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CN-121998306-A - Intelligent optimal configuration system for new energy store decoration resources and use method

CN121998306ACN 121998306 ACN121998306 ACN 121998306ACN-121998306-A

Abstract

The invention relates to the technical field of intelligent engineering management, in particular to an intelligent optimizing configuration system for new energy store decoration resources and a using method thereof, comprising the following steps of obtaining initial parameters of a target store, including available decoration area, functional partition, target date of employment, decoration preset upper limit and available constructor; the method comprises the steps of selecting candidate decoration modules matched with the functional partition from a pre-constructed standard decoration module library, associating a bill of materials, module cost, occupied area, required construction time and experience weight with each module, constructing a resource combination optimization model based on the candidate decoration modules, and automatically outputting an executable decoration scheme on the premise of meeting area, budget, personnel time and purchasing rule constraint by uniformly modeling and intelligently optimizing new energy store decoration modules, materials and construction resources.

Inventors

  • WANG YAMIN

Assignees

  • 无锡筑云科技有限公司

Dates

Publication Date
20260508
Application Date
20251230

Claims (10)

  1. 1. The application method of the intelligent optimal configuration system for the new energy store decoration resources is characterized by comprising the following steps of: Step 1, obtaining initial parameters of a target store, including available decoration area, functional partition, target date of employment, decoration preset upper limit and available constructor time; Step 2, selecting candidate decoration modules matched with the functional partitions from a pre-constructed standard decoration module library, wherein each module is associated with a bill of materials, module cost, occupied area, time of construction and experience weight; step 3, constructing a resource combination optimization model based on the candidate decoration module, wherein the model takes module selection, material purchase and construction time allocation as decision variables and takes area, budget, time and supply capacity as constraints; Step 4, solving the model by adopting an integer programming algorithm to obtain a module selection and material purchase scheme, and automatically switching to heuristic or meta-heuristic algorithm solution if a feasible solution is not obtained within a preset time limit; step 5, performing construction time sequence simulation on the obtained scheme, and detecting and adjusting construction resource concurrency conflicts; step 6, generating a material purchase list and a construction task package according to the final scheme, and transmitting the material purchase list and the construction task package to an enterprise resource planning or supply chain management system; And 7, collecting implementation feedback data, and updating parameters in the standard decoration module library for subsequent optimization.
  2. 2. The method for using the intelligent optimal configuration system for new energy store decoration resources according to claim 1, wherein feasibility pre-screening is performed on candidate decoration modules based on the functional partitions, the available decoration areas and preset decoration rules after the step 2.
  3. 3. The method of claim 1, wherein in step 3, the resource combination optimization model is a mixed integer programming model, and the objective function is a comprehensive function for minimizing total cost or cost and experience, and the constraint conditions include area, budget, time of person and supply constraint.
  4. 4. The method for using the intelligent optimizing configuration system for new energy store decoration resources according to claim 3, wherein the minimum order rule of materials is used as one of constraint conditions when the model is constructed.
  5. 5. The method for using the intelligent optimal configuration system for new energy store decoration resources is characterized in that step 4 comprises the steps of presetting a solution time limit, preferentially adopting integer programming solution, and automatically calling at least one algorithm of large neighborhood search, genetic algorithm or simulated annealing to carry out approximate solution if no feasible solution is obtained after time-out.
  6. 6. The method for using the intelligent optimal configuration system for new energy store decoration resources according to claim 1, wherein the step 5 comprises the steps of dispersing a construction period into time periods, applying concurrent upper limit constraints of personnel and equipment in each time period to simulate, and if a conflict is detected, eliminating the conflict by adjusting module scheduling or replacing a module.
  7. 7. The method of claim 1, wherein steps 1-7 are performed automatically by a computer program interfacing with an enterprise resource planning or supply chain management system and iteratively updating a module library using feedback data.
  8. 8. An intelligent optimizing configuration system for new energy store decoration resources based on any one of claims 1-7, which is characterized by comprising a memory, a storage unit and a storage unit, wherein the memory stores computer executable instructions and a standard decoration module library; a processor coupled to the memory for executing the instructions to implement the method of any of claims 1-7.
  9. 9. The intelligent optimizing configuration system of new energy store decoration resources of claim 8, wherein the processor incorporates a minimum order rule of materials into model constraints when executing instructions to build an optimizing model.
  10. 10. The intelligent optimal configuration system for new energy store decoration resources of claim 8, wherein the processor is configured to call an integer programming solver and solve within a preset time limit when executing the instruction, and automatically fall back to an enabled heuristic algorithm module to solve if the integer programming solver is unsuccessful.

Description

Intelligent optimal configuration system for new energy store decoration resources and use method Technical Field The invention relates to an intelligent optimal allocation system for new energy store decoration resources and a use method thereof, and belongs to the technical field of intelligent engineering management. Background Along with the networked expansion of new energy stores (such as charging pile service points, new energy automobile experience stores and the like), store decoration becomes an important project for chain expansion and brand consistency guarantee; however, the existing decoration management and implementation have a plurality of pain points, namely, on one hand, the inter-store scale, the function partition and the local supply condition are greatly different, and the decoration scheme is dependent on manual experience or a single template, so that material purchasing is repeated, cost waste and experience are inconsistent; In addition, construction schedule management is generally based on overall man-hour estimation, and lacks time-interval concurrent verification, so that key industrial species or equipment concurrency conflicts are easy to generate to influence a utility node, BIM/plan, supplier performance and actual execution data are not effectively integrated for closed loop improvement, so that modeling decision capability is insufficient, reusability is poor and continuous optimization is difficult, existing partial automation means do not tightly combine modular design, purchasing constraint (such as MOQ), multi-constraint optimization and time sequence simulation, and systematic treatment is lacking on feasibility of large-scale solving and engineering delivery guarantee (such as solving overtime rollback strategy), so that improvement on an intelligent optimizing configuration system and a using method of new energy store decoration resources are needed to solve the problems. Disclosure of Invention The invention aims to provide an intelligent optimal configuration system for new energy store decoration resources and a use method thereof, so as to solve the problems in the background technology. In order to achieve the above purpose, the present invention provides the following technical solutions: a new energy store decoration resource intelligent optimal configuration system and a use method thereof comprise the following steps: Step 1, acquiring initial parameters of a target store, wherein the initial parameters comprise available decoration area, functional partition, target date of employment, decoration budget upper limit and available constructor time; Selecting a plurality of candidate decoration modules matched with the functional partition from a pre-constructed standard decoration module library, wherein each candidate decoration module is associated with a predefined parameter set, and the parameter set comprises a bill of materials, module cost, occupied area, required construction person time and experience weight; Step 3, constructing a resource combination optimization model based on the candidate decoration modules and parameter sets thereof, wherein the selection state of the modules, the purchase quantity of each material and the distribution of constructors are taken as decision variables, and the available decoration area, the decoration upper limit, the available constructors and the material supply capacity of a store are taken as model constraints; Step 4, solving the resource combination optimization model by adopting an integer programming algorithm to obtain a module matching scheme and material purchase quantity, wherein if a feasible solution is not obtained within a preset time limit, the method is automatically switched to a heuristic algorithm or a meta-heuristic algorithm to carry out approximate solution; Step 5, performing construction time sequence simulation on the module matching scheme obtained by solving, and detecting whether construction resources conflict concurrently or not; Step 6, generating a material purchase list and a construction task package according to the final scheme after the conflict is eliminated, and transmitting the material purchase list and the construction task package to an enterprise resource planning system or a supply chain management system through an interface; and 7, collecting progress feedback and supplier delivery data in the actual implementation process of the scheme, and updating parameters in the standard decoration module library by using the data for configuration optimization of subsequent stores. And further, performing feasibility pre-screening on the candidate decoration modules between the step 2 and the step 3, wherein the pre-screening is used for eliminating the modules which do not meet the matching condition based on the functional partition, the available decoration area and a preset quantifiable decoration rule. Further, in step 3, the constructed resource combination optimiz