Building project material ordering optimization method and system considering supply interruption

Abstract

The invention discloses a building project material ordering optimization method and system considering supply interruption. The optimization method comprises the steps of obtaining a construction plan and material consumption; based on the construction plan and the material consumption, predicting a material demand within a preset time; obtaining a preliminary material ordering plan according to the material demand; obtaining an optimal material purchasing channel, and performing risk assessment according to the optimal material purchasing channel and the preliminary material ordering plan to obtain a supply risk; and obtaining an optimal material ordering plan according to the supply risk. According to the method, factors such as project progress, construction plans and material consumption are comprehensively considered, material demands in a certain period in the future are predicted, a material ordering plan is made according to a prediction result, the purchasing time, the purchasing quantity and the purchasing channels of materials are reasonably arranged, and the situation of material shortage or excessive purchasing is avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of information processing, and in particular relates to a construction project material ordering optimization method and system taking into account supply interruption. Background Art

[0002] In the existing ordering plan in the construction project logistics management, by analyzing and predicting the demand for materials, a reasonable material ordering plan is formulated, but it is impossible to simultaneously meet the problem of minimizing material procurement costs and supply interruptions, and there are the following risks when ordering:

[0003] Price Fluctuation Risk: Fluctuation in raw material prices is one of the main risks in material ordering.

[0004] Supplier integrity issues: When selecting suppliers, despite qualification review and screening, it is still difficult to ensure that every supplier is honest and trustworthy.

[0005] Contract fraud risk: In a complex market environment, contract fraud is common, resulting in the inability to guarantee the quality of material supply and service.

[0006] Information asymmetry risk: When selecting building materials online, you choose styles and colors based on photos provided by the merchant, but there may be color differences between the pictures and the actual objects.

[0007] Therefore, there is an urgent need for a construction project material ordering optimization method and system that takes supply interruptions into account. Summary of the invention

[0008] In order to solve the above technical problems, the present invention proposes a construction project material ordering optimization method and system taking supply interruptions into consideration. The method and system can comprehensively consider factors such as project progress, construction plan, material consumption, etc., predict material demand in a certain period in the future, and formulate a material ordering plan based on the prediction results, reasonably arrange the procurement time, procurement quantity and procurement channels of the materials, and avoid material shortages or excessive procurement.

[0009] The present invention provides a construction project material ordering optimization method considering supply interruptions, comprising:

[0010] Obtain construction schedule and material consumption;

[0011] Based on the construction plan and material consumption, forecast material demand within a preset time;

[0012] Obtain preliminary material ordering plan based on the material requirements;

[0013] Obtain the best material procurement channel, conduct risk assessment based on the best material procurement channel and preliminary material ordering plan, and obtain supply risks;

[0014] Obtain the optimal material ordering plan based on the stated supply risk.

[0015] Optionally, based on the construction plan and material consumption, predicting material demand within a preset time includes:

[0016] Establishing a time series data set based on the construction plan and material consumption;

[0017] Establishing a prediction model, wherein the prediction model is trained by a maximum likelihood method;

[0018] The time series data is input into a forecasting model to obtain material demand within a preset period.

[0019] Optionally, based on the material requirements, obtaining a preliminary material ordering plan includes:

[0020] Obtain information on the type and quantity of materials required for each stage of the project based on the material requirements;

[0021] Genetic algorithm is used to minimize the total cost of material procurement as the optimization goal, and a material procurement optimization model is established in combination with the project progress control requirements;

[0022] The type and quantity information of materials required at each stage of the project is input into the material procurement optimization model to obtain the preliminary material ordering plan.

[0023] Optionally, obtaining the optimal material procurement channel includes:

[0024] Obtain basic information of potential suppliers;

[0025] Adopting the analytic hierarchy process to establish a supplier evaluation index system;

[0026] Input the basic information into the supplier evaluation index system to obtain a comprehensive score;

[0027] Screening the potential suppliers according to the comprehensive scores to determine the shortlisted suppliers;

[0028] Conduct a detailed investigation on the shortlisted suppliers to determine the best supplier, that is, the best material procurement channel.

[0029] Optionally, the basic information includes: company name, contact information, main business, supply capacity, delivery cycle and material price.

[0030] Optionally, a risk assessment is performed based on the optimal material procurement channel and the preliminary material ordering plan to obtain supply risks including:

[0031] Establishing a material supply chain simulation model based on the optimal material procurement channel and the preliminary material ordering plan;

[0032] A Monte Carlo simulation algorithm is used to introduce random variables into the material supply chain simulation model to obtain operation data of the material supply chain under different scenarios, wherein the random variables include: order fulfillment rate, inventory level and shortage probability;

[0033] A risk prediction model is established, and the operation data is input into the risk prediction model to obtain the supply risk.

[0034] Optionally, obtaining the optimal material ordering plan according to the supply risk includes:

[0035] Dynamically adjust procurement time and quantity according to risk level to obtain procurement costs;

[0036] Obtain the optimal material ordering plan based on the stated supply risk and procurement costs.

[0037] The present invention also provides a construction project material ordering optimization system considering supply interruptions, comprising: an information collection module, a material demand forecasting module, a preliminary plan formulation module, a procurement channel acquisition module, a supply risk analysis module and an optimal plan formulation module;

[0038] The information collection module is used to obtain the construction plan and material consumption;

[0039] The material demand forecasting module is used to forecast material demand according to the construction plan and material consumption;

[0040] The preliminary plan making module is used to make a preliminary material ordering plan according to material demand;

[0041] The procurement channel acquisition module is used to screen suitable material procurement channels;

[0042] The supply risk analysis module is used to perform risk analysis based on the preliminary material ordering plan and material procurement channels;

[0043] The optimal plan formulation module is used to formulate an optimal material ordering plan based on supply risks.

[0044] Compared with the prior art, the present invention has the following advantages and technical effects:

[0045] The present invention comprehensively considers factors such as project progress, construction plan, material consumption, etc., predicts material demand in a certain period in the future, and formulates a material ordering plan based on the prediction results, reasonably arranges the purchase time, purchase quantity and purchase channel of materials, and avoids the occurrence of material shortage or over-purchase. This method can effectively reduce procurement costs and supply interruption risks while ensuring the timely supply of materials, and improve the overall operational efficiency of construction projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0047] Figure 1 It is a flow chart of a construction project material ordering optimization method considering supply interruptions according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0049] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0050] This paper proposes a construction project material ordering optimization method considering supply interruptions, such as Figure 1 As shown, the specific steps include:

[0051] Obtain construction schedule and material consumption;

[0052] Based on the construction plan and material consumption, forecast the material demand within the preset time;

[0053] Obtain preliminary material ordering plan based on material requirements;

[0054] Obtain the best material procurement channels, conduct risk assessment based on the best material procurement channels and preliminary material ordering plan, and obtain supply risks;

[0055] Get the optimal material ordering plan based on supply risk.

[0056] Furthermore, based on the construction plan and material consumption, the material demand within the preset time is predicted to include:

[0057] Create a time series dataset based on construction schedule and material consumption;

[0058] Establishing a prediction model, wherein the prediction model is trained by a maximum likelihood method;

[0059] Input time series data into forecasting models to obtain material demand within a preset time period.

[0060] Specifically, the construction schedule for a certain period in the future is obtained according to the construction plan, and a time series data set is established in combination with historical material consumption data. The ARIMA model is used to model the time series data, and the material demand forecast for a certain period in the future is obtained through model training. According to the material demand forecast and the current material inventory, it is determined whether the material needs to be purchased: if the predicted demand is greater than the inventory, a material procurement plan is generated; otherwise, no procurement is required. The material procurement plan is matched with the construction plan, the procurement time and quantity of the materials are determined, and a detailed material procurement plan is generated. According to the material procurement plan, a purchase order is automatically generated and sent to the supplier, and the material inventory information is updated at the same time. After the materials are put into storage, barcodes or RFID technology are used to identify and manage the materials according to the type and specification of the materials, so as to realize the refined management of the materials. Regularly monitor the consumption of materials, compare the actual consumption with the predicted value, adjust the prediction model parameters in time, improve the prediction accuracy, and ensure that the material supply matches the construction plan.

[0061] Further, based on material requirements, obtain a preliminary material ordering plan including:

[0062] Based on material requirements, obtain information on the type and quantity of materials required at each stage of the project;

[0063] Genetic algorithm is used to minimize the total cost of material procurement as the optimization goal, and a material procurement optimization model is established in combination with the project progress control requirements;

[0064] Input the type and quantity information of materials required at each stage of the project into the material procurement optimization model to obtain a preliminary material ordering plan.

[0065] Specifically, according to the material demand forecast results, the type and quantity information of materials required at each stage of the project are obtained as the input parameters of the optimization algorithm. The genetic algorithm is used to minimize the total cost of material procurement as the optimization goal, and the material procurement optimization model is established by considering the project schedule control requirements. In the genetic algorithm, the material procurement time and quantity are used as decision variables, and the optimization is continuously iterated through operations such as selection, crossover and mutation until the termination condition is met. From the optimization results of the genetic algorithm, the optimal procurement time and corresponding procurement quantity of various materials are obtained to form a preliminary material ordering plan. According to the constraints such as the supply capacity of the material supplier and the project funding budget, the feasibility analysis and necessary adjustments are made to the preliminary material ordering plan. The adjusted material ordering plan is compared with the project schedule to ensure that the material procurement progress is coordinated with the project construction progress to avoid material shortages or backlogs. According to the material ordering plan, contracts are negotiated and signed with suppliers to clarify the specific contents such as material specifications, quality standards, delivery time, payment methods, etc. to ensure timely supply of materials.

[0066] Furthermore, obtaining the best material procurement channels includes:

[0067] Obtain basic information of potential suppliers;

[0068] Adopting the analytic hierarchy process to establish a supplier evaluation index system;

[0069] Input basic information into the supplier evaluation index system to obtain a comprehensive score;

[0070] Screen potential suppliers based on comprehensive scores and determine the shortlisted suppliers;

[0071] Conduct detailed investigation on the shortlisted suppliers to determine the best supplier, that is, the best material procurement channel.

[0072] Specifically, according to the material procurement needs, determine the list of potential suppliers and obtain their basic information. For potential suppliers, collect key evaluation indicator data such as their supply capacity, delivery cycle, material price, etc. Use the hierarchical analysis method to establish a supplier evaluation indicator system and determine the weight of each indicator. Input the supplier's supply capacity, delivery period, price and other data into the evaluation model to calculate the comprehensive score. According to the comprehensive score sorting results, combined with the quality, cost and other requirements of material procurement, preliminarily screen suitable suppliers. Further investigate the production capacity, quality management system, after-sales service, etc. of the preliminary selected suppliers to comprehensively judge whether they meet the material procurement requirements. Finally, determine the suppliers who have passed the evaluation as material procurement channels, establish long-term cooperative relationships with them, and ensure the stability and reliability of material supply.

[0073] Furthermore, the basic information includes: company name, contact information, main business, supply capacity, delivery cycle and material price.

[0074] Furthermore, a risk assessment is conducted based on the optimal material procurement channel and the preliminary material ordering plan to obtain supply risks including:

[0075] Establish a material supply chain simulation model based on the optimal material procurement channel and preliminary material ordering plan;

[0076] Monte Carlo simulation algorithm is used to introduce random variables into the material supply chain simulation model to obtain the operation data of the material supply chain under different scenarios. The random variables include order fulfillment rate, inventory level and shortage probability.

[0077] Establish a risk prediction model, input the operating data into the risk prediction model, and obtain supply risk.

[0078] Specifically, a material supply chain simulation model is established based on the material ordering plan and procurement channel information, which includes key nodes such as suppliers, transportation, and inventory. The Monte Carlo simulation algorithm is used to introduce random variables into the material supply chain simulation model, such as supplier delivery time, transportation delays, demand fluctuations and other uncertain factors. Through multiple iterative simulations, the operation data of the material supply chain under different scenarios are obtained, such as key indicators such as order fulfillment rate, inventory level, and shortage probability. A material supply risk prediction model is established using machine learning algorithms such as decision trees or support vector machines, and input features include historical supply data, market information, etc. The simulation results are combined with the risk prediction model to identify high-risk nodes and potential bottlenecks in the material supply chain, and the probability of shortage and over-purchase is quantitatively evaluated. For the identified high-risk nodes, corresponding risk response strategies are formulated, such as adjusting the safety inventory level, developing alternative suppliers, and optimizing transportation routes. The optimized material ordering plan is matched with the procurement channel to form a final material procurement execution plan, and the supply chain operation is continuously monitored to adjust the response strategy in a timely manner.

[0079] Furthermore, based on the supply risk, obtaining the optimal material ordering plan includes:

[0080] Dynamically adjust procurement time and quantity according to risk level to obtain procurement costs;

[0081] Get the optimal material ordering plan based on supply risk and procurement cost.

[0082] Specifically, obtain the material ordering plan, extract the planned material procurement time and quantity information, and establish a material procurement task list; continuously monitor the material consumption in the production process, obtain the actual material consumption data, and compare and analyze the actual consumption data with the planned procurement volume; obtain the project progress information, determine the difference between the project progress and the planned progress, and if the actual progress lags behind the planned progress, determine that there may be a risk of material shortage; based on the difference between the material consumption and the planned procurement volume and the project progress difference, use a linear regression algorithm to predict the subsequent material demand; based on the material demand forecast results, dynamically adjust the material procurement task list to optimize the material procurement time and quantity; if the adjusted material procurement volume is higher than the preset safety stock threshold, trigger the procurement task and send a material order to the supplier; continuously track the material supply progress, and if the material arrival time is later than the production plan requirements, warn of the risk of material shortage and adjust the production plan to adapt to the material supply situation.

[0083] Obtain historical material procurement data and supply risk data, conduct quantitative assessment of material procurement costs and supply interruption risks, and obtain quantitative indicators of material procurement costs and supply risks. According to the quantitative indicators of material procurement costs and supply risks, the analytic hierarchy process is used to determine the weight coefficients of material procurement costs and supply risks, and a comprehensive benefit evaluation model for material ordering plans is constructed. For different material ordering plan schemes, the comprehensive benefit score of each ordering plan is calculated using the constructed comprehensive benefit evaluation model. The comprehensive benefit scores of different material ordering plans are ranked and compared, and the ordering plan with the highest comprehensive benefit score is selected as the optimal plan. If the supply timeliness of the optimal material ordering plan cannot meet the requirements, the material procurement cost and supply risk weights are appropriately adjusted, and the comprehensive benefit evaluation is re-performed until the optimal ordering plan that meets the supply timeliness requirements is selected. In the process of executing the optimal material ordering plan, material procurement cost and supply risk data are continuously collected, the evaluation model is regularly updated and optimized, and the material ordering plan is dynamically adjusted. Through the dynamic optimization and adjustment of the material ordering plan, while ensuring the timely supply of materials, the material procurement cost is minimized, the supply interruption risk is controlled, and the cost-effectiveness optimization of material ordering is achieved.

[0084] The present invention also provides a construction project material ordering optimization system considering supply interruptions, comprising: an information collection module, a material demand forecasting module, a preliminary plan formulation module, a procurement channel acquisition module, a supply risk analysis module and an optimal plan formulation module;

[0085] Information collection module, used to obtain construction plans and material consumption;

[0086] Material demand forecasting module, used to forecast material demand based on construction plan and material consumption;

[0087] A preliminary planning module is used to formulate a preliminary material ordering plan based on material requirements;

[0088] Procurement channel acquisition module, used to screen suitable material procurement channels;

[0089] Supply risk analysis module, used to conduct risk analysis based on preliminary material ordering plan and material procurement channels;

[0090] The optimal planning module is used to formulate the optimal material ordering plan based on supply risks.

[0091] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A construction project material ordering optimization method considering supply interruptions, characterized in that include: Obtain construction schedule and material consumption; Based on the construction plan and material consumption, forecast material demand within a preset time; Obtain preliminary material ordering plan based on the material requirements; Obtain the best material procurement channel, conduct risk assessment based on the best material procurement channel and preliminary material ordering plan, and obtain supply risks; Obtain the optimal material ordering plan based on the stated supply risk.

2. A construction project material ordering optimization method considering supply interruptions according to claim 1, characterized in that: Based on the construction plan and material consumption, the material demand within the preset time is predicted to include: Establishing a time series data set based on the construction plan and material consumption; Establishing a prediction model, wherein the prediction model is trained by a maximum likelihood method; The time series data is input into a forecasting model to obtain material demand within a preset period.

3. A construction project material ordering optimization method considering supply interruptions according to claim 1, characterized in that: Based on the material requirements, obtain a preliminary material ordering plan including: Obtain information on the type and quantity of materials required for each stage of the project based on the material requirements; Genetic algorithm is used to minimize the total cost of material procurement as the optimization goal, and a material procurement optimization model is established in combination with the project progress control requirements; The type and quantity information of materials required at each stage of the project is input into the material procurement optimization model to obtain the preliminary material ordering plan.

4. A construction project material ordering optimization method considering supply interruptions according to claim 1, characterized in that: The optimal material procurement channels include: Obtain basic information of potential suppliers; Adopting the analytic hierarchy process to establish a supplier evaluation index system; Input the basic information into the supplier evaluation index system to obtain a comprehensive score; Screening the potential suppliers according to the comprehensive scores to determine the shortlisted suppliers; Conduct a detailed investigation on the shortlisted suppliers to determine the best supplier, that is, the best material procurement channel.

5. A construction project material ordering optimization method considering supply interruptions according to claim 4, characterized in that: The basic information includes: company name, contact information, main business, supply capacity, delivery cycle and material price.

6. A construction project material ordering optimization method considering supply interruptions according to claim 1, characterized in that: Conduct risk assessment based on the optimal material procurement channels and preliminary material ordering plan to obtain supply risks including: Establishing a material supply chain simulation model based on the optimal material procurement channel and the preliminary material ordering plan; A Monte Carlo simulation algorithm is used to introduce random variables into the material supply chain simulation model to obtain operation data of the material supply chain under different scenarios, wherein the random variables include: order fulfillment rate, inventory level and shortage probability; A risk prediction model is established, and the operation data is input into the risk prediction model to obtain the supply risk.

7. A construction project material ordering optimization method considering supply interruptions according to claim 1, characterized in that: According to the supply risk, obtaining the optimal material ordering plan includes: Dynamically adjust procurement time and quantity according to risk level to obtain procurement costs; Obtain the optimal material ordering plan based on the stated supply risk and procurement costs.

8. A construction project material ordering optimization system taking into account supply interruptions, characterized in that include: Information collection module, material demand forecasting module, preliminary plan making module, procurement channel acquisition module, supply risk analysis module and optimal plan making module; The information collection module is used to obtain the construction plan and material consumption; The material demand forecasting module is used to forecast material demand according to the construction plan and material consumption; The preliminary plan making module is used to make a preliminary material ordering plan according to material demand; The procurement channel acquisition module is used to screen suitable material procurement channels; The supply risk analysis module is used to perform risk analysis based on the preliminary material ordering plan and material procurement channels; The optimal plan formulation module is used to formulate an optimal material ordering plan based on supply risks.

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