Supply chain management platform and method based on intelligent optimization

Abstract

The invention belongs to the technical field of supply chain management, and particularly relates to a supply chain management platform and method based on intelligent optimization. Dynamic monitoring and management of each production link in the supply chain are achieved by collecting real-time production data, so that the response speed and flexibility of the whole supply chain are improved, bottlenecks and potential risks in the production links can be rapidly recognized through an intelligent optimization algorithm, production strategies can be adjusted in time, resource allocation is optimized, resource waste is reduced, and the production efficiency is improved. And meanwhile, through an early warning and warning mechanism, the risk of supply chain interruption can be effectively prevented and dealt with, stable operation of the supply chain is ensured, the operation cost is reduced, and the anti-risk capability of the supply chain is enhanced.

Description

Technical Field

[0001] The present invention belongs to the technical field of supply chain management, and in particular relates to a supply chain management platform and method based on intelligent optimization. Background Art

[0002] With the rapid development of big data, cloud computing and artificial intelligence technologies, supply chain management is gradually moving towards intelligence and dynamism to adapt to complex and changing market demands, achieve efficient operation of the supply chain and optimal allocation of resources, and thus meet the needs of enterprises for high efficiency and low cost of supply chain management.

[0003] However, traditional supply chain management methods often lack sufficient flexibility and intelligence, and it is difficult to effectively respond to market fluctuations and uncertainties in the production process, such as emergencies such as supply shortages or demand surges, which may lead to supply and demand imbalances in the production links of the supply chain, thereby affecting the stability and efficiency of the entire supply chain. Based on this, the present invention proposes a supply chain management method based on intelligent optimization to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a supply chain management platform and method based on intelligent optimization, which can effectively cope with market fluctuations and uncertainties in the production process, thereby improving the stability and efficiency of the supply chain.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A supply chain management method based on intelligent optimization, comprising:

[0007] Acquire production data of each production link in the supply chain, wherein the production data includes supply information, demand information and inventory information;

[0008] According to the supply and demand relationship of the production links, the production status of the production data of each production link is evaluated, wherein the production status includes a normal supply and demand status and an abnormal supply and demand status;

[0009] Under the normal supply and demand state, the production data of the production link is recorded as normal condition parameters, and the production boundary of the corresponding production link is determined according to the normal condition parameters;

[0010] Under the abnormal supply and demand state, the production data of the production link is recorded as an abnormal condition parameter, and the supply and demand difference of the corresponding production link is calculated according to the abnormal condition parameter;

[0011] Based on the supply-demand difference, the production resources corresponding to the production links are optimized to balance the supply-demand relationship of each production link.

[0012] In a preferred embodiment, the acquisition of production data of each production link in the supply chain includes the following steps:

[0013] Establishing a monitoring period and setting a plurality of monitoring nodes within the monitoring period;

[0014] Collecting supply information, demand information and inventory information of each production link under each monitoring node;

[0015] Preprocessing the supply information, demand information and inventory information under each of the production links, wherein the preprocessing includes data cleaning, data standardization and data normalization;

[0016] The pre-processed supply information, demand information and inventory information in each of the production links are classified and summarized, and output as production data of the corresponding production link.

[0017] In a preferred embodiment, the step of evaluating the production status of the production data of each production link according to the supply and demand relationship of the production link includes:

[0018] Obtaining the supply and demand relationship of each of the production links, wherein the supply and demand relationship includes a connection relationship and an independent relationship;

[0019] Collecting the production redundancy corresponding to the production link under the connection relationship and recording it as the condition parameter to be evaluated;

[0020] Obtaining a preset evaluation threshold, and comparing the condition parameter to be evaluated with the evaluation threshold;

[0021] When the condition parameter to be evaluated is greater than the evaluation threshold, it indicates that the supply and demand status between the interconnected production links is normal, and the production status of the corresponding production link is recorded as normal;

[0022] When the condition parameter to be evaluated is less than or equal to the evaluation threshold, it indicates that the supply and demand status between the interconnected production links is abnormal, and the production status of the corresponding production link is recorded as an abnormal state.

[0023] In a preferred embodiment, the step of collecting the production redundancy corresponding to the production link under the connection relationship and recording it as the condition parameter to be evaluated includes:

[0024] Obtaining the unit supply, unit demand and inventory of each production link under each monitoring node;

[0025] For each of the monitoring nodes, the unit supply quantity, the unit demand quantity and the inventory quantity of each of the production links are respectively subjected to difference processing to obtain the unit supply difference quantity, the unit demand difference quantity and the inventory difference quantity;

[0026] Performing bidirectional offset processing on the unit supply difference, unit demand difference and inventory difference to obtain a unit supply evaluation interval, a unit demand evaluation interval and an inventory difference evaluation interval;

[0027] Collecting the quantity of unit supply difference, the quantity of unit demand difference and the quantity of inventory difference in each of the unit supply evaluation interval, the unit demand evaluation interval and the inventory difference evaluation interval, and recording them as the first condition parameter, the second condition parameter and the third condition parameter respectively;

[0028] Filter out the first condition parameter, the second condition parameter and the third condition parameter with the largest value, and record the unit supply quantity, unit demand quantity and inventory quantity corresponding to the first condition parameter, the second condition parameter and the third condition parameter as the standard supply quantity, the standard demand quantity and the standard inventory quantity respectively;

[0029] A first calculation function is obtained, and the standard supply quantity, standard demand quantity and standard inventory quantity are input into the first calculation function, and the output result of the first calculation function is recorded as a condition parameter to be evaluated.

[0030] In a preferred embodiment, the step of determining the production boundary of the corresponding production link according to the normal condition parameter includes:

[0031] Obtaining the production redundancy difference corresponding to the normal condition parameter and recording it as the planning condition parameter;

[0032] Obtain a second calculation function, input the planning condition parameter into the second calculation function, and record the output result of the second calculation function as the allowable deviation duration;

[0033] The real-time production nodes under normal condition parameters are collected, and the real-time production nodes are offset according to the allowable offset duration, and output as the production boundary of the corresponding production link.

[0034] In a preferred embodiment, the step of calculating the supply-demand difference of the corresponding production link according to the abnormal condition parameter includes:

[0035] Acquire the abnormal condition parameter and the production redundancy difference corresponding to the abnormal condition parameter, and record them as the control condition parameter;

[0036] Obtaining a third calculation function, inputting the control condition parameter into the third calculation function, and recording the output result of the third calculation function as the abnormality allowable duration;

[0037] The abnormal allowable duration is reversely offset to obtain the allowable regulation duration, and the production redundancy corresponding to the allowable regulation duration is recorded as the supply-demand difference.

[0038] In a preferred solution, after the supply-demand difference is output, the unit supply quantity corresponding to the production link is collected;

[0039] When the value of the unit supply amount is greater than the control condition parameter, it indicates that the supply-demand difference in the production link can be replenished, and the replenishment time is calculated according to the unit supply amount;

[0040] If the replenishment time is less than the allowable regulation time, the production status of the production link is adjusted to an acceptable state, and the replenishment of the corresponding production link is performed synchronously;

[0041] If the replenishment time is greater than or equal to the allowable regulation time, it indicates that the supply-demand gap cannot be replenished within an acceptable time, and a warning signal is issued simultaneously;

[0042] When the unit supply amount is less than the control condition parameter, it indicates that the supply-demand difference of the production link cannot be replenished in time, and an alarm signal is triggered simultaneously;

[0043] Among them, the risk level of the alarm signal is higher than the risk level of the early warning signal.

[0044] In a preferred embodiment, the step of optimizing the production resources corresponding to the production link according to the supply-demand difference includes:

[0045] Obtaining production resources for the supply-demand difference requirement and recording them as demand resources;

[0046] Obtain the production resources that can be deployed in the production process under the normal condition parameters, and record them as deployable resources

[0047] The resource matching is performed on the deployable resources according to the required resources until the required resources are met.

[0048] The present invention also provides a supply chain management platform based on intelligent optimization, using the above-mentioned supply chain management method based on intelligent optimization, including:

[0049] A data acquisition module, which is used to acquire production data of each production link in the supply chain, wherein the production data includes supply information, demand information and inventory information;

[0050] A status evaluation module, the status evaluation module is used to evaluate the production status of the production data of each production link according to the supply and demand relationship of the production link, wherein the production status includes a normal supply and demand status and an abnormal supply and demand status;

[0051] A first intervention module, the first intervention module is used to record the production data of the production link as normal condition parameters under the normal supply and demand state, and determine the production boundary of the corresponding production link according to the normal condition parameters;

[0052] a second intervention module, the second intervention module being used to record the production data of the production link as abnormal condition parameters under the abnormal supply and demand state, and calculate the supply and demand difference of the corresponding production link according to the abnormal condition parameters;

[0053] A resource balancing module is used to optimize the production resources corresponding to the production links according to the supply-demand difference, and balance the supply-demand relationship of each production link.

[0054] And, an electronic device, the electronic device comprising:

[0055] at least one processor;

[0056] and a memory communicatively coupled to the at least one processor;

[0057] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned supply chain management method based on intelligent optimization.

[0058] The technical effects achieved by the present invention are:

[0059] The present invention collects real-time production data to realize dynamic monitoring and management of each production link in the supply chain, thereby improving the response speed and flexibility of the entire supply chain. Through intelligent optimization algorithms, it can quickly identify bottlenecks and potential risks in the production links, adjust production strategies in time, optimize resource allocation, reduce resource waste, and improve production efficiency. At the same time, through early warning and alarm mechanisms, it can effectively prevent and respond to the risks of supply chain disruptions, ensure the stable operation of the supply chain, reduce operating costs, and enhance the risk resistance of the supply chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a schematic flow chart of the method of the present invention;

[0061] Figure 2 It is a schematic diagram of the system module of the present invention;

[0062] Figure 3 It is a schematic diagram of the structure of an electronic device of the present invention. DETAILED DESCRIPTION

[0063] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0064] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0065] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" that appears in different places in this specification does not refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0066] See also Figure 1 As shown, the present invention provides a supply chain management method based on intelligent optimization, comprising:

[0067] Obtain production data of each production link in the supply chain, where production data includes supply information, demand information and inventory information;

[0068] According to the supply and demand relationship of the production links, the production status of the production data of each production link is evaluated, where the production status includes normal supply and demand status and abnormal supply and demand status;

[0069] Under normal supply and demand conditions, the production data of the production link is recorded as normal condition parameters, and the production boundary of the corresponding production link is determined based on the normal condition parameters;

[0070] Under abnormal supply and demand conditions, the production data of the production link is recorded as abnormal condition parameters, and the supply and demand difference of the corresponding production link is calculated based on the abnormal condition parameters;

[0071] Based on the difference between supply and demand, the production resources of the corresponding production links will be optimized to balance the supply and demand relationship of each production link.

[0072] With the continuous development and complexity of the supply chain industry, traditional supply chain management methods have been unable to meet the needs of high efficiency, flexibility and intelligence. In the present invention, first, detailed production data of each production link in the supply chain is comprehensively acquired. The production data covers multiple aspects such as supply information, demand information and inventory information to ensure the comprehensiveness and accuracy of production data acquisition. Secondly, the acquired production data is evaluated for the corresponding production status according to the supply and demand relationship of each production link. In this embodiment, the evaluation results are divided into two states, namely, normal supply and demand state and abnormal supply and demand state. In the normal supply and demand state, the production data of the production link is recorded in detail as normal condition parameters, and the production boundary of the corresponding production link is predicted and determined based on the normal condition parameters to ensure the stability and controllability of the production process. In the abnormal supply and demand state, the production data of the production link is recorded as abnormal condition parameters, and the supply and demand difference of the corresponding production link is calculated based on the abnormal condition parameters, so as to timely discover and solve problems. Finally, based on the calculated supply and demand difference, the production resources of the corresponding production link are intelligently optimized and adjusted. By rationally allocating resources, the supply and demand relationship of each production link is balanced, thereby improving the operation efficiency and stability of the entire supply chain.

[0073] In a preferred embodiment, the acquisition of production data of each production link in the supply chain includes the following steps:

[0074] Establishing a monitoring period and setting a plurality of monitoring nodes within the monitoring period;

[0075] Collecting supply information, demand information and inventory information of each production link under each monitoring node;

[0076] Preprocessing the supply information, demand information and inventory information under each of the production links, wherein the preprocessing includes data cleaning, data standardization and data normalization;

[0077] The pre-processed supply information, demand information and inventory information in each of the production links are classified and summarized, and output as production data of the corresponding production link.

[0078] In this implementation, in the process of obtaining production data of each production link in the supply chain, first, it is necessary to construct a clear monitoring period to ensure that the monitoring period can cover the key stages of the entire production process, and reasonably set multiple monitoring nodes within the monitoring period to comprehensively capture data changes in each link, and then collect relevant information of each production link at each monitoring node, including but not limited to supply information, demand information and inventory information, to ensure the comprehensiveness and accuracy of the data, and then perform systematic preprocessing on the collected supply information, demand information and inventory information under each production link. The preprocessing content mainly includes data cleaning to remove invalid or erroneous data, data standardization to unify the data format for subsequent analysis, and data normalization to eliminate data dimensional differences and improve the fairness and comparability of data analysis. Finally, the supply information, demand information and inventory information under each production link that have been preprocessed are carefully classified and summarized, and organized into structured and easy-to-understand production data.

[0079] Secondly, the step of evaluating the production status of the production data of each production link according to the supply and demand relationship of the production link includes:

[0080] Obtaining the supply and demand relationship of each of the production links, wherein the supply and demand relationship includes a connection relationship and an independent relationship;

[0081] Collecting the production redundancy corresponding to the production link under the connection relationship and recording it as the condition parameter to be evaluated;

[0082] Obtaining a preset evaluation threshold, and comparing the condition parameter to be evaluated with the evaluation threshold;

[0083] When the condition parameter to be evaluated is greater than the evaluation threshold, it indicates that the supply and demand status between the interconnected production links is normal, and the production status of the corresponding production link is recorded as normal;

[0084] When the condition parameter to be evaluated is less than or equal to the evaluation threshold, it indicates that the supply and demand status between the interconnected production links is abnormal, and the production status of the corresponding production link is recorded as an abnormal state.

[0085] When evaluating the production status of the production data of each production link according to the supply and demand relationship of the production link, the supply and demand relationship between each production link is firstly comprehensively obtained. The supply and demand relationship not only covers the connection relationship between each link, but also includes the independent relationship of each link when operating independently. On the basis of clarifying the connection relationship, the production redundancy existing in each corresponding production link is collected, and the production redundancy is recorded as the condition parameter to be evaluated for subsequent evaluation. Then, a pre-set evaluation threshold is obtained. The evaluation threshold is the standard for judging whether the production status is normal or not. Then, the previously recorded condition parameter to be evaluated is compared and analyzed with the evaluation threshold. During the comparison process, if it is found that the condition parameter to be evaluated is greater than the evaluation threshold, it indicates that the supply and demand status between the interconnected production links is at a normal level. At this time, the production status of the corresponding production link is clearly recorded as a normal state to show that it operates well. On the contrary, if the condition parameter to be evaluated is less than or equal to the evaluation threshold, it indicates that there is an abnormality in the supply and demand status between the interconnected production links. At this time, the production status of the corresponding production link needs to be recorded as an abnormal state in a timely manner so that corresponding adjustment and improvement measures can be taken later.

[0086] Secondly, the step of collecting the production redundancy corresponding to the production link under the connection relationship and recording it as the condition parameter to be evaluated includes:

[0087] Obtaining the unit supply, unit demand and inventory of each production link under each monitoring node;

[0088] For each of the monitoring nodes, the unit supply quantity, the unit demand quantity and the inventory quantity of each of the production links are respectively subjected to difference processing to obtain the unit supply difference quantity, the unit demand difference quantity and the inventory difference quantity;

[0089] Performing bidirectional offset processing on the unit supply difference, unit demand difference and inventory difference to obtain a unit supply evaluation interval, a unit demand evaluation interval and an inventory difference evaluation interval;

[0090] Collecting the quantity of unit supply difference, the quantity of unit demand difference and the quantity of inventory difference in each of the unit supply evaluation interval, the unit demand evaluation interval and the inventory difference evaluation interval, and recording them as the first condition parameter, the second condition parameter and the third condition parameter respectively;

[0091] Filter out the first condition parameter, the second condition parameter and the third condition parameter with the largest value, and record the unit supply quantity, unit demand quantity and inventory quantity corresponding to the first condition parameter, the second condition parameter and the third condition parameter as the standard supply quantity, the standard demand quantity and the standard inventory quantity respectively;

[0092] A first calculation function is obtained, and the standard supply quantity, standard demand quantity and standard inventory quantity are input into the first calculation function, and the output result of the first calculation function is recorded as a condition parameter to be evaluated.

[0093] In this embodiment, when determining the condition parameters to be evaluated, it is first necessary to comprehensively obtain the unit supply, unit demand and current inventory of each specific production link, and then perform difference processing on the unit supply, unit demand and inventory of each production link under each monitoring node. Through this processing, the unit supply difference, unit demand difference and inventory difference can be obtained respectively. Then, for the obtained unit supply difference, unit demand difference and inventory difference, a two-way offset processing is performed. The purpose is to construct a more reasonable evaluation interval, so as to obtain the unit supply evaluation interval, unit demand evaluation interval and inventory difference evaluation interval, so as to provide a more scientific range for subsequent parameter collection. On this basis, the specific values ​​in each unit supply evaluation interval, unit demand evaluation interval and inventory difference evaluation interval are collected in detail, including the unit supply difference. The quantity, the quantity of unit demand difference and the quantity of inventory difference are collected and recorded as the first condition parameter, the second condition parameter and the third condition parameter respectively, so as to facilitate subsequent analysis and comparison. Subsequently, the parameter with the largest value is screened out from the collected first condition parameter, the second condition parameter and the third condition parameter, and the unit supply quantity, unit demand quantity and inventory quantity corresponding to the maximum value are recorded as the standard supply quantity, the standard demand quantity and the standard inventory quantity respectively, to provide a benchmark for subsequent measurement, and then the first measurement function is obtained, and the screened standard supply quantity, standard demand quantity and standard inventory quantity are input into the first measurement function, wherein the expression of the first measurement function is: condition parameter to be evaluated = standard inventory quantity + standard supply quantity - standard demand quantity. Through the processing of the measurement function, the condition parameter to be evaluated can be obtained, thereby providing a scientific basis for subsequent production optimization and decision-making.

[0094] In a preferred embodiment, the step of determining the production boundary of the corresponding production link according to the normal condition parameter includes:

[0095] Obtaining the production redundancy difference corresponding to the normal condition parameter and recording it as the planning condition parameter;

[0096] Obtain a second calculation function, input the planning condition parameter into the second calculation function, and record the output result of the second calculation function as the allowable deviation duration;

[0097] Real-time production nodes under normal condition parameters are collected, and the real-time production nodes are offset according to the allowable offset duration, and output as the production boundary of the corresponding production link.

[0098] In this implementation, when determining the production boundary of the corresponding production link according to the normal condition parameter, first, it is necessary to obtain the production redundancy difference corresponding to the normal condition parameter and define it as the planned condition parameter. Secondly, a second measurement function for measuring the allowable deviation time is obtained, and the recorded planned condition parameter is input into the second measurement function to output the allowable deviation time. The expression of the second measurement function is: Where, T 1 Indicates the allowable offset duration, M r Represents the allowable redundant difference, M d Represents the production redundancy difference under the current node, t 1 Indicates the length of the monitoring period, J i and J i-1 Represents the planned condition parameters under adjacent monitoring nodes, n represents the number of planned condition parameters, the allowable offset duration obtained by the second measurement function is the time deviation range allowed in the actual production process, and then the real-time production nodes under normal condition parameters are collected, and then according to the allowable offset duration, the collected real-time production nodes are subjected to corresponding offset processing, and the result after offset processing is output as the production boundary of the corresponding production link.

[0099] Secondly, the step of calculating the supply-demand difference of the corresponding production link according to the abnormal condition parameter includes:

[0100] Acquire the abnormal condition parameter and the production redundancy difference corresponding to the abnormal condition parameter, and record them as the control condition parameter;

[0101] Obtaining a third calculation function, inputting the control condition parameter into the third calculation function, and recording the output result of the third calculation function as the abnormality allowable duration;

[0102] The abnormal allowable duration is reversely offset to obtain the allowable regulation duration, and the production redundancy corresponding to the allowable regulation duration is recorded as the supply-demand difference.

[0103] When calculating the supply-demand difference of the corresponding production link based on the abnormal condition parameters, it is necessary to first obtain the relevant abnormal condition parameters, and at the same time determine the production redundancy difference corresponding to the abnormal condition parameters, and use them as the subsequent control condition parameters, and then obtain the preset third measurement function, and input the recorded control condition parameters into the third measurement function. Through the calculation and processing of the third measurement function, the abnormal allowable duration is obtained, wherein the expression of the third measurement function is: Where, T 2 Indicates the allowed duration of abnormality, S j and S j-1represents the control condition parameters under adjacent nodes during the duration of the abnormal supply and demand state, m represents the statistical number of control condition parameters, and finally, the obtained abnormal allowable duration is reversely offset to output the allowable control period. During the allowable control period, the production link works normally, and its supply and demand relationship with other production links can continue to be executed under the action of redundant difference. Of course, the redundant difference of the corresponding product consumed during this period needs to be replenished. In this embodiment, this replenishment amount is recorded as the supply and demand difference, which is used as a basis to provide a basis for the formulation of subsequent replenishment strategies.

[0104] Secondly, after the supply-demand difference is output, the unit supply quantity corresponding to the production link is collected;

[0105] When the value of the unit supply amount is greater than the control condition parameter, it indicates that the supply-demand difference in the production link can be replenished, and the replenishment time is calculated according to the unit supply amount;

[0106] If the replenishment time is less than the allowable regulation time, the production status of the production link is adjusted to an acceptable state, and the replenishment of the corresponding production link is performed synchronously;

[0107] If the replenishment time is greater than or equal to the allowable regulation time, it indicates that the supply-demand gap cannot be replenished within an acceptable time, and a warning signal is issued simultaneously;

[0108] When the unit supply amount is less than the control condition parameter, it indicates that the supply-demand difference of the production link cannot be replenished in time, and an alarm signal is triggered simultaneously;

[0109] Among them, the risk level of the alarm signal is higher than the risk level of the early warning signal.

[0110] In this embodiment, after the supply-demand difference is output, the unit supply quantity required by the corresponding production link will be collected immediately, that is, the number of products required to be replenished in the corresponding production link within a unit time. When the specific value of the collected unit supply quantity exceeds the preset control condition parameter, this indicates that the supply-demand difference of the production link can be effectively replenished. In this case, the required replenishment time will be further accurately calculated based on the specific value of the unit supply quantity. If the calculated replenishment time is less than the set allowable control period, the production status of the production link will be adjusted to an acceptable state, and the replenishment operation of the corresponding production link will be started simultaneously to ensure the smooth progress of the production process. However, if the calculated If the replenishment time is greater than or equal to the allowable control period set by the system, it means that the current supply-demand gap cannot be effectively replenished within an acceptable time frame, and an early warning signal will be immediately issued to remind relevant personnel to pay attention to potential production risks. In addition, when the collected unit supply volume is less than the pre-set control condition parameters, it indicates that the supply-demand gap in the production link cannot be replenished in a timely and effective manner, and an alarm signal will be triggered simultaneously to warn relevant personnel to take emergency measures to deal with possible problems. It should be noted that the risk level of the alarm signal is significantly higher than the risk level of the early warning signal, which means that the problem indicated by the alarm signal is more serious and urgent, and requires higher priority processing and response.

[0111] In a preferred embodiment, the step of optimizing the production resources corresponding to the production link according to the supply-demand difference includes:

[0112] Obtaining production resources for the supply-demand difference requirement and recording them as demand resources;

[0113] Obtain the production resources that can be deployed in the production process under the normal condition parameters, and record them as deployable resources

[0114] The resource matching is performed on the deployable resources according to the required resources until the required resources are met.

[0115] In this implementation, when optimizing the production resources of a production link, first, the demand for production resources caused by the difference between supply and demand is obtained and defined as demand resources. Secondly, the status of production resources available for deployment in each production link under normal production conditions is clarified, and the available production resource information is recorded in detail and classified as deployable resources. Finally, according to the identified demand resources, corresponding resource matching work is performed on the deployable resources. By continuously adjusting and optimizing resource allocation, all demand resources are fully met, at which time the resource matching process can be stopped.

[0116] See also Figure 2, a supply chain management platform based on intelligent optimization, using the above-mentioned supply chain management method based on intelligent optimization, including:

[0117] A data acquisition module, which is used to acquire production data of each production link in the supply chain, wherein the production data includes supply information, demand information and inventory information;

[0118] A status evaluation module, the status evaluation module is used to evaluate the production status of the production data of each production link according to the supply and demand relationship of the production link, wherein the production status includes a normal supply and demand status and an abnormal supply and demand status;

[0119] A first intervention module, the first intervention module is used to record the production data of the production link as normal condition parameters under the normal supply and demand state, and determine the production boundary of the corresponding production link according to the normal condition parameters;

[0120] a second intervention module, the second intervention module being used to record the production data of the production link as abnormal condition parameters under the abnormal supply and demand state, and calculate the supply and demand difference of the corresponding production link according to the abnormal condition parameters;

[0121] A resource balancing module is used to optimize the production resources corresponding to the production links according to the supply-demand difference, and balance the supply-demand relationship of each production link.

[0122] The management platform mentioned above includes a data acquisition module, a status assessment module, a first intervention module, a second intervention module and a resource balance module. The main responsibility of the data acquisition module is to comprehensively obtain detailed production data of each production link in the supply chain. Specifically, the production data covers multiple dimensions such as supply information, demand information and inventory information, ensuring comprehensive monitoring and data support for each link of the supply chain. The function of the status assessment module is to conduct in-depth analysis of the acquired production data based on the supply and demand relationship of each production link, so as to accurately assess the production status of each production link. In this process, the production status is subdivided into two categories: normal supply and demand status and abnormal supply and demand status, so as to carry out targeted intervention and management later. The first intervention module It plays a role under normal supply and demand conditions. The specific operation is to record the production data of the production link as normal condition parameters, and based on these normal condition parameters, determine the production boundaries of the corresponding production links, so as to ensure the stability and controllability of the production process. The second intervention module is executed in abnormal supply and demand conditions. Under abnormal circumstances, the production data of the production link will be recorded as abnormal condition parameters, and the supply and demand difference of the corresponding production link will be calculated based on the abnormal condition parameters, providing data basis for subsequent adjustments and optimizations. The core task of the resource balancing module is to intelligently optimize and adjust the production resources of the corresponding production link based on the supply and demand difference calculated above, aiming to balance the supply and demand relationship of each production link and ensure the efficient operation of the entire supply chain and the optimal allocation of resources.

[0123] See also Figure 3 , an electronic device, the electronic device comprising:

[0124] at least one processor;

[0125] and a memory communicatively coupled to the at least one processor;

[0126] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned supply chain management method based on intelligent optimization.

[0127] The processor of the above-mentioned electronic device can be a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), etc., or other types of processors, such as a neural network processor (NPU), etc. The processor can be a combination of one or more, and the memory can include a random access memory (RAM), a read-only memory (ROM), a disk storage, a flash memory, etc. The memory is used to store computer programs and data required by the processor when running or executing. In addition, the electronic device can also include input devices, output devices, network interfaces, etc. The input devices can include keyboards, mice, touch screens, etc. The output devices can include displays, speakers, etc. The network interface is used to realize the connection between the electronic device and other devices or networks, such as wired connections or wireless connections. By executing the computer program stored in the memory, the processor can realize the various steps and functions of the above-mentioned supply chain management method based on intelligent optimization, thereby realizing effective management and optimization of each production link in the supply chain.

[0128] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0129] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. A supply chain management method based on intelligent optimization, characterized by: include: Acquire production data of each production link in the supply chain, wherein the production data includes supply information, demand information and inventory information; According to the supply and demand relationship of the production links, the production status of the production data of each production link is evaluated, wherein the production status includes a normal supply and demand status and an abnormal supply and demand status; Under the normal supply and demand state, the production data of the production link is recorded as normal condition parameters, and the production boundary of the corresponding production link is determined according to the normal condition parameters; Under the abnormal supply and demand state, the production data of the production link is recorded as an abnormal condition parameter, and the supply and demand difference of the corresponding production link is calculated according to the abnormal condition parameter; Based on the supply-demand difference, the production resources corresponding to the production links are optimized to balance the supply-demand relationship of each production link.

2. The supply chain management method based on intelligent optimization according to claim 1, characterized in that: The acquisition of production data of each production link in the supply chain includes the following steps: Establishing a monitoring period and setting a plurality of monitoring nodes within the monitoring period; Collecting supply information, demand information and inventory information of each production link under each monitoring node; Preprocessing the supply information, demand information and inventory information under each of the production links, wherein the preprocessing includes data cleaning, data standardization and data normalization; The pre-processed supply information, demand information and inventory information in each of the production links are classified and summarized, and output as production data of the corresponding production link.

3. The supply chain management method based on intelligent optimization according to claim 1, characterized in that: The step of evaluating the production status of the production data of each production link according to the supply and demand relationship of the production link comprises: Obtaining the supply and demand relationship of each of the production links, wherein the supply and demand relationship includes a connection relationship and an independent relationship; Collecting the production redundancy corresponding to the production link under the connection relationship and recording it as the condition parameter to be evaluated; Obtaining a preset evaluation threshold, and comparing the condition parameter to be evaluated with the evaluation threshold; When the condition parameter to be evaluated is greater than the evaluation threshold, it indicates that the supply and demand status between the interconnected production links is normal, and the production status of the corresponding production link is recorded as normal; When the condition parameter to be evaluated is less than or equal to the evaluation threshold, it indicates that the supply and demand status between the interconnected production links is abnormal, and the production status of the corresponding production link is recorded as an abnormal state.

4. The supply chain management method based on intelligent optimization according to claim 1, characterized in that: The step of collecting the production redundancy corresponding to the production link under the connection relationship and recording it as the condition parameter to be evaluated includes: Obtaining the unit supply, unit demand and inventory of each production link under each monitoring node; For each of the monitoring nodes, the unit supply quantity, the unit demand quantity and the inventory quantity of each of the production links are respectively subjected to difference processing to obtain the unit supply difference quantity, the unit demand difference quantity and the inventory difference quantity; Performing bidirectional offset processing on the unit supply difference, unit demand difference and inventory difference to obtain a unit supply evaluation interval, a unit demand evaluation interval and an inventory difference evaluation interval; Collecting the quantity of unit supply difference, the quantity of unit demand difference and the quantity of inventory difference in each of the unit supply evaluation interval, the unit demand evaluation interval and the inventory difference evaluation interval, and recording them as the first condition parameter, the second condition parameter and the third condition parameter respectively; Filter out the first condition parameter, the second condition parameter and the third condition parameter with the largest value, and record the unit supply quantity, unit demand quantity and inventory quantity corresponding to the first condition parameter, the second condition parameter and the third condition parameter as the standard supply quantity, the standard demand quantity and the standard inventory quantity respectively; A first calculation function is obtained, and the standard supply quantity, standard demand quantity and standard inventory quantity are input into the first calculation function, and the output result of the first calculation function is recorded as a condition parameter to be evaluated.

5. The supply chain management method based on intelligent optimization according to claim 1, characterized in that: The step of determining the production boundary of the corresponding production link according to the normal condition parameter comprises: Obtaining the production redundancy difference corresponding to the normal condition parameter and recording it as the planning condition parameter; Obtain a second calculation function, input the planning condition parameter into the second calculation function, and record the output result of the second calculation function as the allowable deviation duration; The real-time production nodes under normal condition parameters are collected, and the real-time production nodes are offset according to the allowable offset duration, and output as the production boundary of the corresponding production link.

6. The supply chain management method based on intelligent optimization according to claim 1, characterized in that: The step of calculating the supply-demand difference of the corresponding production link according to the abnormal condition parameter includes: Acquire the abnormal condition parameter and the production redundancy difference corresponding to the abnormal condition parameter, and record them as the control condition parameter; Obtaining a third calculation function, inputting the control condition parameter into the third calculation function, and recording the output result of the third calculation function as the abnormality allowable duration; The abnormal permissible duration is reversely offset to obtain a permissible regulation period, and the corresponding production redundancy in the permissible regulation period is recorded as the supply-demand difference.

7. The supply chain management method based on intelligent optimization according to claim 6 is characterized by: After the supply-demand difference is output, the unit supply quantity corresponding to the production link is collected; When the value of the unit supply amount is greater than the control condition parameter, it indicates that the supply-demand difference in the production link can be replenished, and the replenishment time is calculated according to the unit supply amount; If the replenishment duration is less than the allowable control period, the production status of the production link is adjusted to an acceptable state, and the replenishment of the corresponding production link is performed synchronously; If the replenishment time is greater than or equal to the permissible control period, it indicates that the supply-demand gap cannot be replenished within an acceptable time, and a warning signal is issued simultaneously; When the unit supply amount is less than the control condition parameter, it indicates that the supply-demand difference of the production link cannot be replenished in time, and an alarm signal is triggered simultaneously; Among them, the risk level of the alarm signal is higher than the risk level of the early warning signal.

8. The supply chain management method based on intelligent optimization according to claim 1, characterized in that: The step of optimizing the production resources corresponding to the production link according to the supply-demand difference comprises: Obtaining production resources for the supply-demand difference requirement and recording them as demand resources; Obtain the production resources that can be deployed in the production process under the normal condition parameters, and record them as deployable resources The resource matching is performed on the deployable resources according to the required resources until the required resources are met.

9. A supply chain management platform based on intelligent optimization, characterized by: The supply chain management method based on intelligent optimization according to any one of claims 1 to 8 comprises: A data acquisition module, which is used to acquire production data of each production link in the supply chain, wherein the production data includes supply information, demand information and inventory information; A status evaluation module, the status evaluation module is used to evaluate the production status of the production data of each production link according to the supply and demand relationship of the production link, wherein the production status includes a normal supply and demand status and an abnormal supply and demand status; A first intervention module, the first intervention module is used to record the production data of the production link as normal condition parameters under the normal supply and demand state, and determine the production boundary of the corresponding production link according to the normal condition parameters; a second intervention module, the second intervention module being used to record the production data of the production link as abnormal condition parameters under the abnormal supply and demand state, and calculate the supply and demand difference of the corresponding production link according to the abnormal condition parameters; A resource balancing module is used to optimize the production resources corresponding to the production links according to the supply-demand difference, and balance the supply-demand relationship of each production link.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the supply chain management method based on intelligent optimization as described in any one of claims 1 to 8.

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