CN109886527B - Intelligent scheduling method and intelligent scheduling system for electric energy metering verification production based on branch definition algorithm - Google Patents
Intelligent scheduling method and intelligent scheduling system for electric energy metering verification production based on branch definition algorithm Download PDFInfo
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Abstract
The invention relates to an intelligent scheduling method and system for electric energy metering verification production based on a branch definition algorithm, wherein the method comprises the following steps: constructing a model and model constraint conditions with the lowest production cost of electric energy metering verification; acquiring an initial parameter data set according to the model constraint condition; judging whether the initial parameter data set meets the integer requirement of the model with the lowest electric energy metering verification production cost, if not, acquiring a lower boundary value and an upper boundary value of the model according to the model with the lowest electric energy metering verification production cost; branching the initial parameter data set to obtain a branched parameter data set so as to calculate the current value of the model; and judging whether the current value of the model is between the upper model limit value and the lower model limit value, if so, further branching the branched parameter data set until the branched parameter data set simultaneously meets the conditions. The invention combines the model, the model constraint condition and the branch definition algorithm to obtain the optimal schedule so as to reasonably arrange purchasing, verification production, inventory and distribution.
Description
Technical Field
The invention relates to the technical field of electric energy metering verification production, in particular to an intelligent scheduling method and an intelligent scheduling system for electric energy metering verification production based on a branch definition algorithm.
Background
The front end of the metering device supply chain needs to optimally configure the resources of purchasing, producing and distributing links. The whole supply chain comprises a plurality of suppliers at the upstream, an automatic detection center integrating storage and detection and a plurality of demand points at the downstream, including a secondary warehouse and a direct warehouse. Suppliers may offer different categories of metering devices such as single phase, three phase, sensing, etc. The detection center is provided with automatic detection lines for detecting different types of metering appliances, each detection line is formed by connecting detection tables with different functions in series, for example, the detection lines of a single meter mainly comprise appearance detection tables, error detection tables and the like, wherein the error detection tables with the same functions are connected in parallel, and the appearance detection tables are connected in series. The time required for error detection is approximately 98% of the total detection time. The error detection table body has a corresponding relation with the metering devices, namely, one table body in a certain type (appliance type) detection table body can only detect the metering devices of part (or all) modules. In addition, the metering center makes a purchase plan (new product) once a month, the purchase lead time is one month, and detection is arranged after arrival. And after the detection is finished, the three-dimensional warehouse is stored, and the storage is required to be re-detected after exceeding 6 months.
Currently, the production capacity of a grid metering center is far greater than the demand, and the metering center adopts an MTS (Make to Stock) mode to arrange production. The automation degree of the power grid metering center is higher, and the maximum verification capability is more than twice of the requirement from the verification capability. Although the demand is far less than the capacity, because the demand of the ammeter is not easy to predict, the power grid metering center adopts a strategy based on inventory production, and the maximization of the customer demand satisfaction rate is achieved by setting a higher safety inventory. However, the specific nature of the meter, and the re-testing of the tested meter in the library for more than six months, requires a fast inventory turnover, which is clearly difficult to achieve with high safety inventory and MTS strategies.
The branch definition algorithm is an algorithm that can be used to solve both pure integer programming and mixed integer programming. From the optimal solution of the original relaxation problem, the method branches discrete variables which do not meet integer conditions, and subdivides a feasible region until an integer solution of the discrete variables is obtained. The solution of integer ambiguity based on the branch definition algorithm is theoretically superior to other algorithms.
Therefore, an intelligent scheduling method and an intelligent scheduling system for electric energy metering verification production based on a branch definition algorithm are provided.
Disclosure of Invention
In view of the foregoing, the present invention has been made to provide an intelligent scheduling method and an intelligent scheduling system for electric energy metering verification production based on a branch definition algorithm, which overcome or at least partially solve the foregoing problems, and solve the problem of slow inventory turnover speed.
According to one aspect of the present invention, there is provided an intelligent scheduling method for electrical energy metering verification production based on a branch definition algorithm, comprising:
constructing an electric energy metering verification production cost minimum model based on the purchasing influence element, the verification production influence element, the inventory influence element and the distribution influence element, and constructing an electric energy metering verification production cost minimum model constraint condition based on the purchasing influence element, the verification production influence element, the inventory influence element and the distribution influence element;
selecting an initial parameter data set meeting the constraint condition of the electric energy metering verification production cost minimum model, wherein the initial parameter data set consists of initial purchasing parameters, initial verification production parameters, initial inventory parameters and initial distribution parameters;
judging whether the initial parameter data set meets the integer requirement of the electric energy metering verification production cost minimum model or not:
if yes, editing purchasing schedule parameters, verification production schedule parameters, inventory schedule parameters and distribution schedule parameters according to the initial parameter data set;
If the model is not matched with the model, acquiring a lower limit value of the model according to the initial parameter data set and the model with the lowest electric energy metering verification production cost, and acquiring an upper limit value of the model according to constraint conditions of the model with the lowest electric energy metering verification production cost and the model with the lowest electric energy metering verification production cost; branching the initial parameter data set to obtain at least two branched parameter data sets, and obtaining a current model value according to the branched parameter data sets and the model with the lowest electric energy metering verification production cost;
and judging whether the current value of the model is between an upper model limit value and a lower model limit value, if so, further branching the branched parameter data set until the branched parameter data set simultaneously meets the constraint conditions of the model with the lowest electric energy metering verification production cost and the model with the lowest electric energy metering verification production cost, and editing purchase scheduling parameters, verification production scheduling parameters, inventory scheduling parameters and distribution scheduling parameters according to the branched parameter data set.
Further, the intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm further comprises the following steps: by assigning each electric energy metering verification production cost minimum model constraint condition as an equation, an initial purchase parameter, an initial verification production parameter, an initial inventory parameter and an initial distribution parameter are calculated.
Further, the intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm further comprises the following steps:
selecting any parameter which does not meet the integer requirement from the initial parameter data set to branch, acquiring at least two branched parameter data sets, and acquiring a current value of a branched model according to the branched parameter data sets and the model with the lowest electric energy metering verification production cost;
judging whether the current value of the branched model is between the upper model limit value and the lower model limit value, if yes, branching any parameter which does not meet the integer requirement in the branched parameter data set, obtaining a re-branched parameter data set, obtaining the current value of the re-branched model according to the re-branched parameter data set, judging whether the current value of the re-branched model is between the upper model limit value and the lower model limit value, if yes, editing purchasing schedule parameters, verification production schedule parameters, inventory schedule parameters and distribution schedule parameters according to the branched parameter data set until the branched parameter data set simultaneously meets the minimum electric energy metering verification production cost model and the minimum electric energy metering verification production cost model constraint conditions.
Further, the intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm further comprises the following steps: and if the current value of the model is not between the upper model limit value and the lower model limit value, deleting the branched parameter data set.
Further, the minimum model constraint conditions for the electric energy metering verification production cost are as follows:
wherein h is i Inventory cost for product i per unit time, gamma o For the earliest delivery time of order O,for the end time, alpha, of production of product i in order O o For order O start time, +.>For the demand of product i in order O, +.>Production on day t for product i in order O, < >>To change the production cost, is->Increasing function, k i To represent the stock cost per unit time of product i +.>For the production of product i on day t, u mt To verify the bin number on day t of line m,
further, the minimum model constraint conditions for the electric energy metering verification production cost are as follows:
first, the order start time is earlier than the order production start time:
wherein alpha is o For the order O start time,representing the production start time of product i in order O;
second, the end of production time of the product in the order is earlier than the difference between the order deadline and the earliest delivery time of the order:
wherein, the liquid crystal display device comprises a liquid crystal display device,for order O production end time, beta o Order O deadline;
third, the daily order yield is less than the capacity:
wherein z is mt Indicating the influence on the verification capability of the verification line m under the condition of overhauling on the t th day; v mt Indicating the influence of the t day on the verification ability of the verification line m under the overtime condition, u m *n m *l m The assay capacity of the test line m (assay capacity=bin number×number of rounds),
fourth, the volume of the order in the production cycle meets the order demand
Wherein, the liquid crystal display device comprises a liquid crystal display device,for the demand of product i in order O, +.>Yield on day t for product i;
fifth, the production end time is earlier than the earliest delivery time, which is earlier than the order cut-off time:
wherein, gamma o For the earliest delivery time of order O,for the end time, beta, of production of product i in order O o Order O deadline;
sixth, the sum of the production per order on day t is the production on day t:
wherein, the liquid crystal display device comprises a liquid crystal display device,represents the production of product i on day t in order O, < >>Yield on day t for product i;
seventh, ensure that the products in each order are continuously produced in the production cycle:
wherein, the liquid crystal display device comprises a liquid crystal display device,representing the production of product i on day t in order O.
According to another aspect of the present invention, there is provided an intelligent scheduling system for electric energy metering verification production based on a branch definition algorithm, which implements the method described above, comprising:
the model and model constraint condition construction module is used for constructing an electric energy metering verification production cost minimum model based on the purchasing influence element, the verification production influence element, the inventory influence element and the distribution influence element, and constructing an electric energy metering verification production cost minimum model constraint condition based on the purchasing influence element, the verification production influence element, the inventory influence element and the distribution influence element;
The system comprises an initial parameter data set acquisition module, a power metering verification module and a power metering verification module, wherein the initial parameter data set acquisition module is used for selecting an initial parameter data set meeting the constraint condition of the electric energy metering verification production cost minimum model, and the initial parameter data set consists of initial purchasing parameters, initial verification production parameters, initial inventory parameters and initial distribution parameters;
the initial parameter data set screening module is used for judging whether the initial parameter data set accords with the integer requirement of the electric energy metering verification production cost minimum model, if so, editing purchasing schedule parameters, verification production schedule parameters, inventory schedule parameters and distribution schedule parameters according to the initial parameter data set;
the model value delimiting module is used for acquiring a model lower limit value according to the initial parameter data set and the electric energy metering verification production cost minimum model when the initial parameter data set does not meet the integer requirement of the electric energy metering verification production cost minimum model, and acquiring a model upper limit value according to the electric energy metering verification production cost minimum model constraint condition and the electric energy metering verification production cost minimum model;
the post-branching parameter data set acquisition module is used for branching the initial parameter data set to acquire at least two post-branching parameter data sets, and acquiring a current value of the model according to the post-branching parameter data set and the model with the lowest electric energy metering verification production cost;
And the branched parameter data set optimizing module is used for judging whether the current value of the model is between the upper model limit value and the lower model limit value, if so, further branching the branched parameter data set until the branched parameter data set simultaneously meets the constraint conditions of the model with the lowest electric energy metering verification production cost and the model with the lowest electric energy metering verification production cost, and editing purchase scheduling parameters, verification production scheduling parameters, inventory scheduling parameters and distribution scheduling parameters according to the branched parameter data set.
Further, the initial parameter data set acquisition module is further configured to calculate an initial procurement parameter, an initial verification production parameter, an initial inventory parameter, and an initial distribution parameter by assigning each electric energy metering verification production cost minimum model constraint condition to be an equation.
Further, the post-branching parameter data set acquisition module is further used for selecting any parameter which does not meet the integer requirement from the initial parameter data set to branch, acquiring at least two post-branching parameter data sets, and acquiring a current value of the post-branching model according to the post-branching parameter data sets and the electric energy metering verification production cost minimum model;
the post-branching parameter data set optimizing module is further configured to determine whether a current value of the post-branching model is between an upper model limit value and a lower model limit value, if yes, branch any parameter of the post-branching parameter data set that does not meet an integer requirement to obtain a post-branching parameter data set, obtain a post-branching model current value according to the post-branching parameter data set, determine whether the post-branching model current value is between the upper model limit value and the lower model limit value, if yes, edit the purchase scheduling parameter, the production verification scheduling parameter, the inventory scheduling parameter and the distribution scheduling parameter according to the post-branching parameter data set until the post-branching parameter data set simultaneously meets a model with a minimum electric energy metering verification production cost and a model constraint condition with a minimum electric energy metering verification production cost.
Further, the post-branching parameter data set optimizing module is further configured to delete the post-branching parameter data set when the current value of the model is not between the upper-model boundary value and the lower-model boundary value.
Compared with the prior art, the invention has the following advantages:
1. the intelligent scheduling method and the intelligent scheduling system for electric energy metering verification production based on the branch definition algorithm adopt the branch definition algorithm, are suitable for predicting the unpredictable optimal scheduling, have few calculation steps, high calculation efficiency and good adaptability to sudden conditions such as bill insertion and the like.
2. According to the intelligent scheduling method and the intelligent scheduling system for electric energy metering verification production based on the branch definition algorithm, the purchasing scheduling parameters, verification production scheduling parameters, inventory scheduling parameters and distribution scheduling parameters are obtained by combining the electric energy metering verification production cost minimum model, the electric energy metering verification production cost minimum model constraint condition and the branch definition algorithm, and purchasing, verification production, inventory turnover and distribution are reasonably arranged through control cost.
3. According to the intelligent scheduling method and the intelligent scheduling system for the electric energy metering verification production based on the branch definition algorithm, which are disclosed by the invention, the intelligent scheduling of the whole flow of purchasing goods, verifying production and distribution is obtained, so that the defect of manual experience is effectively avoided, and the scientific formulation and efficient execution of a metering production plan are realized.
4. The intelligent scheduling method and the intelligent scheduling system for electric energy metering verification production based on the branch definition algorithm not only can meet the meter using requirements of a power supply unit and a station (a secondary warehouse and a direct warehouse) thereof in time, but also can greatly reduce the center inventory and the production cost, and provide powerful support for realizing intelligent operation of a metering center.
Drawings
The invention is further described below with reference to the drawings and examples.
FIG. 1 is a step diagram of an intelligent scheduling method for electrical energy metering verification production based on a branch definition algorithm of the present invention;
FIG. 2 is a production scheduling logic diagram of the present invention for production by order;
FIG. 3 is a flow chart of a process for solving a minimum model for electric energy metering verification production cost according to a branch definition algorithm;
FIG. 4 is a block diagram of an intelligent scheduling system for electrical energy metering verification production based on a branch definition algorithm of the present invention;
FIG. 5 is a schematic process diagram of the application of the intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It will be understood by those skilled in the art that all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs unless defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The invention aims to rely on an intelligent scheduling system for electric energy metering verification production to realize intelligent production of electric energy metering verification. Firstly, guaranteeing a hundred percent completion rate according to an MTO (make to order) strategy under dynamic order requirements to arrange a production plan, and refining the production plan to the day; on the basis, according to an advanced scheduling theory, a mathematical model of the problem is constructed by adopting an operation optimization method based on the requirement of a dynamic order, the current detection situation of a metering appliance and constraint conditions so as to realize intelligent scheduling, and a daily production plan and a daily distribution plan are output, so that the use table requirement of a downstream station (a secondary warehouse and a direct warehouse) is met, the capacity is fully utilized, the continuity and the stability of production are ensured, and the overtime of a detection line worker is reduced as much as possible. Therefore, the core of the invention is that: how to make scientific production schedule according to dynamic orders under the condition of ensuring hundred percent of satisfaction rate, not only can meet all orders, but also can improve the stock turnover speed, reduce the stock, and meanwhile, the whole work efficiency is improved by better linking with the stock and distribution.
Fig. 1 is a step diagram of an intelligent scheduling method for electric energy metering verification production based on a branch definition algorithm, referring to fig. 1, the intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm provided by the invention comprises the following steps:
s110, constructing an electric energy metering verification production cost minimum model based on purchase influencing elements, verification production influencing elements, inventory influencing elements and distribution influencing elements, and constructing an electric energy metering verification production cost minimum model constraint condition based on the purchase influencing elements, the verification production influencing elements, the inventory influencing elements and the distribution influencing elements;
specifically, before constructing the electric energy metering verification production cost minimum model and constraint conditions of the electric energy metering verification production cost minimum model, firstly, researching the production current situation, collecting data and inducing problems to determine a production scheduling logic diagram for production according to orders according to the production current situation and the problems, and constructing the electric energy metering verification production cost minimum model according to the production scheduling logic diagram. As shown in fig. 2, the production schedule logic includes: warehousing new products; sample comparison, a totipotency experiment and spot check, wherein the mutual inductor does not perform the sample comparison and the totipotency experiment, directly performs the spot check, and the acquisition terminal does not perform the spot check; reading a new product stock, matching the new product stock with the order requirement, wherein part of the new product which cannot be met is output, and adding reasons such as insufficient new product; reading order pool information; estimating a demand arrangement production planning amount; review the plan, execution and plan made, judge whether there is newly increased demand (demand fluctuation, newly increased urgent bill); if there is a new demand, calling the safety stock and judging whether the safety stock meets all emergency orders; if the safety stock does not meet all emergency orders, judging whether the residual capacity is matched one by one according to the order priority; if the residual capacity is matched one by one according to the order priority, outputting an order for arranging production and inserting the order to adjust a main production plan and make a production plan; establishing a production scheduling model according to the production plan, and selecting an intelligent scheduling optimization algorithm to obtain the production plan and the scheduling plan; judging whether the distribution is executed according to the plan; and if the delivery is not executed according to the plan, performing delay punishment and delivering.
The data collected by the current state of production is extracted from the data of the marketing business application system, the metering production scheduling platform, the metering storage system and the electricity consumption information acquisition system, so that the later data storage and preprocessing and data checking are realized, the data quality and consistency of the multi-system data are ensured, and the reliability and the authenticity of the data sources are ensured.
S120, selecting an initial parameter data set meeting the constraint condition of the electric energy metering verification production cost minimum model, wherein the initial parameter data set consists of initial purchasing parameters, initial verification production parameters, initial inventory parameters and initial distribution parameters;
s130, judging whether the initial parameter data set meets the integer requirement of the electric energy metering verification production cost minimum model:
s140, if the parameters are met, editing purchase scheduling parameters, verification production scheduling parameters, inventory scheduling parameters and distribution scheduling parameters according to the initial parameter data set;
s150, if the model is not matched with the initial parameter data set, acquiring a model lower bound value according to the initial parameter data set and the electric energy metering verification production cost minimum model, and acquiring a model upper bound value according to the electric energy metering verification production cost minimum model constraint condition and the electric energy metering verification production cost minimum model; branching the initial parameter data set to obtain at least two branched parameter data sets, and obtaining a current model value according to the branched parameter data sets and the model with the lowest electric energy metering verification production cost;
S160, judging whether the current value of the model is between the upper limit value of the model and the lower limit value of the model, if so, further branching the branched parameter data set until the branched parameter data set simultaneously meets the constraint conditions of the model with the lowest electric energy metering verification production cost and the model with the lowest electric energy metering verification production cost, and editing purchase scheduling parameters, verification production scheduling parameters, inventory scheduling parameters and distribution scheduling parameters according to the branched parameter data set. Here, the schedule means a schedule order table.
Specifically, as shown in fig. 3, the process of solving the lowest model of the electric energy metering verification production cost according to the branch definition algorithm is as follows: determining a new demand by inquiring the new demand, the demand for supplementing the library and the completion condition of the inquiry plan, determining a demand to be verified and a demand to be distributed by inquiring the finished product inventory of the center and the new product inventory of the center and combining the new demand, performing redundant scheduling by taking the demand to be verified, the demand to be distributed, the existing plan, the batch inventory, the verification capability and the distribution capability as input data, outputting the verification plan and the distribution plan, judging whether the verification plan and the distribution plan meet the demand, if so, further judging whether all the schedules meet the demand, if so, performing plan confirmation and outputting all the schedules, such as purchasing schedule, verification production schedule, inventory schedule and distribution schedule; if the verification plan and the distribution plan do not meet the requirements, any one of parameter adjustment, adjustment or feedback giving is performed until all schedules meet the requirements.
The intelligent scheduling method and the intelligent scheduling system for electric energy metering verification production based on the branch definition algorithm adopt the branch definition algorithm, are suitable for predicting the unpredictable optimal scheduling, have few calculation steps, high calculation efficiency and good adaptability to sudden conditions such as bill insertion and the like.
The intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm combines the electric energy metering verification production cost minimum model, the electric energy metering verification production cost minimum model constraint condition and the branch definition algorithm to acquire purchasing scheduling parameters, verification production scheduling parameters, inventory scheduling parameters and distribution scheduling parameters, and reasonably arranges purchasing, verification production, inventory turnover and distribution through control cost.
The intelligent scheduling method for the electric energy metering verification production based on the branch definition algorithm acquires intelligent scheduling of the whole flow of purchasing goods, verifying production and distribution, effectively avoids the defect of manual experience, and realizes scientific formulation and efficient execution of metering production plans.
The intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm not only timely meets the meter using requirements of a power supply unit and a station (a secondary warehouse and a direct warehouse) thereof, but also greatly reduces the center inventory and the production cost, and provides a powerful support for realizing intelligent operation of a metering center.
Further, the intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm further comprises the following steps: by assigning each electric energy metering verification production cost minimum model constraint condition as an equation, an initial purchase parameter, an initial verification production parameter, an initial inventory parameter and an initial distribution parameter are calculated.
Further, the intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm further comprises the following steps:
selecting any parameter which does not meet the integer requirement from the initial parameter data set to branch, acquiring at least two branched parameter data sets, and acquiring a current value of a branched model according to the branched parameter data sets and the model with the lowest electric energy metering verification production cost;
judging whether the current value of the branched model is between the upper model limit value and the lower model limit value, if yes, branching any parameter which does not meet the integer requirement in the branched parameter data set, obtaining a re-branched parameter data set, obtaining the current value of the re-branched model according to the re-branched parameter data set, judging whether the current value of the re-branched model is between the upper model limit value and the lower model limit value, if yes, editing purchasing schedule parameters, verification production schedule parameters, inventory schedule parameters and distribution schedule parameters according to the branched parameter data set until the branched parameter data set simultaneously meets the minimum electric energy metering verification production cost model and the minimum electric energy metering verification production cost model constraint conditions.
Further, the intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm further comprises the following steps: and if the current value of the model is not between the upper model limit value and the lower model limit value, deleting the branched parameter data set.
The inventory turnover speed is improved by controlling the inventory cost, the occupied time of the produced order in the inventory is minimized, and the produced order is distributed as soon as possible so as to move out of the inventory space; the overtime cost is controlled to arrange overtime as little as possible, so that the capacity utilization in the normal working time is promoted; the fluctuation of production is reduced by controlling the production fluctuation punishment cost, so that the daily planning arrangement is ensured to be uniform and stable as much as possible; the empty time of the table body is reduced by controlling the production preparation cost, and the full utilization of the productivity is ensured.
Further, the minimum model constraint conditions for the electric energy metering verification production cost are as follows:
wherein h is i Inventory cost for product i per unit time, gamma o For the earliest delivery time of order O,for the end time, alpha, of production of product i in order O o For order O start time, +.>For the demand of product i in order O, +.>Production on day t for product i in order O, < >>To change the production cost, is- >Increasing function, k i To represent the stock cost per unit time of product i +.>For the production of product i on day t, u mt To verify the bin number on day t of line m,
further, the minimum model constraint conditions for the electric energy metering verification production cost are as follows:
first, the order start time is earlier than the order production start time:
wherein alpha is o For the order O start time,representing the production start time of product i in order O;
second, the end of production time of the product in the order is earlier than the difference between the order deadline and the earliest delivery time of the order:
wherein, the liquid crystal display device comprises a liquid crystal display device,for order O production end time, beta o Order O deadline;
third, the daily order yield is less than the capacity:
wherein z is mt Indicating the influence on the verification capability of the verification line m under the condition of overhauling on the t th day; v mt Indicating the influence of the t day on the verification ability of the verification line m under the overtime condition, u m *n m *l m The assay capacity of the test line m (assay capacity=bin number×number of rounds),
fourth, the volume of the order in the production cycle meets the order demand
Wherein, the liquid crystal display device comprises a liquid crystal display device,for the demand of product i in order O, +.>Yield on day t for product i;
fifth, the production end time is earlier than the earliest delivery time, which is earlier than the order cut-off time:
Wherein, gamma o For the earliest delivery time of order O,for the end time, beta, of production of product i in order O o Order O deadline;
sixth, the sum of the production per order on day t is the production on day t:
wherein, the liquid crystal display device comprises a liquid crystal display device,represents the production of product i on day t in order O, < >>Yield on day t for product i;
seventh, ensure that the products in each order are continuously produced in the production cycle:
wherein, the liquid crystal display device comprises a liquid crystal display device,representing the production of product i on day t in order O.
For the purposes of simplicity of explanation, the methodologies are shown and described as a series of acts, it is to be understood and appreciated by one of ordinary skill in the art that the methodologies are not limited by the order of acts, as some acts may, in accordance with the methodologies, take place in other order or concurrently. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred embodiments, and that the acts are not necessarily required by the embodiments of the invention.
Fig. 4 is a block diagram of an intelligent scheduling system for electric energy metering verification production based on a branch definition algorithm according to the present invention, referring to fig. 4, the intelligent scheduling system for electric energy metering verification production based on a branch definition algorithm for implementing the method according to the present invention includes:
The model and model constraint condition construction module is used for constructing an electric energy metering verification production cost minimum model based on the purchasing influence element, the verification production influence element, the inventory influence element and the distribution influence element, and constructing an electric energy metering verification production cost minimum model constraint condition based on the purchasing influence element, the verification production influence element, the inventory influence element and the distribution influence element;
the system comprises an initial parameter data set acquisition module, a power metering verification module and a power metering verification module, wherein the initial parameter data set acquisition module is used for selecting an initial parameter data set meeting the constraint condition of the electric energy metering verification production cost minimum model, and the initial parameter data set consists of initial purchasing parameters, initial verification production parameters, initial inventory parameters and initial distribution parameters;
the initial parameter data set screening module is used for judging whether the initial parameter data set accords with the integer requirement of the electric energy metering verification production cost minimum model, if so, editing purchasing schedule parameters, verification production schedule parameters, inventory schedule parameters and distribution schedule parameters according to the initial parameter data set;
the model value delimiting module is used for acquiring a model lower limit value according to the initial parameter data set and the electric energy metering verification production cost minimum model when the initial parameter data set does not meet the integer requirement of the electric energy metering verification production cost minimum model, and acquiring a model upper limit value according to the electric energy metering verification production cost minimum model constraint condition and the electric energy metering verification production cost minimum model;
The post-branching parameter data set acquisition module is used for branching the initial parameter data set to acquire at least two post-branching parameter data sets, and acquiring a current value of the model according to the post-branching parameter data set and the model with the lowest electric energy metering verification production cost;
and the branched parameter data set optimizing module is used for judging whether the current value of the model is between the upper model limit value and the lower model limit value, if so, further branching the branched parameter data set until the branched parameter data set simultaneously meets the constraint conditions of the model with the lowest electric energy metering verification production cost and the model with the lowest electric energy metering verification production cost, and editing purchase scheduling parameters, verification production scheduling parameters, inventory scheduling parameters and distribution scheduling parameters according to the branched parameter data set.
The invention applies the electric energy metering verification production cost lowest model established by the operation optimization theory, the logistics integration and the intelligent production scheduling theory, runs the electric energy metering verification production cost lowest model in an intelligent scheduling system of electric energy metering verification production, and depends on the existing MDS system (Measurement of Integrated Production Dispatching System, provincial metering center production scheduling platform) and SG-186 system (national grid company integration enterprise information integration platform) of the Tianjin power grid to realize the intellectualization of metering verification production scheduling.
The intelligent scheduling method and the intelligent scheduling system for electric energy metering verification production based on the branch definition algorithm adopt the branch definition algorithm, are suitable for predicting the unpredictable optimal scheduling, have few calculation steps, high calculation efficiency and good adaptability to sudden conditions such as bill insertion and the like.
The intelligent scheduling system for electric energy metering verification production based on the branch definition algorithm is combined with the electric energy metering verification production cost minimum model, the constraint condition of the electric energy metering verification production cost minimum model and the branch definition algorithm to acquire purchasing scheduling parameters, verification production scheduling parameters, inventory scheduling parameters and distribution scheduling parameters, and purchasing, verification production, inventory turnover and distribution are reasonably arranged through control cost.
The intelligent scheduling system for electric energy metering verification production based on the branch definition algorithm acquires intelligent scheduling of the whole flow of purchasing goods, verifying production and distribution, effectively avoids the defect of manual experience, and realizes scientific formulation and efficient execution of metering production plans.
The intelligent scheduling system for electric energy metering verification production based on the branch definition algorithm not only timely meets the meter using requirements of a power supply unit and a station (a secondary warehouse and a direct warehouse) thereof, but also greatly reduces the center inventory and the production cost, and provides a powerful support for realizing intelligent operation of a metering center.
Further, the initial parameter data set acquisition module is further configured to calculate an initial procurement parameter, an initial verification production parameter, an initial inventory parameter, and an initial distribution parameter by assigning each electric energy metering verification production cost minimum model constraint condition to be an equation.
Further, the post-branching parameter data set acquisition module is further used for selecting any parameter which does not meet the integer requirement from the initial parameter data set to branch, acquiring at least two post-branching parameter data sets, and acquiring a current value of the post-branching model according to the post-branching parameter data sets and the electric energy metering verification production cost minimum model;
the post-branching parameter data set optimizing module is further configured to determine whether a current value of the post-branching model is between an upper model limit value and a lower model limit value, if yes, branch any parameter of the post-branching parameter data set that does not meet an integer requirement to obtain a post-branching parameter data set, obtain a post-branching model current value according to the post-branching parameter data set, determine whether the post-branching model current value is between the upper model limit value and the lower model limit value, if yes, edit the purchase scheduling parameter, the production verification scheduling parameter, the inventory scheduling parameter and the distribution scheduling parameter according to the post-branching parameter data set until the post-branching parameter data set simultaneously meets a model with a minimum electric energy metering verification production cost and a model constraint condition with a minimum electric energy metering verification production cost.
Further, the post-branching parameter data set optimizing module is further configured to delete the post-branching parameter data set when the current value of the model is not between the upper-model boundary value and the lower-model boundary value.
For system embodiments, the description is relatively simple as it is substantially similar to method embodiments, and reference is made to the description of method embodiments for relevant points.
The application principle process of the intelligent scheduling method for electric energy metering verification production based on the branch definition algorithm is shown in fig. 5:
analyzing the influence factor data; analyzing the relevance between the influence factor data; performing advanced scheduling theory research according to the relevance between the influence factor data; designing a data model; establishing a mathematical model; extracting data from the data of the marketing business application system, the metering production scheduling platform, the metering warehousing system and the electricity consumption information acquisition system according to the relevance among the influence factor data; an intelligent scheduling system for electric energy metering verification production is built, and a scheduling plan is realized according to the extracted data and a mathematical model; the scheduling plan is continuously optimized.
The model of the invention takes the lowest inventory cost and production cost (production preparation cost, production fluctuation punishment cost and overtime production cost) as objective functions. The construction of the model fully considers the restriction relation among production, stock and distribution. The finished products after production are put in storage to occupy a certain inventory space, meanwhile, the inventory capacity can restrict production, the delivered finished products can be moved out of the storage space, and the inventory space is reserved for production. The relationships between the constituent elements and the influencing factors are as follows: the method comprises the steps of submitting the requirements of the sub-warehouse to an order pool, distributing the requirements of the sub-warehouse to a central warehouse and a production line by the order pool, storing finished products to the central warehouse by the production line according to inventory capacity (inventory capacity, inventory in-warehouse quantity and inventory in-transit quantity), and calling new products out of the central warehouse by the production line according to production requirements, wherein the conditions required to be met include: the requirements of the sub-warehouse are timely distributed according to the limit of the number of vehicle storage bits and the number of storage bits occupied by unit products, the unit inventory cost of the products in the central warehouse is lowest, the order time window, the product types and the required quantity in the order pool, the fixed production cost of the platform body is lowest and the fixed overtime cost is lowest in the production process, and in the calculation of the fixed overtime cost, the occupancy rate of the number of the storage bits of the platform body, the verification wheel number of the platform body and the overtime verification coefficient are considered.
The distribution process of the electric energy metering device is as follows: the dispensing of the metering device comprises three layers: the first layer is a metering center, and the metering center comprises a center library and a detection center; the second layer is each sub-library (regional library); the third layer is each station (power division). The metering center is responsible for detecting the metering device and distributing the various sub-libraries. The station is responsible for carrying out demand prediction, plan reporting and the like of the metering device, the sub-warehouse is responsible for summarizing the demands of each station and reporting the demands to the metering center, and the metering center carries out demand distribution based on the principle of mainly sub-warehouse and auxiliary center warehouse after receiving the demand application of each sub-warehouse.
The model comprehensively considers factors such as central safety stock, a shift-in-turn system, equipment checking capacity, an overhaul plan thereof and the like, sorts and classifies the influencing factors, and determines verification, stock and overtime constraints in the model. Finally, a metering production plan optimization model based on mixed integer programming is established, wherein the cost and the inventory minimum are taken as objective functions, and daily arrival plans, verification plans and distribution plans are taken as decision variables.
The output of the model of the present invention includes a day verification plan and a delivery plan. The daily verification plan is a plan which is compiled in daily units and used for guiding detection/verification of a metering center according to factors such as actual demand, arrival conditions, inventory conditions, production capacity and the like in the period. The plan is balanced and regulated in combination with the safety stock condition of the metering center, and then the auxiliary decision of daily production quantity and daily production condition is realized. The distribution plan is a distribution plan which is prepared by outputting a demand order with a distribution time window and by taking a day as a unit and is refined to each power supply company and each product according to the factors such as actual demand, verification conditions, inventory conditions, distribution capacity and the like in the demand order period. The plan is linked with production, inventory and arrival conditions to help the manager to make an auxiliary decision on the daily delivery conditions within the order time window.
The model adopts a mixed integer programming method, realizes intelligent scheduling of the whole flow of arrival, verification and distribution, effectively avoids the defect of manual experience, and realizes scientific formulation and efficient execution of metering production plans.
In the electric energy metering verification production link, the invention uses the advanced planning scheduling technology to research and establish a business linkage cooperation model, drives business processes to be connected in a seamless way and to be executed automatically, and constructs a new mode of cooperative operation of each link of metering material supply. The transition of the metrological production from a "planning driven" to a "data driven" mode is achieved.
According to the demand forecasting result, the purchasing and production plan is formulated. And analyzing influence factors of intelligent production scheduling to obtain index parameters required by scheduling optimization, and determining a production plan by adopting an optimized scheduling model according to an advanced scheduling theory. The production schedule is comprehensively considered by combining five aspects of demand, purchase, production, storage and distribution management. Through analysis, the system mainly comprises the aspects of demand prediction, material supply period, material arrival planning, central safety stock, wheel shift working system, equipment checking capability, maintenance planning, transportation and the like. The intelligent production schedule is determined by system parameters and decision principles, and related theories of the parameters and the decision principles limit the parameter indexes such as inventory capacity, warehouse in-warehouse capacity, verification capacity, overtime and overhaul conditions, distribution capacity, safety inventory and the like of the metering center, so that monthly arrival plans, verification plans and distribution plans can be determined by a mathematical model established by the advanced scheduling theory.
In addition, the intelligent scheduling system for electric energy metering verification production is built, intelligent production scheduling is carried out according to input data, the purpose of intelligent production scheduling is achieved, distribution delay and product shortage are reduced, inventory turnover rate is improved, the utilization rate of a detection line is improved, and purchasing accuracy is improved, so that powerful support is provided for intelligent operation of power grid logistics.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (6)
1. An intelligent scheduling method for electric energy metering verification production based on a branch definition algorithm is characterized by comprising the following steps:
constructing an electric energy metering verification production cost minimum model based on the purchasing influence element, the verification production influence element, the inventory influence element and the distribution influence element, and constructing an electric energy metering verification production cost minimum model constraint condition based on the purchasing influence element, the verification production influence element, the inventory influence element and the distribution influence element;
Selecting an initial parameter data set meeting the constraint condition of the electric energy metering verification production cost minimum model, wherein the initial parameter data set consists of initial purchasing parameters, initial verification production parameters, initial inventory parameters and initial distribution parameters;
judging whether the initial parameter data set meets the integer requirement of the electric energy metering verification production cost minimum model or not:
if yes, editing purchasing schedule parameters, verification production schedule parameters, inventory schedule parameters and distribution schedule parameters according to the initial parameter data set;
if the model is not matched with the model, acquiring a lower limit value of the model according to the initial parameter data set and the model with the lowest electric energy metering verification production cost, and acquiring an upper limit value of the model according to constraint conditions of the model with the lowest electric energy metering verification production cost and the model with the lowest electric energy metering verification production cost; branching the initial parameter data set to obtain at least two branched parameter data sets, and obtaining a current model value according to the branched parameter data sets and the model with the lowest electric energy metering verification production cost;
judging whether the current value of the model is between an upper model limit value and a lower model limit value, if so, further branching the branched parameter data set until the branched parameter data set simultaneously meets the constraint conditions of the model with the lowest electric energy metering verification production cost and the model with the lowest electric energy metering verification production cost, and editing purchase scheduling parameters, verification production scheduling parameters, inventory scheduling parameters and distribution scheduling parameters according to the branched parameter data set;
Further comprises: calculating initial purchase parameters, initial verification production parameters, initial inventory parameters and initial distribution parameters by giving the lowest model constraint conditions for the production cost of each electric energy metering verification;
the lowest model objective function of the electric energy metering verification production cost is as follows:
wherein h is i Inventory cost for product i per unit time, gamma O For the earliest delivery time of order O,product i production end time, alpha, in order O 0 For order O start time, +.>For the demand of product i in order O, +.>Production on day t for product i in order O, < >>To change the production cost, is->Is the stock cost per unit time of product i,for the production of product i on day t, u mt To verify the bin number on day t of line m,
the lowest model constraint conditions of the electric energy metering verification production cost are as follows:
first, the order start time is earlier than the order production start time:
wherein alpha is 0 For the order O start time,representing the production start time of product i in order O;
second, the end of production time of the product in the order is earlier than the difference between the order deadline and the earliest delivery time of the order:
wherein, the liquid crystal display device comprises a liquid crystal display device,for order O production end time, beta 0 Order O deadline;
third, the daily order yield is less than the capacity:
Wherein z is mt Indicating the influence on the verification capability of the verification line m under the condition of overhauling on the t th day; v mt Indicating the influence of the t day on the verification ability of the verification line m under the overtime condition, u m *n m *l m Indicating the verification capability of the test line m; wherein, the verification capability=bin number×number of table body number×number of wheel,
fourth, the volume of the order in the production cycle meets the order demand
Wherein, the liquid crystal display device comprises a liquid crystal display device,for the demand of product i in order O, +.>Yield on day t for product i;
fifth, the production end time is earlier than the earliest delivery time, which is earlier than the order cut-off time:
wherein, gamma O For the earliest delivery time of order O,for the end time, beta, of production of product i in order O O Order O deadline;
sixth, the sum of the production per order on day t is the production on day t:
wherein, the liquid crystal display device comprises a liquid crystal display device,represents the production of product i on day t in order O, < >>Yield on day t for product i;
seventh, ensure that the products in each order are continuously produced in the production cycle:
wherein, the liquid crystal display device comprises a liquid crystal display device,representing the production of product i on day t in order O.
2. The branch definition algorithm-based intelligent scheduling method for power metering verification production of claim 1, further comprising:
selecting any parameter which does not meet the integer requirement from the initial parameter data set to branch, acquiring at least two branched parameter data sets, and acquiring a current value of a branched model according to the branched parameter data sets and the model with the lowest electric energy metering verification production cost;
Judging whether the current value of the branched model is between the upper model limit value and the lower model limit value, if so, branching any parameter which does not meet the integer requirement in the branched parameter data set, obtaining a re-branched parameter data set, obtaining the current value of the re-branched model according to the re-branched parameter data set, judging whether the current value of the re-branched model is between the upper model limit value and the lower model limit value, and if so, editing purchasing schedule parameters, verifying production schedule parameters, inventory schedule parameters and distribution schedule parameters according to the branched parameter data set until the branched parameter data set simultaneously meets the constraint conditions of the model with the lowest electric energy metering verification production cost and the model with the lowest electric energy metering verification production cost.
3. The branch definition algorithm-based intelligent scheduling method for power metering verification production of claim 2, further comprising: and if the current value of the model is not between the upper model limit value and the lower model limit value, deleting the branched parameter data set.
4. An intelligent scheduling system for electric energy metering verification production based on a branch definition algorithm for realizing the intelligent scheduling method for electric energy metering verification production based on claim 1, comprising:
The model and model constraint condition construction module is used for constructing an electric energy metering verification production cost minimum model based on the purchasing influence element, the verification production influence element, the inventory influence element and the distribution influence element, and constructing an electric energy metering verification production cost minimum model constraint condition based on the purchasing influence element, the verification production influence element, the inventory influence element and the distribution influence element;
the system comprises an initial parameter data set acquisition module, a power metering verification module and a power metering verification module, wherein the initial parameter data set acquisition module is used for selecting an initial parameter data set meeting the constraint condition of the electric energy metering verification production cost minimum model, and the initial parameter data set consists of initial purchasing parameters, initial verification production parameters, initial inventory parameters and initial distribution parameters;
the initial parameter data set screening module is used for judging whether the initial parameter data set accords with the integer requirement of the electric energy metering verification production cost minimum model, if so, editing purchasing schedule parameters, verification production schedule parameters, inventory schedule parameters and distribution schedule parameters according to the initial parameter data set;
the model value delimiting module is used for acquiring a model lower limit value according to the initial parameter data set and the electric energy metering verification production cost minimum model when the initial parameter data set does not meet the integer requirement of the electric energy metering verification production cost minimum model, and acquiring a model upper limit value according to the electric energy metering verification production cost minimum model constraint condition and the electric energy metering verification production cost minimum model;
The post-branching parameter data set acquisition module is used for branching the initial parameter data set to acquire at least two post-branching parameter data sets, and acquiring a current value of the model according to the post-branching parameter data set and the model with the lowest electric energy metering verification production cost;
the post-branching parameter data set optimizing module is used for judging whether the current value of the model is between the upper limit value and the lower limit value of the model, if so, further branching the post-branching parameter data set until the post-branching parameter data set simultaneously meets the constraint conditions of the model with the lowest electric energy metering verification production cost and the model with the lowest electric energy metering verification production cost, and editing purchase scheduling parameters, verification production scheduling parameters, inventory scheduling parameters and distribution scheduling parameters according to the post-branching parameter data set;
the initial parameter data set acquisition module is further used for calculating initial purchase parameters, initial verification production parameters, initial inventory parameters and initial distribution parameters by giving the lowest model constraint conditions for the production cost of each electric energy metering verification.
5. The electrical energy metering verification production intelligent scheduling system based on the branch definition algorithm of claim 4, wherein,
The post-branching parameter data set acquisition module is further used for selecting any parameter which does not meet the integer requirement from the initial parameter data set to branch, acquiring at least two post-branching parameter data sets, and acquiring the current value of the post-branching model according to the post-branching parameter data sets and the electric energy metering verification production cost minimum model;
the post-branching parameter data set optimizing module is further configured to determine whether a current value of the post-branching model is between an upper model limit value and a lower model limit value, if yes, branch any parameter of the post-branching parameter data set that does not meet an integer requirement to obtain a post-branching parameter data set, obtain a post-branching model current value according to the post-branching parameter data set, determine whether the post-branching model current value is between the upper model limit value and the lower model limit value, and until the post-branching parameter data set meets a model constraint condition that an electric energy metering verification production cost is the lowest and an electric energy metering verification production cost is the lowest, and edit a purchase scheduling parameter, a verification production scheduling parameter, an inventory scheduling parameter and a distribution scheduling parameter according to the post-branching parameter data set.
6. The intelligent scheduling system for electrical energy metering verification production based on the branch definition algorithm of claim 5, wherein the post-branch parameter data set optimizing module is further configured to delete the post-branch parameter data set when the current model value is not between the upper model limit and the lower model limit.
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Inventor after: Wei Fei Inventor after: Qiao Yanan Inventor after: Wu Shoujian Inventor after: Liu Jing Inventor after: Zhao Yong Inventor after: Liu Kai Inventor after: Liu Xue Inventor after: Chen Xin Inventor after: Liu Haoyu Inventor after: Sun Hong Inventor after: Zhai Shuran Inventor before: Wei Fei Inventor before: Qiao Yanan Inventor before: Wu Shoujian Inventor before: Liu Jing Inventor before: Zhao Yong Inventor before: Liu Kai Inventor before: Liu Xue Inventor before: Chen Xin Inventor before: Liu Haoyu Inventor before: Sun Hong Inventor before: Zhai Muran |