81 results about "Gantt chart" patented technology

The invention relates to the technical field of production scheduling, and discloses a production scheduling visualization method based on big data. According to the method, multi-dimensional production data such as equipment real-time states, material inventory, personnel skills and order delivery periods are collected, and a four-dimensional dynamic constraint model is generated through a dynamic constraint modeling algorithm; and obtaining an initial scheduling scheme by using a mixed integer programming and improved genetic algorithm dual-drive optimization engine, inputting the initial scheduling scheme into a visual interaction module, displaying a result by using a drag-and-drop Gantt chart, and detecting resource conflicts in real time. The feasibility of the adjusted scheduling scheme is verified through a dynamic re-calculation algorithm, and then the model is updated. According to the method, multi-dimensional data are integrated, production scheduling optimization and visualization are realized, production resource conflicts can be effectively solved, the production efficiency is improved, the cost is reduced, and an efficient solution is provided for enterprise production management.

The invention belongs to the technical field of intelligent manufacturing, and discloses a production order automatic scheduling correction method and system, and the method comprises the steps: obtaining a product material list; determining a product process route according to the product type and the process comparison result; marking resource configuration of a process route and a production scheduling state of the product; creating a production order for the products of which the production scheduling states are to be scheduled, and forming a production order level material list according to order information of each level and a product material list; according to the production requirements of the products, the production scheduling logic of the products is selected from the shortest construction period logic, the earliest delivery time logic and the emergency order insertion logic, and production scheduling of the production work orders is carried out; when the production work order is arranged, generating a processing equipment Gantt chart based on the processing information of the processing equipment and the production work order information; and correcting the production scheduling plan of the production order by using the automatic correction logic in the Gantt chart of the processing equipment. The automatic production scheduling efficiency of production is improved, and the customer satisfaction is reduced and improved.

The invention provides a construction progress plan intelligent generation method based on a Monte Carlo tree search algorithm, and particularly relates to a construction progress plan intelligent generation and optimization technology based on a Monte Carlo tree search (MCTS) algorithm. According to the technology, a traditional MCTS algorithm is improved, and rapid generation, real-time dynamic adjustment and resource optimization configuration of a construction progress plan are achieved. Specifically, measures such as dynamic adjustment of an exploration coefficient, nonlinear adjustment of a prior probability and introduction of depth regularization are adopted to improve a traditional upper limit confidence coefficient (UCT) formula. And meanwhile, the total construction period is minimized by combining a dependency relationship between construction steps and constraint conditions of resource finiteness and utilizing a reward function with a negative value of the construction period as a core. Finally, the technology can visually output a construction progress plan in a Gantt chart form, remarkably improves the construction efficiency, reduces the dependence on high-end construction management talents, has a good real-time response capability, and has a wide engineering application prospect.

The invention relates to the technical field of engineering settlement, in particular to a dynamic cost management system and method for an engineering cost settlement process, and aims to ensure that key information such as construction data and approval records cannot be tampered through a block chain technology and improve data credibility; a multi-dimensional deviation analysis algorithm comprehensively evaluates deviations of building materials, manpower, construction periods and the like, an approval process is automatically started when a threshold value is triggered, and abnormity is quickly responded; the optimal approver is automatically matched, and the flow time consumption is shortened; electronic signature and process monitoring support mobile terminal signing and real-time uploading, paper file delay is avoided, a reminding mechanism is automatically triggered when time is out, and the approval progress is ensured; the visual interaction module visually displays cost deviation and progress comparison through a thermodynamic diagram, a Gantt chart and other tools; automatic report generation and settlement support are achieved, manual accounting errors are reduced, and therefore the problem that in the existing project cost settlement process, cost dynamic management is low in practicability is solved.

The present invention provides a collaborative scheduling method for a multi-agent system, comprising the following steps: S1: Modeling a real-world problem into a problem scenario of a multi-agent system by means of graphical modeling and constructing a decision model; S2: Optimizing the weight values of each decision index in the decision model to obtain an optimized decision model; S3: Applying the optimized decision model to the problem scenario for collaborative scheduling simulation and recording the intermediate process of the collaborative scheduling simulation; S4: Generating a scheduling Gantt chart from the recorded intermediate process of the simulated scheduling as the scheduling chart of the multi-agent system. The present invention provides a collaborative scheduling method for a multi-agent system, which can make a more feasible and efficient decision by comprehensively considering various factors during the process of collaborative scheduling simulation, and solves the problem that in some multi-agent collaborative control scenarios at present, multiple agents may wait for each other at different stations, resulting in the inability to perform collaboration.

The invention provides a graphics-based scheduling method and equipment, and the method comprises the steps: obtaining a production task, determining a plurality of production processes and a process relation between the production processes according to the production task, automatically analyzing the production processes and the process relation, and carrying out the scheduling. The scheduling Gantt chart generation method comprises the steps of determining the plan starting time and the plan ending time of each production process in a corresponding production resource, and generating a scheduling Gantt chart according to the plan starting time and the plan ending time of the production resource corresponding to each production process, so that the efficiency and the scheduling accuracy can be improved; in the process of executing the production task by using the scheduling Gantt chart, the production condition is monitored, the scheduling of the scheduling Gantt chart is dynamically adjusted according to the production condition or the user adjustment instruction, and the target scheduling Gantt chart is obtained, so that the operation is faster, and the real-time performance can be ensured.

The invention provides a power transmission network power failure maintenance scheduling optimization method based on Q learning, and the method comprises the steps: generating a Gantt chart through obtaining an original topological file of a power grid, and determining a state judgment rule and a target function of reinforcement learning; integrating the maintenance plans of the subordinate units to a Gantt chart to form an initial maintenance plan; calculating an initial power flow set by using a Matlab built-in power flow solver, and evaluating the operation state of the power grid; in the agent training process, an epsilone-greedy method is adopted to select a maintenance action, update a Gantt chart and a topological file, and update a Q value through a Bellman equation to optimize a maintenance plan; and after training is completed, outputting a Gantt chart of a final power failure maintenance plan. According to the method, the power grid dispatching problem is abstracted into the Q learning problem, power failure dispatching is optimized by utilizing the Q learning algorithm through the reasonable constraint and the objective function, the working intensity of dispatching personnel is relieved, the talent training cost is reduced, the dispatching efficiency and reliability are improved, and the key technical problem of power grid dispatching is solved.

The invention discloses an intelligent production scheduling method and system based on a fixed sequence genetic algorithm. The method comprises the following steps: dividing independent production areas of a workshop; key operation is determined, and modeling is carried out on time of the key operation; generating a process set containing a fixed sequence key job based on a process path, performing crossover variation by using an improved genetic algorithm, and keeping the sequence of internal processes of a task unchanged to avoid an invalid solution; and calculating the shortest processing duration through population iteration, and generating a production scheduling Gantt chart. The system comprises a workshop function area module, a key operation type module, a key operation modeling module and a production scheduling result output module, so as to realize the output of an intelligent production scheduling result. The method improves the production scheduling efficiency and the applicability of the production scheduling result, and is suitable for complex production scenes such as electronic assembly and cabinet debugging.

The invention relates to the technical field of data reasoning, and discloses a mining equipment intelligent manufacturing production scheduling optimization system and method.The system comprises a topological graph generation module, an initial scheduling Gantt chart generation module, a demand strength coefficient acquisition module, a flexible scheduling Gantt chart acquisition module and a final scheduling instruction set generation module; constructing a topological graph based on the process relation of the mining equipment; generating an initial scheduling Gantt chart by taking the part task set as a longitudinal axis and the corresponding general assembly line task sequence as a transverse axis; when a disturbance event occurs, an affected process dependence tree is extracted, task delay cost is evaluated, and a requirement strength coefficient for rescheduling in the manufacturing process is output; generating a flexible scheduling Gantt chart based on the process beat deviation and the equipment utilization rate in the synchronous adjustment manufacturing process; determining a final scheduling instruction set through process path dynamic correction and process optimization results; the efficiency of the mining equipment manufacturing and production process scheduling scheme can be improved.

The invention discloses a workshop scheduling optimization method and system based on large and small model collaboration and closed-loop verification, and relates to the technical field of industrial intelligent manufacturing and operation planning optimization, and the method comprises the steps: carrying out the mixed integer linear programming MILP mathematical modeling through the collaboration of a small-parameter large language model and a general large model; the codes subjected to fine tuning training are adopted to construct a large model, and the MILP mathematical model is converted into the codes; calling a solver to run and solve the generated code, and outputting a solving result or returning error information to the code construction large model; the multi-modal large model carries out matching check on solving results-production scheduling data and a Gantt chart one by one according to constraints of a mathematical model, and backtracks the constraints expressing errors or omission to a modeling layer and a coding layer; and the modeling layer and the coding solving layer carry out maintenance according to feedback information. The workshop scheduling method overcomes the defects of an existing workshop scheduling method in the aspects of processing complex constraints, reducing model training cost, improving solving efficiency, verifying results and the like, and efficient and accurate workshop scheduling is achieved.

The invention relates to the technical field of automatic production line data acquisition and analysis, in particular to a production rhythm Gantt chart generation and analysis method, which comprises the following steps: acquiring PLC rhythm data of a production machine of a factory, generating a production rhythm Gantt chart, and analyzing and comparing the difference between circulating rhythms and the difference between robot torque similarity and an expected value. Compared with the prior art, a production rhythm Gantt chart is introduced in the aspect of fine management of a production plan, and production tasks are refined to specific production links and time points, so that an enterprise can more accurately grasp the production schedule, reasonably arrange resources and ensure smooth implementation of the production plan, and meanwhile, the production plan can be more accurately managed. And through the analysis of the Gantt chart, the enterprise can be helped to predict the production demand in a period of time in the future, and powerful support is provided for the production decision of the enterprise.

The invention provides an information processing method and apparatus, an electronic device, a storage medium and a program product. The method includes the following steps: acquiring a first operation on a first work item in a first system; displaying a first view, wherein the first view comprises a first tree view and a Gantt chart; wherein the first tree view is used for displaying the first work item and at least part of work item associated information of associated work items of the first work item, and the Gantt chart is used for displaying the first work item and scheduling information of the associated work items of the first work item.

This technology generates suggested commands based on the status of a Gantt chart, allowing users to easily manipulate the Gantt chart. [Solution] An information processing device comprising a processing device and a display device, wherein the processing device displays a Gantt chart on the display device, generates command suggestions in natural language format based on the status of the Gantt chart, displays the command suggestions on the display device, accepts a command selected by the user from among the command suggestions, and modifies the configuration information of the Gantt chart based on the selected command.

The present application belongs to the technical field of workshop production scheduling optimization, in particular to a flexible workshop scheduling method and system based on a hybrid whale optimization algorithm. The method comprises S1, analyzing the flexible workshop scheduling problem and determining the mathematical model of FJSP; S2, continuously processing the discrete workshop scheduling; S3, initializing the position of the whale individual in the whale optimization algorithm through Tent chaotic mapping; S4, calculating the fitness of all whale individuals; S5, updating the whale position; S6, searching the neighborhood structure; S7, judging whether the number of whale position updates reaches the maximum iteration number, if not, returning to step S4, if yes, continuing to step S8; S8, outputting the best whale position; S9, outputting the maximum completion time of the found machine and drawing a Gantt chart. The present application has the characteristics of enhancing the local search ability of the whale optimization algorithm, thereby realizing the reasonable allocation of workshop scheduling and improving the production efficiency.

The invention discloses a Gantt chart visualization conflict early warning and scheduling automatic adjustment method and system, and belongs to the technical field of production management, and the method comprises the steps: obtaining the planning time of a newly-added scheduling order, carrying out the conflict detection of the newly-added scheduling order and a scheduled order, and generating a conflict early warning and operation option if there is a conflict; in response to user operation, chain time rearrangement is automatically carried out on the affected orders according to a multi-objective optimization scheduling algorithm; according to the method, conflict information, operation results and scheduling data are visualized in real time through a Gantt chart, user interactive editing and real-time conflict verification are supported, and the system comprises a conflict detection module, an automatic adjustment module and a visual scheduling module which are used for achieving the functions, so that real-time early warning, automatic chain adjustment and visual interactive closed loop of scheduling conflicts are achieved. The problems that in traditional scheduling, conflict discovery lags behind, adjustment depends on manpower, and decision making is not visual are solved, and the automation and intelligence level and response efficiency of scheduling are improved.

This invention relates to the field of data processing and discloses a method, apparatus, computer device, and readable storage medium for generating Gantt charts. The method includes: acquiring user stories of the iterative process of a target task; determining the iteration data corresponding to each user story; determining the cycle of each task and the task completion progress of each target task subject, thereby obtaining the individual work status of each target task subject; and finally, generating a Gantt chart based on the iteration tag, cycle, task completion progress, iteration plan start time, iteration plan end time, and each target task subject. Based on this, the present invention enables the Gantt chart to display the work status of different target task subjects under the same target task, and to reflect the overlap of R&D resources / development resources in the development process of the target task, thereby clearly displaying the development progress of the target task.

The application provides a multi-constraint aircraft assembly scheduling method based on multi-target migration learning, and relates to the technical field of assembly scheduling. Firstly, task decomposition is performed on assembly list requirements in the aircraft scheduling process, an operation station adjustment mechanism is designed, and reconfiguration operation of operation stations corresponding to assembly tasks is completed; then, operation station types required by the assembly tasks are updated, an aircraft scheduling problem is mathematically modeled, a multi-constraint multi-target aircraft assembly scheduling problem model is constructed, an initial task sequence of the tasks is determined, a non-dominated fast sorting genetic algorithm optimization framework with a multi-target elite gene reservation strategy is established, a multi-target migration strategy is established, and a migratable solution set is obtained; finally, a Pareto front solution set is obtained, one solution with the minimum value in the Pareto front solution set is selected, a corresponding specific assembly scheme Gantt chart is obtained, an assembly scheduling table is made, and the assembly process of the aircraft is guided.

The application provides a power grid outage maintenance scheduling optimization method based on Q learning, which comprises the following steps: generating a Gantt chart by acquiring an original power grid topology file, and establishing a state judgment rule and a target function of reinforcement learning; integrating maintenance plans of subordinate units to the Gantt chart to form an initial maintenance plan; calculating an initial power flow collection by using a built-in power flow solver of Matlab, and evaluating a power grid operation state; in the agent training process, an epsilon-greedy method is used to select a maintenance action, the Gantt chart and the topology file are updated, and the Q value is updated through a Bellman equation, so that the maintenance plan is optimized; and the Gantt chart of a final outage maintenance plan is output after the training is completed. The power grid scheduling problem is abstracted as a Q learning problem, the outage scheduling is optimized by using a Q learning algorithm through reasonable constraints and a target function, the work intensity of dispatchers is reduced, the talent training cost is reduced, the scheduling efficiency and reliability are improved, and the key technical problems of power grid scheduling are solved.

The invention discloses a production prediction method for a flexible manufacturing system. The production prediction method comprises the steps of 1, setting algorithm preconditions and scheduling strategy requirements, 2, constructing a core element model, and 3, executing production whole-process simulation prediction. The method effectively solves the problem of production prediction of a flexible manufacturing system caused by uncertainty of varieties, processes and cutters and influence of a scheduling strategy, can simulate the whole production processing process, outputs multi-dimensional results such as work order completion time, a blank and cutter preparation list, a production Gantt chart, a production trend chart and an equipment starting rate, and improves the production efficiency. And reliable data support is provided for a user to adjust a production plan and configure resources.

This invention discloses a flexible job shop scheduling method and system based on a hybrid sandcat optimization algorithm. The method includes the following steps: S1, reading information from a standard format flexible job shop scheduling problem example, and storing the machine information, machine processing time information, and workpiece information in a list for classification; S2, randomly generating multiple feasible process codes and machine codes based on a two-stage coding rule as an initial population; S3, using the obtained initial population, setting the sandcat sensitivity, iteratively optimizing the process codes using a hybrid sine and cosine algorithm of the sandcat optimization algorithm, and updating the machine codes using a uniform crossover operator; S4, recording the minimum maximum completion time in the population after each iteration, and outputting the Gantt chart of the optimal solution obtained by the algorithm after the iteration. This invention solves the problem of inaccurate manual scheduling calculations in industrial production, which requires a large amount of human resources.

The invention provides a production schedule Gantt chart drawing method, device and equipment for a semiconductor factory, and belongs to the field of semiconductor manufacturing, and the method comprises the steps: receiving work order schedules of all processing machines, and determining the time granularity of a time axis of a Gantt chart according to the work order schedules; constructing a data structure hierarchy corresponding to the processing machine to display the association between the business scenes; receiving a real-time Gantt chart fed back by rendering, receiving interface data corresponding to each processing machine, calculating the interface data, and drawing task bars forming a business scene according to time granularity through each Gantt chart component to obtain a real-time Gantt chart corresponding to the work order schedule; and displaying the real-time Gantt chart so as to carry out dragging modification on the task bar, and outputting the real-time Gantt chart after dragging verification. According to the processing scheme provided by the invention, different Gantt chart levels are designed for different types of machine processing flows in a semi-conductor factory, and an association relationship is established; and the page time axis granularity can be adjusted, and more comprehensive information can be displayed.

The invention discloses an industrial production line scheduling method based on Gantt chart driving, and relates to the field of industrial production line scheduling, and the method comprises the following steps: defining production line scheduling scale parameters and constraint conditions; the constraint conditions are converted into Gantt chart visual coding rules, multi-channel coding is carried out in combination with production line scheduling scale parameters, and a structured Gantt chart is constructed; carrying out production process simulation, and extracting operation variables to calculate a total cost value; constructing an annotation data set to carry out image generation model training; and generating an initial Gantt chart based on to-be-scheduled production line configuration parameters, inputting the trained image generation model, obtaining a complete Gantt chart, and outputting a scheduling result. According to the method, multi-dimensional industrial constraints are fused into multi-channel visual coding of a Gantt chart, and semantic rules are embedded in the generation process in combination with a diffusion model, so that visual integration of a production scheduling scheme, closed-loop cost optimization and intelligent generation of physical feasibility are realized.

The present invention belongs to the field of workshop scheduling technology and specifically discloses a workshop scheduling solution generation method and system based on local search, which includes: performing AL operations on a processing process sequence to generate an initial workshop scheduling Gantt chart; cyclically performing IL operations and IR operations on the initial workshop scheduling Gantt chart until a steady state is reached, thereby obtaining an IL Gantt chart and an IR Gantt chart; transforming the IL Gantt chart or the IR Gantt chart to obtain a domain solution, and judging whether the domain solution is feasible based on process constraints to obtain several feasible solutions; determining the head and tail lengths based on the transformed IL Gantt chart and the IR Gantt chart, performing an approximate evaluation of feasible solutions based on the head length and tail lengths, screening out the current solution, and performing the next round of optimization until the optimal solution is obtained as the workshop scheduling solution. The present invention simultaneously utilizes data under the constraints of both processes, thereby improving local search capabilities, significantly reducing unnecessary idle time, and obtaining a more optimal workshop scheduling Gantt chart.

The invention relates to an order process merging workshop scheduling method and system based on operation level constraints. The method comprises the steps of obtaining production data; establishing a mixed integer programming scheduling model taking the minimization of the maximum completion time and the minimization of the assembly time as targets; order combination constraints, process combination constraints and operation level constraints are integrated in the mixed integer programming scheduling model; and an improved grey wolf optimization algorithm is established to solve the mixed integer programming scheduling model, an optimal scheduling scheme is output, the improved grey wolf optimization algorithm combines a double-layer coding scheme of three constraints, a mixed initialization population strategy and an improved hunting mechanism, and a variable neighborhood search and simulated annealing dynamic acceptance mechanism is integrated, so that the optimal scheduling scheme of the hybrid integer programming scheduling model is obtained. Global exploration and local development capabilities are enhanced, so that an optimal scheduling scheme is obtained; and finally outputting the dispatching Gantt chart and issuing and executing. The scheduling problem caused by a complex assembly relation and too long preparation time in multi-variety small-batch production is effectively solved, and the production period is remarkably shortened.

The invention discloses a flexible job shop scheduling optimization method based on a hybrid zebra-artificial travel mouse algorithm, which comprises the following steps: constructing a flexible job shop scheduling mathematical model taking the maximum completion time as an optimization target, and setting constraint conditions; representing a scheduling solution by adopting double-sequence coding; initializing algorithm parameters; designing a continuous-discrete conversion mechanism; randomly initializing a population and determining a global leader; a zebra optimization algorithm exploration stage is combined with a sine candidate step length strategy and a Levy flight disturbance strategy to pre-update individual positions; the individual position is pre-updated in combination with a Levy flight strategy by using an artificial mouse algorithm development stage; and after judging that an iteration termination condition is satisfied, outputting an optimal scheduling scheme and maximum completion time and drawing a Gantt chart. According to the method, the performance of solving the flexible job shop scheduling problem is remarkably improved, a better scheduling scheme can be found to shorten the maximum completion time, and the production efficiency is improved.

The present application relates to a kind of based on production plan fusion's steel enterprise demand mixed prediction and collaborative optimization method and system, belong to plan scheduling technical field.Based on production plan fusion's steel enterprise demand mixed prediction and collaborative optimization method includes using 5G mobile network and wired network to the power system electricity data is collected, and based on mechanism model, electricity load is classified and predicted;Time series superimposed prediction result, estimate future time period demand value;Synchronous user production plan, generate and electricity load linkage's gantt chart, realize visualization;According to optimization adjustment strategy, generate electricity process adjustment strategy.Effectively solved the technical problem of traditional single prediction model in the face of steel production multi-process, complex load fluctuation industry, significantly improve the robustness and adaptability of prediction system.

The invention provides a log processing method and device for drug screening, equipment and a storage medium, and the method comprises the steps: A, obtaining a running log generated in a drug screening process, and converting the running log into an event structured entry to construct a dual index; step B, according to the reverse index, aggregating all structured event entries associated with each material identifier to obtain a task node corresponding to each material, and generating a hierarchical mapping structure of the task node; c, aiming at the execution result code contained in each task node, generating a state identifier, performing verification at the same time, and if the states of different log sources conflict, generating a verification state; and step D, for each task node, according to the execution condition of the sub-steps of the task node, determining the percentage progress, drawing a Gantt chart, and displaying the Gantt chart on a visual interface. By adopting the technical scheme, the abnormality can be found in time by providing a visual interface, and the abnormality response time is shortened.

The invention provides a Gantt chart processing method and device, a computer program product and electronic equipment, and the method comprises the steps: determining cell space information and cell content information corresponding to a Gantt chart according to the task information of the Gantt chart to be drawn; according to the cell space information, transverse grid line attributes and longitudinal grid line attributes are determined, transverse grid lines and longitudinal grid lines are drawn in a cross arrangement mode according to the transverse grid line attributes and the longitudinal grid line attributes, visual cells are formed, and the visual cells are used for simulating virtual cells of the Gantt chart; and controlling the cell content information to be displayed at the corresponding position of the visual cell according to the cell space information. According to the method, the virtual cells in the Gantt chart are simulated by using the orthogonally crossed lines, so that the number of objects needing to be created by the browser can be reduced, the drawing complexity of the cells can be reduced, the rendering performance of the browser can be optimized, and the collapse risk can be reduced.

The invention discloses a project scheduling optimization method based on resource limitation, which comprises the following steps: a model construction step: constructing a project scheduling optimization model under the conditions of resource limitation and uncertain number of project tasks; an objective function determination step: determining an objective function of the project scheduling optimization model by taking the shortest construction period of the delivery project task as an objective; and a model solving step: combining a genetic algorithm and a simulated annealing algorithm to generate a final project scheduling optimization scheme. According to the invention, a chart for representing a personnel-time arrangement mode under the condition of multiple tasks is created according to a set mathematical model, and compared with a Gantt chart, the chart can more intuitively display the work participated by each personnel and the starting and ending time of the work.

This application proposes a heterogeneous multi-core scheduling method and apparatus for maritime unmanned equipment, relating to the field of edge computing heterogeneous multi-core task scheduling. The method includes: acquiring processing tasks and describing their constraints using a directed acyclic graph (DAG); executing the processing tasks using processing cores; ensuring that the processing time and total energy consumption of the processing cores satisfy preset constraints; acquiring a scheduling scheme that satisfies the constraints, and obtaining a first processing time and a first total energy consumption under the scheduling scheme; generating corresponding Gantt charts and energy consumption charts based on the first processing time and first total energy consumption; and adjusting the adaptive dynamic voltage-frequency adjustment (DVFS) technique of the scheduling scheme based on the constraints of the processing tasks, the Gantt chart, and the energy consumption chart. By monitoring task processing time and energy consumption, and leveraging the idle status of processing cores and the constraints of local tasks, the DVFS level is adjusted to compress idle time and reduce energy consumption.