91 results about "Planning method" patented technology

The invention discloses a complex product process route flexible planning method based on a deep cycle Q network. The method is suitable for efficient process route optimization in a dynamic manufacturing environment. The method comprises the following steps: firstly, modeling process characteristics, processing operation, resources and constraint relationships of a part, and constructing a state space and reward mechanism based on a partial observable Markov decision process; and then constructing a long short-term memory network to extract time sequence characteristics in a processing state, and constructing a DRQN on the basis to realize an optimal decision of processing operation. In order to adapt to variable process targets and environments, a self-adaptive reward function adjustment strategy is introduced, and dynamic optimization is realized by adjusting weights such as processing quality, time and energy consumption; and meanwhile, a selective forgetting mechanism is constructed, and model parameters are suppressed and updated by utilizing a Fisher information matrix, so that efficient forgetting of outdated process knowledge is realized, and the migration ability and generalization performance of the model are improved.

The invention provides a model-based consumption type process planning method in a three-dimensional environment. The method comprises the steps of preprocessing design data and reconstructing an EBOM structure; a PBOM structure is constructed in a consumption type distribution mode; constructing an MBOM top layer structure by adopting a consumption type distribution mode; completing the definition of manufacturing items in a consumption type distribution mode; and issuing the MBOM structure. According to the process planning method adopted by the invention, planning is carried out in a three-dimensional space by completely depending on a model entity structure, and the planning of the process flow is efficiently completed by utilizing the accuracy and high-precision characteristics of the three-dimensional model. According to the method, consumption distribution of a product structure, construction of a BOM structure and manufacturing definition can be realized in a three-dimensional environment, so that a process planning task can be accurately and rapidly completed in a visual perspective.

The invention belongs to the technical field of AGV path planning, and particularly relates to an AGV path planning method and system for a production line, and the method comprises the steps: obtaining an instantaneous speed sequence, a planning speed sequence, a current remaining electric quantity, a current load mass, a rated load, and a safe electric quantity of a single transportation task of an AGV; calculating the weight of the current land parcel where the AGV is located in the warehouse area divided into the plurality of land parcels; obtaining the current passing resistance; calculating an electric quantity risk factor; the load condition and the electric quantity risk of the AGV are integrated, the situation passing cost is calculated, the comprehensive cost is calculated based on the geometric distance between the adjacent land parcels and the fluctuation condition of the situation passing cost, and the optimal path is obtained; and performing trajectory interpolation on the optimal path, generating a smooth motion trajectory to control the AGV to run, and feeding back operation data to the central scheduling system to realize optimization. The technical problems of low path planning efficiency and high energy consumption in the prior art are solved.

The invention discloses an industrial park comprehensive energy system low-carbon planning method considering a production process, and the method comprises the following steps: 1, obtaining the production line condition of an industrial park, and constructing a production line model; 2, determining to-be-planned equipment and parameters, and constructing a lower-layer planning operation model considering short-term uncertainty; 3, determining medium and long term uncertainty parameters, and constructing a medium and long term uncertainty set; step 4, determining a multi-objective optimization model; 5, searching a Pareto leading edge by using multi-target reinforcement learning based on a decomposition technology; and 6, selecting a proper Pareto frontier solution, and substituting the Pareto frontier solution into the lower-layer planning operation model to obtain a corresponding planning result. The invention aims to realize low-carbon transformation of an integrated energy system (IRIES) in an industrial area so as to cope with carbon reduction, emission reduction and challenges in a carbon dense area.

The invention belongs to the technical field of power system optimization, and particularly relates to a power system optimization planning method and device considering supply and demand probability balance, and the method comprises the steps: defining edge distribution for a random variable of each geographic position; a hierarchical Copula model is constructed; estimating parameters in the joint Copula model by using a maximum likelihood estimation method; a sample is extracted from the joint Copula function through a Monte Carlo method, and a joint scene is generated; based on the power loss risk and the resource waste risk, setting a comprehensive risk index under the joint scene; establishing a power system planning model, and setting an objective function and constraint conditions; and solving the power system planning model by using a Benders decomposition method to obtain a power system optimization planning scheme. According to the method, the space-time uncertainty of the new energy power system can be accurately quantified, the planning model considering the investment cost and the operation risk is constructed, and the reliability and the economical efficiency of the system are remarkably improved.

The invention discloses an eVTOL cluster collaborative task and charging planning method based on space-time uncertainty, and the method comprises the following steps: S1, building an eVTOL dynamic model based on the flight dynamic characteristics of a four-rotor eVTOL, and building an eVTOL energy consumption and charging model based on the motor system efficiency and the battery discharge characteristics; s2, collaborative decision making and dynamic adjustment are carried out through reinforcement learning algorithms based on double-layer DQN, navigation point coordinates are output, and the reinforcement learning algorithms based on the double-layer DQN comprise an outer-layer DQN agent decision algorithm and an inner-layer DQN agent decision algorithm; s3, inputting the navigation point coordinates into an A * algorithm, and generating an optimal reference path by the A * algorithm according to a multi-dimensional cost function; s4, dynamically adjusting the course angle and the flight speed of the eVTOL according to the optimal reference path by utilizing a PID (Proportion Integration Differentiation) controller until the eVTOL reaches the target node; through multi-agent collaborative decision and online optimization, the space-time uncertainty in the urban airspace is effectively dealt with, and the maximization of the eVTOL cluster operation efficiency and economic benefits is realized.

The invention provides a multi-AGV path planning method in a flexible manufacturing workshop complex environment, and the method comprises the steps: firstly carrying out the modeling of a logistics process of a flexible manufacturing workshop based on a Petri net theory, and then designing a single-AGV path planning algorithm considering the congestion degree based on a constructed Petri net model of the logistics process of the flexible manufacturing workshop, a multi-AGV collision deadlock prevention strategy based on a Petri net is designed, finally, a multi-AGV path optimization algorithm considering an AGV motion state uncertainty scene is designed, a collision conflict prevention method is expanded, and the AGV is constrained by constructing a probability motion model according to a station arrival prediction probability. According to the method, the stability and the transportation efficiency of the multi-AGV system in a complex dynamic environment are remarkably improved, and an innovative solution is provided for realizing intelligent and efficient logistics in a flexible manufacturing workshop.

A demand and supply planning method generates a supply-demand plan including information that specifies operation of an energy generation unit for each unit time in a microgrid having energy generation units being connected to an external energy supply system and generating energy while consuming fuel, an energy storage unit, and a load unit; by calculating an optimization problem related to an objective function including terms related to energy transfer from the external energy supply system in the microgrid and terms related to fuel consumption in the microgrid by using a constraint condition related to a relationship between information related to an operating duration time in each of the one or more energy generation units at a start time for generating the supply-demand plan and a minimum operation time constraint of the energy generation unit; and outputting the supply-demand plan based on a calculation result of the optimization problem.

The invention provides a hot rolling batch planning method and system based on a multi-target model, and relates to the technical field of metallurgical hot rolling production line production plan arrangement. Determining a pool to be selected according to the order demand; constructing a multi-target bonus collection vehicle path problem model; setting a target function and a constraint condition of the multi-target bonus collection vehicle path problem model; and under the constraint of the constraint condition, taking a minimization objective function as an objective, solving the multi-objective bonus collection vehicle path problem model through a third-generation multi-objective non-dominated genetic algorithm, outputting a Pareto optimal solution set, and obtaining an optimal hot rolling batch plan in the Pareto optimal solution set according to the preference of the hot rolling batch plan for different objectives. By means of the method, a high-quality hot rolling batch plan can be obtained, and the productivity and benefits of a hot rolling plant are effectively improved.

The application discloses an arc additive and subtractive composite manufacturing process planning method and system, and specific steps of the method include three-dimensional modeling, slicing and layering, collision interference detection, cutter accessible area correction, interference identification to obtain an initial machining sequence, and process merging optimization to obtain an optimal process planning scheme. Compared with the prior art, the application proposes a cutter accessible area correction method fusing arc additive process characteristics, and realizes initial partitioning of the component without interference. On this basis, process merging optimization is carried out with the optimization target of minimizing the number of additive and subtractive process alternations, and a process planning scheme satisfying the interference-free constraint is obtained. Compared with the prior art, the application effectively solves the technical problems of poor process planning adaptability, process redundancy, high alternation cost, single manufacturing process data acquisition, and lack of real-time monitoring and intelligent control in the arc additive and subtractive composite manufacturing.

The invention discloses a production plan generation method and device, electronic equipment and a storage medium, and relates to the technical field of production plan generation. The method comprises the following steps: acquiring basic information related to a production plan; based on the basic information, constructing a constraint condition and a plan target corresponding to the production plan; wherein the constraint conditions comprise order dimension constraint, equipment dimension constraint and man-machine coordination dimension constraint; the planning target comprises an order outgoing cost dimension, an equipment use cost dimension and an order processing waiting time dimension; and generating a production plan corresponding to the basic information through a mixed integer rule MIP model based on the constraint condition and the plan target. Therefore, the limitation of a traditional artificial planning method in processing large-scale orders and complex man-machine coordination tasks is effectively solved, the plan generation efficiency is improved, the resource utilization is optimized, the production cost is reduced, and the response capability and quality of the plan are remarkably improved.

The invention relates to a power system multi-resource collaborative planning method based on attribution analysis, and belongs to the technical field of power system planning. Comprising the steps of constructing a target function by taking the minimum supply and demand mismatching degree as a target based on the load demand of a power system and the output of each unit, and constructing a planning model based on set constraints and the target function; solving the planning model based on the multiple groups of boundary condition values of the planning model to obtain corresponding planning schemes; analyzing to obtain quantitative expressions of the influence degrees of the boundary conditions and the constraints on the planning scheme; and corresponding boundary condition values are adjusted based on quantitative representation, the planning models are solved, and the planning scheme with the lowest planning cost in solving results is selected as the optimal planning scheme. According to the method, the key factors influencing the planning scheme are determined by performing attribution analysis on the electric power planning, and the optimal planning scheme is determined by adjusting the key factors, so that the scientificity and the economical efficiency of the planning scheme are further improved.

This invention provides a multi-stage planning method and system for various types of energy stations that take into account mixed traffic flow. [Solution] A multi-stage planning method for various types of energy stations considering mixed traffic flow includes the steps of: constructing a traffic topology; considering a time-dependent road impedance function model and obtaining traffic conditions in the traffic topology of different types of energy vehicles; considering the travel needs of different types of energy vehicles and planning various different types of energy refueling routes for each; and constructing a mixed traffic flow model based on the obtained various different types of energy refueling routes for each type of energy vehicle with the goal of minimizing total costs, thereby completing the multi-stage planning for various types of energy stations.

The present application provides a path planning method that supports multiple devices and multiple scenarios, including: obtaining the setting parameters for each type of AGV; obtaining the constraints of each planned path; splitting the setting parameters and constraints respectively, and constructing a path planning pipeline based on the split setting parameters and the constraints; obtaining the input constraints of the target logistics task, and filtering and planning the split setting parameters and the constraints through the path planning pipeline based on the input constraints, so as to obtain a path planning solution that meets the target logistics task. The above solution dynamically plans the shortest path between workstations through the construction of the path planning pipeline, improves the overall production efficiency of the factory, and realizes path planning for different types of AGVs in complex scenarios, which can adapt to most industrial scenarios.

The invention discloses a digital twin-driven LCD backlight plate production collaborative management and control method and system, and particularly relates to the technical field of production management. The method is used for solving the problems of resource mismatching, quality risk and efficiency loss caused by neglecting the capability difference of a production line in a specific process and a dynamic coupling relationship between process paths of products in use in an existing static planning method. A digital twin model corresponding to a physical production line is constructed, a process capability vector and a process path vector are integrated, a candidate production line set is identified based on vector data, a parameter resonance risk level is evaluated, a key bottleneck process in a process network topology is positioned, and a dynamic routing scheme is generated to avoid high-risk paths and bottlenecks. And a manufacturing execution system triggers real-time adjustment of a product production path to realize dynamic collaborative optimization of production resources and order demands.

To provide a planning program, a planning method, and an information processing apparatus capable of suppressing local congestion in a feeding order into a work line.SOLUTION: A planning program that causes a computer configured to sequentially specify the order of processing a plurality of types of objects in a work line for processing the plurality of types of objects, to execute processing of: specifying, as a basic value, a ratio of the number of objects of each of the types to the total number of the plurality of types of objects; calculating, as an appearance probability, a value obtained by subtracting the number of objects of the type of which a processing order has been determined, from a product of a process number and the basic value for each of the respective types; and changing a frequency of the processing for each of the types in accordance with a selection status of each of the types, in selecting a type to be processed next using the calculated appearance probability.SELECTED DRAWING: Figure 4

To provide a replenishment planning system, method, and program for creating a replenishment plan for replenishment of an item based on whether or not the item has been shipped recently from a warehouse.SOLUTION: A replenishment planning system 100 comprises: an unshipped days calculation unit that calculates the number of days elapsed since the most recent shipping date; a shipping interval expected value calculation unit that calculates a shipping interval expected value from the time-series change amount of a shipping interval; a shipping interval variation calculation unit that calculates a shipping interval variation from the time-series change amount of the shipping interval; a shipment-time expected shipping quantity calculation unit that calculates a shipment-time shipping quantity expected value from the time-series change amount of a shipment-time shipping quantity; a shipment-time shipping quantity variation calculation unit that calculates a shipment-time shipping quantity variation from the time-series change amount of the shipment-time shipping quantity; a shipping occurrence expected value calculation unit that calculates a shipping occurrence expected value from the number of days elapsed, the shipping interval expected value, and the shipping interval variation; and a replenishment planning unit that calculates a forecasted shipping quantity for each item based on the shipping occurrence expected value, the shipping quantity expected value at the time of shipment, the shipping quantity variation at the time of shipment, and inventory amount data.SELECTED DRAWING: Figure 1

This application discloses a planning method, system, equipment, medium, and product for a new energy hydrogen production system based on multi-timescale risk quantification, relating to the field of new energy hydrogen production technology. The method includes: constructing a new energy hydrogen production system; constructing an operational model; constructing a risk quantification model; acquiring hourly predicted and historical power generation data of the new energy generator units; calculating the prediction error based on the predicted and historical power generation data; constructing constraints based on the operational model and the prediction error; constructing a planning mathematical model for the new energy hydrogen production system considering multi-timescale risks based on the constraints and the risk quantification model; and solving the planning mathematical model for the new energy hydrogen production system considering multi-timescale risks under the constraints, with the objective of minimizing the annual comprehensive risk level, to obtain the optimal planning scheme. This application improves the safety and reliability of the new energy hydrogen production system.

The invention provides a steel production technical scheme planning method and device, equipment and a medium, and the method comprises the steps: obtaining the productivity, production age limit and production technical scheme application data of a steel mill employing a corresponding technical scheme, and carrying out the clustering of the production technical scheme application data; fitting the technical income data of different production technologies in the income evaluation dimension with the productivity and the production age limit of the steel mill adopting the corresponding technical scheme, and training a preset scheme planning model according to the technical income data of different production technologies in each steel mill type in the income evaluation dimension; inputting the productivity and the production age limit of the target steel mill into a target evaluation formula, and inputting the technical profit evaluation value into the target production technical scheme planning model to obtain a production technical scheme planning result; the steel mill production technical scheme is planned based on the production technical scheme application data, the accuracy and efficiency of production technical scheme planning are improved, and quantitative analysis data and technical support are provided for subsequent engineering practice.

To provide a planning program, a planning method, and an information processing apparatus capable of planning a feeding order to a work line while suppressing man-hours of a user.SOLUTION: A planning program that causes a computer to execute processing of: generating a plurality of priority order patterns with priority orders assigned thereto, for a plurality of work groups, when processes selected from the plurality of work groups are sequentially performed on each of a plurality of objects; specifying the order of processes in the work group for each of the priority orders according to the priority orders of the plurality of priority order patterns; and specifying the order of the plurality of objects corresponding to a combination of the specified processes.SELECTED DRAWING: Figure 6

The invention discloses a demand side capacity two-stage robust planning method considering cost and flexible resources, and belongs to the technical field of power system operation and maintenance. According to the method, uncertainty adjustment parameters are introduced, a box type uncertainty set capable of flexibly adjusting conservative property is constructed, the inherent defect that a traditional robust optimization method is too conservative is effectively relieved, the model can dynamically adjust the boundary of the uncertainty set according to different bearing capacities of an actual system to risks, and the robustness of the system is improved. Therefore, refined balance of economy and reliability can be realized in the planning stage. According to the constructed two-stage robust optimization model considering the electricity-carbon coupling mechanism, the carbon transaction cost is taken as an important component of the operation cost to be incorporated into the target function, and the requirements of the national green low-carbon energy strategy are effectively responded. According to the improved column generation and interior point hybrid algorithm designed by the invention, a self-adaptive scene screening mechanism and a gradient guide initialization strategy are provided, the solving time is remarkably shortened, and meanwhile, the global optimality of understanding is ensured.

To solve the problem of a physical distribution plan composed of a combination of many variables to be considered, that it is difficult to derive an optimum solution to the physical distribution plan in a realistic time.SOLUTION: A physical distribution planning system 500 comprises: an optimization control device 200 for generating a learning model that accepts data for each element of a physical distribution network to transport commodities as input and outputs a physical distribution plan under constraint conditions; and a solver device 300 for executing optimization using the learning model and calculating an optimum solution to minimize the cost required for physical distribution as an objective function. The optimization control device 200 assigns, on the basis of a manufacturing lot of a commodity included in the data, a lot number to the commodity, as well as sets a constraint necessary threshold from the lot number, creates a constraint that the order of lot numbers must always be observed for older manufacturing lots than the constrain necessary threshold, and creates a constraint that the order of lot numbers would better be observed for newer manufacturing lots than the constrain necessary threshold whenever possible.SELECTED DRAWING: Figure 8

To create, accurately and with a low load, a tentative journal scheduled for a cash flow at acquisition of a budget containing a non-accounting title.SOLUTION: A cash flow schedule creation device of an embodiment includes budget accept processing means which accepts input of budget data containing a settlement term, a general account title containing a non-accounting title, an auxiliary title, and the amount of money for each month, and refers to a budget accepting journal definition master with the general account title and the auxiliary title as keys on the basis of the budget data, to create journal data scheduled for a cash flow containing occurrence date, a credit / debit classification, a general account title, an auxiliary title, an auxiliary breakdown title, and the amount of money calculated based on the amount of money for a target month of the budget data, a classification of the amount of money of a fund obtained from the budget accepting journal definition master, a fund allocation month, a fund allocation rate, and the calculated amount of money.SELECTED DRAWING: Figure 1

The invention provides a ship body large-assembly goods store design and planning method, a medium and a terminal. The method specifically comprises the steps of obtaining a production plan and making a demand plan based on the production plan; analyzing the demand plan to obtain a stable period and demand days of the large assemblage; designing goods stores based on the stable period and the number of required days of the large assemblage; and obtaining a plan advance period and a plan period, and formulating a store use rule. Through the method, the inventory level can be remarkably reduced, the inventory cost is reduced, and the circulation efficiency is improved.

The invention relates to a reverse deduction power system planning method, which comprises the following steps of: obtaining a long-term annual total installed capacity target in a long-term planning layer; in the middle-term coordination layer, an adjusted long-term annual total installed capacity target is obtained; in the short-term verification layer, outputting a final long-term annual total installed capacity target; the long-term planning layer, the middle-term coordination layer and the short-term verification layer jointly form a long-term-middle-term-short-term three-layer coupling deduction framework, and iterative optimization circulation of verification is operated from bottom to top. According to the method, a long-term-middle-term-short-term three-layer coupling deduction framework is constructed, reverse solution is carried out with the carbon peak reaching target year as rigid constraint, the problem that long-term strategy and short-term operation are disjointed frequently occurring in traditional electric power planning is effectively solved, the planning result has perspectiveness, and the method is suitable for large-scale popularization and application. The scientificity and the performability of the planning scheme are obviously improved; the total economic cost of low-carbon transformation of the whole power industry is effectively reduced, and collaborative improvement of economy and reliability is achieved.

To realize a delivery planning in consideration of a status of an edge between nodes.SOLUTION: A delivery planning device includes: an edge calculation part which calculates edge information, which is a travel time or travel distance between nodes, for each pair of nodes in a plurality of nodes; and an algorithm calculation part for solving a delivery planning problem determining a route to provide a service to the plurality of nodes by a moving object departing from a certain location using a neural network that performs reinforcement learning using an actor-critic method. The algorithm calculation part solves the delivery planning problem using a feature quantity related to the edge information obtained by the edge calculation part.SELECTED DRAWING: Figure 1

The invention provides a work planning method, a work planning system, and a program, which can limit the work area of a forklift and realize the application of minimizing human intervention in the work of lifting and lowering goods from a storage rack and the work of transporting the goods. A work planning method for making a picking work plan on the basis of shipment information includes the steps of: determining products to be loaded on an AGV and making a product list; determining a storage shelf corresponding to the commodities in the commodity list; distributing forklifts to goods on the basis of the information of the determined storage shelves; and making work plans including commodity information, work time, and work places for the forklift and the AGV respectively.