspect, an embodiment of the present invention provides a method for arranging cabinets for conveying raw materials in a production line based on a heuristic algorithm, including the following steps:
s1, acquiring an upper limit of daily transport capacity;
s2, acquiring all material requirements in the time period of arranging the cabinets, and generating a material requirement list;
s3, acquiring all containers which can be pulled currently, including the positions of the containers and the details of materials contained in the containers;
s4, calculating the required coverage rate of each container in all the containers capable of being pulled according to the material requirement list, and arranging the containers in the sequence from large to small of the required coverage rate to generate a container list to be pulled;
s5, creating a corresponding number of transport capacity vacancies according to the daily transport capacity upper limit, and generating a transport capacity list according to a time sequence; the capacity vacancy is the number of cars waiting for the allocated container and is set to be empty in an initial state;
s6, generating an initial cabinet arrangement scheme according to the number of the waiting containers to be distributed, which are empty in the initial state, and calculating the fraction of the initial cabinet arrangement scheme according to a preset cabinet arrangement rule;
s7, taking out the containers with the first arrangement position from the container list to be pulled according to the coverage rate sequence required, randomly selecting an empty train number different from the last selection from the transport capacity list, arranging the containers to the train number, and generating a new scheme;
s8, calculating the score of the current scheme according to a preset cabinet arrangement rule, and comparing the score with the score of the previous scheme; if the current scheme score is larger than the previous scheme score, the pulled containers are sequentially generated into a pulled container list, meanwhile, the current container is deleted from the container list to be pulled, and the step S9 is carried out; if the score of the current scheme is less than or equal to the score of the previous scheme, abandoning the current scheme, and turning to the step S7;
s9, judging whether all the material requirements are met; if yes, entering step S10; if not, the step S7 is executed;
s10, randomly selecting a container from the pulled container list, removing the selected container from the list, and generating a new scheme; or randomly selecting two containers from the pulled container list, exchanging the train numbers of the two containers and generating a new scheme;
s11, calculating the score of the current scheme according to a preset cabinet arrangement rule, and comparing the score with the score of the previous scheme; if the current scheme score is larger than the previous scheme score, the step S12 is carried out; if the score of the current scheme is less than or equal to the score of the previous scheme, judging whether the current scheme is greater than the historical optimal scheme score before the step n, if so, entering the step S12; if not, the step S10 is carried out;
step S12, storing the current scheme into a historical optimal scheme list, and judging whether the current scheme reaches a termination condition; if not, the step S10 is carried out; if yes, go to step S13;
and S13, taking the scheme with the highest score in the historical optimal scheme list as a final cabinet arrangement scheme.
As a preferred embodiment of the present invention, the material requirement list includes material priority, material name, number, and requirement date.
As a preferred embodiment of the invention, the required coverage rate of each container is calculated in step S4, and the calculation is performed according to the formula (1):
in the formula (1), the reaction mixture is,N r representing the number of types of required parts in the container,Nrepresenting the total number of types of parts contained in the container.
As a preferred embodiment of the invention, the preset row cabinet rule sequentially comprises the following components according to the importance degree:
(1) The material requirements of the production line need to be met;
(2) The smaller the number of the containers pulled, the better;
(3) Containers of a designated warehouse need to be preferentially pulled;
(4) The material requirements of the specified kind need to be met preferentially;
and the number of the first and second electrodes,
the rules are divided into three levels, and the three variables correspond to the scheme scores and comprise a first-level score, a second-level score and a third-level score; wherein, the step (1) is divided into a first-level rule corresponding to a first-level score; dividing the step (2) into two-level rules corresponding to two-level scores; and (4) dividing the (3) and the (4) into three levels of rules, and corresponding to three levels of scores.
As a preferred embodiment of the present invention, the score of each level is calculated as follows:
first-order fraction: all containers pulled currently are obtained, missing materials and the number of the containers are screened out, corresponding negative scores are accumulated according to the number, and if no materials are missing, the score is 0;
secondary fraction: all containers pulled currently are obtained, the number is counted, and corresponding negative scores are accumulated according to the number;
and (3) third-level fraction: all containers pulled currently are obtained, the containers from an appointed warehouse are screened out, the number is counted, and corresponding positive scores are accumulated according to the number; all containers pulled currently are obtained, the pulling dates of the containers where the specified materials are located are screened out, the number of days between the pulling dates and the material demand expiration dates is calculated, and corresponding positive scores are accumulated according to the number of days.
As a preferred embodiment of the present invention, in step S9, whether the material matching is completed is determined by checking the current scheme score; if the primary score is 0, it indicates completion.
As a preferred embodiment of the present invention, the termination condition includes: the current optimal scheme is not updated within a certain time; or, the solution timing is terminated; or, artificially terminate.
In a second aspect, an embodiment of the present invention further provides a system for arranging containers for conveying raw materials in a production line based on a heuristic algorithm, where the system includes a capacity acquisition module, a material demand acquisition module, a container data acquisition module, a to-be-pulled container list generation module, a capacity list generation module, an initial plan generation module, a first plan score calculation and comparison module, a material demand determination module, a second plan generation module, a second plan score calculation and comparison module, a termination condition determination module, and a plan output module; wherein the content of the first and second substances,
the transport capacity acquisition module is used for acquiring the upper limit of the transport capacity per day;
the material demand acquisition module is used for acquiring all material demands in the time period of arranging the cabinets and generating a material demand list;
the container data acquisition module is used for acquiring all containers which can be pulled currently, including container positions and material details contained in the containers;
the to-be-pulled container list generating module is used for calculating the required coverage rate of each container in all the containers capable of being pulled according to the material requirement list, and arranging the containers in the sequence from large to small according to the required coverage rate to generate a to-be-pulled container list;
the transport capacity list generating module is used for creating transport capacity vacancies of corresponding quantity according to the upper limit of the transport capacity per day and generating a transport capacity list according to the time sequence; the capacity vacancy is the number of cars waiting for the allocated container and is set to be empty in an initial state;
the initial scheme generation module is used for generating an initial cabinet arrangement scheme according to the number of the vehicles waiting for the allocated containers in the initial state, and calculating the initial cabinet arrangement scheme fraction according to a preset cabinet arrangement rule;
the first scheme generation module is used for taking out the containers arranged at the first position from the container list to be pulled according to the coverage rate sequence, randomly selecting an empty train number different from the last selection from the transport capacity list, arranging the containers in the train number and generating a new scheme;
the first scheme score calculating and comparing module is used for calculating the score of the current scheme according to a preset cabinet arrangement rule and comparing the score with the score of the previous scheme; if the current scheme score is larger than the previous scheme score, the pulled containers are sequentially generated into a pulled container list, meanwhile, the current container is deleted from the container list to be pulled, and the current scheme is sent to the material requirement judgment module; if the score of the current scheme is less than or equal to the score of the previous scheme, abandoning the current scheme and starting a first scheme generation module;
the material requirement judging module is used for judging whether all material requirements are met; if yes, starting a second scheme generation module; if not, starting a first scheme generation module;
the second scheme generation module is used for randomly selecting a container from the pulled container list, removing the selected container from the list and generating a new scheme; or randomly selecting two containers from the pulled container list, exchanging the train numbers of the two containers and generating a new scheme;
the second scheme score calculating and comparing module is used for calculating the score of the current scheme according to a preset cabinet arrangement rule and comparing the score with the score of the previous scheme; if the score of the current scheme is larger than the score of the previous scheme, storing the current scheme into a historical optimal scheme list, and sending the current scheme to the termination condition judgment module; if the score of the current scheme is less than or equal to the score of the previous scheme, judging whether the current scheme is greater than the score of the historical optimal scheme before the step n, if so, storing the current scheme into a historical optimal scheme list, and sending the current scheme to the termination condition judging module; if not, starting a second scheme generation module;
the termination condition judging module is used for judging whether the current scheme design reaches the termination condition; if not, starting a second scheme generation module; if yes, sending the historical optimal scheme list to a scheme output module;
and the scheme output module is used for taking the scheme with the highest score in the historical optimal scheme list as a final cabinet arrangement scheme.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
the invention provides a cabinet arranging method for conveying raw materials on a production line based on a heuristic algorithm, which is divided into two stages, namely a first stage for matching a bill of materials; and after the matching of the bill of materials is finished, entering a second stage, and reducing the number of the pull cabinets. If the calculated number of the pull cabinets is not changed for a long time, the algorithm is terminated, and a cabinet arrangement result is output. The method has short solving time consumption, reduces the number of the pull cabinets to the maximum extent while matching the bill of materials, thereby saving the cost of the pull cabinets, and reasonably arranges the conveying of the raw materials of the production line by considering the priority of the materials.
Of course, not all of the advantages described above need to be achieved at the same time in the practice of any one product or method of the invention.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flowchart of the method for arranging raw materials in a production line based on a heuristic algorithm according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a first stage of a method for arranging cabinets according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a second stage of the method for arranging cabinets according to the embodiment of the present invention;
fig. 4 is a schematic diagram illustrating a classification of preset bin arrangement rules according to an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It should be apparent that the described embodiments are only some of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. It should be noted that the embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. In the description of the present invention, the terms "first", "second", "third", "fourth", and the like are used only for distinguishing the description, and are not intended to indicate or imply relative importance.
The invention provides a cabinet arranging method for conveying raw materials on a production line based on a heuristic algorithm, which is divided into two stages, namely a first stage for matching a bill of materials; and after the matching of the bill of materials is finished, entering a second stage, and reducing the number of pull cabinets. If the calculated number of the cabinet pulling is unchanged for a long time, the algorithm is terminated, and a cabinet arrangement result is output. The method has short solving time consumption, reduces the number of the pull cabinets to the maximum extent while matching the bill of materials, thereby saving the cost of the pull cabinets, and reasonably arranges the conveying of the raw materials of the production line by considering the priority of the materials.
Referring to fig. 1, the method for arranging raw materials in a production line based on a heuristic algorithm comprises the following steps:
s1, acquiring the upper limit of the daily transport capacity, namely the maximum number of containers which can be pulled every day.
In this step, the upper limit of the transport capacity can be obtained by manual filling or random generation, and the obtaining mode is not limited.
And S2, acquiring all material demands in the time period of arranging the cabinets, and generating a material demand list, wherein the material demand list comprises material priorities, material names, quantity and demand dates.
In this step, the material requirements can be divided into multiple categories, such as special, emergency and normal requirements, according to the allocation problem of the material priorities. In addition, the requirement provides the name, quantity and required date of the materials.
And S3, acquiring all containers which can be pulled currently, including the positions of the containers and the details of materials contained in the containers.
In this step, the containers are all warehouses for pull-able containers. Since the number of warehouses is not limited to one, the container location representation includes the name of the warehouse in which it is located. The material details contained in the container show the name and the quantity of the materials loaded in the container.
And S4, calculating the required coverage rate of each container in all the containers capable of being pulled according to the material requirement list, and arranging the containers in the sequence from large to small of the required coverage rate to generate a container list to be pulled.
In this step, the required coverage rate of each container is calculated according to the formula (1):
in the formula (1), the reaction mixture is,N r representing the number of types of required parts in the container,Nrepresenting the total number of types of parts contained in the container.
S5, creating a corresponding number of transport capacity vacancies according to the daily transport capacity upper limit, and generating a transport capacity list according to a time sequence; the capacity vacancy is the number of cars waiting for the container to be allocated and sets the initial state to be empty, i.e. the container is not pulled.
And S6, generating an initial cabinet arrangement scheme according to the number of the waiting containers to be distributed with the empty initial state, and calculating the initial cabinet arrangement scheme fraction according to a preset cabinet arrangement rule.
In this step, the preset row cabinet rule sequentially comprises according to the importance degree:
(1) The material requirements of the production line need to be met;
(2) The smaller the number of the containers pulled, the better;
(3) Containers of a designated warehouse need to be preferentially pulled;
(4) The material requirements of the specified kind need to be met preferentially.
As shown in fig. 4, the above rule may be divided into three levels, and the three variables corresponding to the solution score are sorted according to importance, and the former takes the latter into consideration when the solution score remains the same, and if the solution score is described as [ first level score/second level score/third level score ], the three variables include first level score, second level score and third level score. The material requirement is a task which must be completed by the discharge cabinet, so that the (1) is divided into a first-level rule corresponding to a first-level score, and the importance is highest. And (3) considering the capacity saving under the condition of meeting the requirement, so that the step (2) is divided into two-level rules corresponding to two-level scores. After the capacity is determined, the pulling sequence of the containers can be sequenced, so that the (3) and the (4) are divided into three levels of rules, the importance is the lowest, and the three levels of rules correspond to three levels of scores. The three levels have different score grades and are respectively calculated and displayed.
Subsequent scenarios involve a score comparison of the two scenarios. When the scores of different schemes are compared, the scores are compared in three levels in sequence. For example, when two scores [ 100/20/50 ] and [ 100/50/20 ] are compared, since the primary score is the same and further the secondary scores are compared, 20-straw 50, it is still higher although the tertiary score of [ 100/50/20 ] is lower. Each comparison will give priority to the first stage, and when the first stage has not changed, the comparison will continue with the second stage.
The score for each level is calculated as follows:
the first grade of the score: all containers pulled currently are obtained, missing materials and the number of the containers are screened out, corresponding negative scores are accumulated according to the number, and if no materials are missing, the score is 0;
secondary fraction: all containers pulled currently are obtained, the number is counted, and corresponding negative scores are accumulated according to the number;
and (3) third-level fraction: all containers pulled currently are obtained, the containers from an appointed warehouse are screened out, the number is counted, and corresponding positive scores are accumulated according to the number; all containers pulled currently are obtained, the pulling dates of the containers where the specified materials are located are screened out, the number of days between the pulling dates and the material demand expiration dates is calculated, and corresponding positive scores are accumulated according to the number of days.
And S7, taking out the containers with the first arrangement position from the container list to be pulled according to the coverage rate sequence required, randomly selecting an empty train number different from the last selection from the transport capacity list, arranging the containers to the train number, and generating a new scheme.
In this step, if the preference of the train number exists, probability selection can be performed according to the preference of the train number.
S8, calculating the score of the current scheme according to a preset cabinet arrangement rule, and comparing the score with the score of the previous scheme; if the current scheme score is larger than the previous scheme score, the pulled containers are sequentially generated into a pulled container list, meanwhile, the current container is deleted from the container list to be pulled, and the step S9 is carried out; and if the score of the current scheme is less than or equal to the score of the previous scheme, abandoning the current scheme and turning to the step S7.
S9, judging whether all material requirements are met; if yes, entering step S10; if not, the process proceeds to step S7.
In this step, whether the material matching is completed or not can be judged by checking the current optimal scheme score. If the primary score is 0, it may indicate completion.
As shown in fig. 2 and 3, up to this point, steps S1-S9 are taken as the first stage of the racking method, and the subsequent steps are taken as the second stage of the racking method.
Step S10, randomly selecting a container from the pulled container list, removing the selected container from the list, and generating a new scheme; or randomly selecting two containers from the pulled container list, exchanging the train numbers of the two containers and generating a new scheme.
S11, calculating the score of the current scheme according to a preset cabinet arrangement rule, and comparing the score with the score of the previous scheme; if the current scheme score is larger than the previous scheme score, the step S12 is carried out; if the score of the current scheme is smaller than or equal to the score of the previous scheme, judging whether the current scheme is larger than the historical optimal scheme score before the step n, and if so, entering the step S12; if not, the process proceeds to step S10.
Preferably, in this step, the value of n is determined according to specific situations and is not limited to a specific value. For example, taking n as 20, by performing score comparison with the historical optimal solution before 20 steps, the local optimal solution is avoided.
Step S12, storing the current scheme into a historical optimal scheme list, and judging whether the current scheme reaches a termination condition; if not, the step S10 is carried out; if yes, go to step S13;
in this step, the termination condition includes: the current optimal scheme is not updated within a certain time; or, the solution timing is terminated; or, artificially terminate. The above termination conditions are only a few of the listed items, and other termination conditions can be added according to actual situations, and the list of the conditions does not limit the invention.
And S13, taking the scheme with the highest score in the historical optimal scheme list as a final cabinet arrangement scheme.
Based on the same idea, the embodiment of the invention also provides a container arrangement system for conveying raw materials in a production line based on a heuristic algorithm, wherein the system comprises a capacity acquisition module, a material demand acquisition module, a container data acquisition module, a container list generation module to be pulled, a capacity list generation module, an initial scheme generation module, a first scheme score calculation and comparison module, a material demand judgment module, a second scheme generation module, a second scheme score calculation and comparison module, a termination condition judgment module and a scheme output module; wherein the content of the first and second substances,
the transport capacity acquisition module is used for acquiring the upper limit of the transport capacity per day;
the material demand acquisition module is used for acquiring all material demands in the time period of arranging the cabinets and generating a material demand list;
the container data acquisition module is used for acquiring all containers which can be pulled currently, including the positions of the containers and the details of materials contained in the containers;
the to-be-pulled container list generating module is used for calculating the required coverage rate of each container in all the containers capable of being pulled according to the material requirement list, arranging the containers in the sequence from large to small of the required coverage rate and generating a to-be-pulled container list;
the transport capacity list generating module is used for creating transport capacity vacancies of corresponding quantity according to the upper limit of the transport capacity per day and generating a transport capacity list according to the time sequence; the capacity vacancy is the number of cars waiting for the allocated container and is set to be empty in an initial state;
the initial scheme generation module is used for generating an initial cabinet arrangement scheme according to the number of the vehicles waiting for the allocated containers in the initial state, and calculating the initial cabinet arrangement scheme fraction according to a preset cabinet arrangement rule;
the first scheme generation module is used for taking out the first container in the ranking according to the coverage rate order from the container list to be pulled, randomly selecting an empty train number different from the last selection from the transport capacity list, arranging the container to the train number and generating a new scheme;
the first scheme score calculating and comparing module is used for calculating the score of the current scheme according to a preset cabinet arrangement rule and comparing the score with the score of the previous scheme; if the current scheme score is larger than the previous scheme score, the pulled containers are sequentially generated into a pulled container list, meanwhile, the current container is deleted from the container list to be pulled, and the current scheme is sent to the material requirement judgment module; if the score of the current scheme is less than or equal to the score of the previous scheme, abandoning the current scheme and starting a first scheme generation module;
the material requirement judging module is used for judging whether all material requirements are met; if yes, starting a second scheme generation module; if not, starting a first scheme generation module;
the second scheme generation module is used for randomly selecting a container from the pulled container list, removing the selected container from the list and generating a new scheme; or randomly selecting two containers from the pulled container list, exchanging the train numbers of the two containers and generating a new scheme;
the second scheme score calculating and comparing module is used for calculating the score of the current scheme according to a preset cabinet arrangement rule and comparing the score with the score of the previous scheme; if the score of the current scheme is larger than that of the previous scheme, the current scheme is stored in a historical optimal scheme list, and the current scheme is sent to the termination condition judgment module; if the score of the current scheme is less than or equal to the score of the previous scheme, judging whether the current scheme is greater than the score of the historical optimal scheme before the step n, if so, storing the current scheme into a historical optimal scheme list, and sending the current scheme to the termination condition judging module; if not, starting a second scheme generation module;
the termination condition judging module is used for judging whether the current scheme design reaches the termination condition; if not, starting a second scheme generation module; if yes, sending the historical optimal scheme list to a scheme output module;
and the scheme output module is used for taking the scheme with the highest score in the historical optimal scheme list as a final cabinet arrangement scheme.
It should be noted that, the cabinet arrangement system for conveying raw materials in a production line based on a heuristic algorithm in this embodiment corresponds to the cabinet arrangement method for conveying raw materials in a production line based on a heuristic algorithm, and the description and the limitation of the method are also applicable to the system, and are not described herein again.
The above description is only a preferred embodiment of the invention and an illustration of the applied technical principle and is not intended to limit the scope of the claimed invention but only to represent a preferred embodiment of the invention. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Claims (8)
1. A cabinet arranging method for conveying raw materials on a production line based on a heuristic algorithm is characterized by comprising the following steps:
s1, acquiring an upper limit of daily transport capacity;
s2, acquiring all material requirements in the time period of arranging the cabinets, and generating a material requirement list;
s3, acquiring all containers which can be pulled currently, including container positions and material details contained in the containers;
s4, calculating the required coverage rate of each container in all the containers capable of being pulled according to the material requirement list, and arranging the containers in the sequence from large to small of the required coverage rate to generate a container list to be pulled;
s5, creating a corresponding number of transport capacity vacancies according to the daily transport capacity upper limit, and generating a transport capacity list according to a time sequence; the capacity vacancy is the number of cars waiting for the allocated container and is set to be empty in an initial state;
s6, generating an initial cabinet arrangement scheme according to the number of the waiting containers to be distributed, which are empty in the initial state, and calculating the fraction of the initial cabinet arrangement scheme according to a preset cabinet arrangement rule;
s7, taking out the containers with the first arrangement position from the container list to be pulled according to the coverage rate order, randomly selecting an empty train number different from the last selection from the transport capacity list, arranging the containers to the train number, and generating a new scheme;
s8, calculating the score of the current scheme according to a preset cabinet arrangement rule, and comparing the score with the score of the previous scheme; if the current scheme score is larger than the previous scheme score, the pulled containers are sequentially generated into a pulled container list, meanwhile, the current container is deleted from the container list to be pulled, and the step S9 is carried out; if the score of the current scheme is less than or equal to the score of the previous scheme, abandoning the current scheme, and turning to the step S7;
s9, judging whether all the material requirements are met; if yes, entering step S10; if not, the step S7 is executed;
s10, randomly selecting a container from the pulled container list, removing the selected container from the list, and generating a new scheme; or randomly selecting two containers from the pulled container list, exchanging the train numbers of the two containers and generating a new scheme;
s11, calculating the score of the current scheme according to a preset cabinet arrangement rule, and comparing the score with the score of the previous scheme; if the current scheme score is larger than the previous scheme score, the step S12 is carried out; if the score of the current scheme is less than or equal to the score of the previous scheme, judging whether the current scheme is greater than the historical optimal scheme score before the step n, if so, entering the step S12; if not, the step S10 is carried out;
step S12, storing the current scheme into a historical optimal scheme list, and judging whether the current scheme reaches a termination condition; if not, the step S10 is carried out; if yes, go to step S13;
and S13, taking the scheme with the highest score in the historical optimal scheme list as a final cabinet arrangement scheme.
2. The bin ordering method for the production line conveying raw materials based on the heuristic algorithm of claim 1, wherein the list of material demands comprises material priority, material name, quantity and demand date.
3. The bin racking method for production line conveying raw material based on heuristic algorithm of claim 1, characterized in that the required coverage of each container is calculated in step S4, according to formula (1):
in the formula (1), the reaction mixture is,N r representing the number of types of required parts in the container,Nrepresenting the total number of types of parts contained in the container.
4. The method for arranging cabinets used for conveying raw materials in a production line based on the heuristic algorithm of claim 1, wherein the preset cabinet arranging rule sequentially comprises the following steps according to the importance degree:
(1) The material requirements of the production line need to be met;
(2) The smaller the number of the containers pulled, the better;
(3) Containers of a designated warehouse need to be preferentially pulled;
(4) The material requirements of the specified kind need to be met preferentially;
and the number of the first and second electrodes,
the rules are divided into three levels, and the three variables correspond to the scores of the scheme, wherein the three variables comprise a first-level score, a second-level score and a third-level score; wherein, the step (1) is divided into a first-level rule corresponding to a first-level score; dividing the step (2) into two-level rules corresponding to two-level scores; and (4) dividing the (3) and the (4) into three levels of rules, and corresponding to three levels of scores.
5. A bin ordering method for a production line conveying raw material based on a heuristic algorithm as in claim 4, characterized in that the score of each level is calculated as follows:
the first grade of the score: all containers pulled currently are obtained, missing materials and the number of the containers are screened out, corresponding negative scores are accumulated according to the number, and if no materials are missing, the score is 0;
secondary fraction: all containers pulled currently are obtained, the number is counted, and corresponding negative scores are accumulated according to the number;
and (3) third-level fraction: all containers pulled currently are obtained, the containers from an appointed warehouse are screened out, the number is counted, and corresponding positive scores are accumulated according to the number; all containers pulled currently are obtained, the pulling date of the container where the specified material is located is screened out, the interval days of the pulling date and the material demand deadline date are calculated, and corresponding positive scores are accumulated according to the days.
6. The cabinet arranging method for the production line conveying raw materials based on the heuristic algorithm of claim 5, wherein in the step S9, whether the material matching is completed is judged by checking the score of the current scheme; if the primary score is 0, it indicates completion.
7. A method as set forth in claim 1, wherein the termination condition comprises: the current optimal scheme is not updated within a certain time; or, solving for timing expiration; or, artificially terminate.
8. A counter arrangement system based on heuristic algorithm and used for conveying raw materials in a production line is characterized by comprising a transport capacity acquisition module, a material demand acquisition module, a container data acquisition module, a to-be-pulled container list generation module, a transport capacity list generation module, an initial scheme generation module, a first scheme score calculation and comparison module, a material demand judgment module, a second scheme generation module, a second scheme score calculation and comparison module, a termination condition judgment module and a scheme output module; wherein the content of the first and second substances,
the transport capacity acquisition module is used for acquiring a daily transport capacity upper limit;
the material demand acquisition module is used for acquiring all material demands in the time period of arranging the cabinets and generating a material demand list;
the container data acquisition module is used for acquiring all containers which can be pulled currently, including container positions and material details contained in the containers;
the to-be-pulled container list generating module is used for calculating the required coverage rate of each container in all the containers capable of being pulled according to the material requirement list, and arranging the containers in the sequence from large to small according to the required coverage rate to generate a to-be-pulled container list;
the transport capacity list generating module is used for creating transport capacity vacancies of corresponding quantity according to the upper limit of the transport capacity per day and generating a transport capacity list according to the time sequence; the capacity vacancy is the number of cars waiting for the allocated container and is set to be empty in an initial state;
the initial scheme generation module is used for generating an initial cabinet arrangement scheme according to the number of the vehicles waiting for the allocated containers in the initial state, and calculating the initial cabinet arrangement scheme fraction according to a preset cabinet arrangement rule;
the first scheme generation module is used for taking out the containers arranged at the first position from the container list to be pulled according to the coverage rate sequence, randomly selecting an empty train number different from the last selection from the transport capacity list, arranging the containers in the train number and generating a new scheme;
the first scheme score calculating and comparing module is used for calculating the score of the current scheme according to a preset cabinet arrangement rule and comparing the score with the score of the previous scheme; if the current scheme score is larger than the previous scheme score, the pulled containers are sequentially generated into a pulled container list, meanwhile, the current container is deleted from the container list to be pulled, and the current scheme is sent to the material requirement judgment module; if the score of the current scheme is less than or equal to the score of the previous scheme, abandoning the current scheme and starting a first scheme generation module;
the material requirement judging module is used for judging whether all material requirements are met; if yes, starting a second scheme generation module; if not, starting a first scheme generation module;
the second scheme generation module is used for randomly selecting a container from the pulled container list, removing the selected container from the list and generating a new scheme; or randomly selecting two containers from the pulled container list, exchanging the train numbers of the two containers and generating a new scheme;
the second scheme score calculating and comparing module is used for calculating the score of the current scheme according to a preset cabinet arrangement rule and comparing the score with the score of the previous scheme; if the score of the current scheme is larger than the score of the previous scheme, storing the current scheme into a historical optimal scheme list, and sending the current scheme to the termination condition judgment module; if the score of the current scheme is less than or equal to the score of the previous scheme, judging whether the current scheme is greater than the score of the historical optimal scheme before the step n, if so, storing the current scheme into a historical optimal scheme list, and sending the current scheme to the termination condition judging module; if not, starting a second scheme generation module;
the termination condition judging module is used for judging whether the current scheme design reaches the termination condition; if not, starting a second scheme generation module; if yes, sending the historical optimal scheme list to a scheme output module;
and the scheme output module is used for taking the scheme with the highest score in the historical optimal scheme list as a final cabinet arrangement scheme.
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