12 results about "Tabu search" patented technology

The application provides a multiple layout splitting method, system, medium and program product. First, an initial splitting coloring operation is performed based on a saturation priority strategy to generate an initial layout splitting scheme. Then, the global exploration ability of a tabu search algorithm is utilized, and a preset target function is combined to perform multiple rounds of iteration update operations on an initial conflict node set to generate a multiple layout splitting optimization scheme. For ultimate conflict nodes that cannot be completely eliminated by the tabu search algorithm, a backtracking pruning algorithm is started to maximize the attempt to eliminate all ultimate conflicts to generate a final multiple layout splitting target scheme. The application combines the initial optimization ability of the saturation priority strategy, the global exploration ability of the tabu search algorithm, and the quality guarantee of the backtracking pruning algorithm to realize accurate splitting of multiple layouts, guarantee splitting quality and lithography yield, improve splitting efficiency, reduce computational complexity, and adapt to the needs of multiple layout splitting.

The application discloses a satellite slant beam inter-beam interference avoidance method and system based on cost flow and dynamic graph coloring, and accurately models the interference range of slant beams in a multi-satellite satellite hop-beam system, considers the influence of the slant beams when modeling the anti-beam inter-beam interference hop-beam pattern design problem, divides the dynamic graph coloring problem into two sub-problems of satellite-wave position matching and hop-beam time slot allocation which are coupled with each other, pre-solves the satellite-wave position matching problem by using a minimum cost maximum flow algorithm, obtains a satellite-wave position matching initial solution which maximizes the sum of satellite elevation angles of all wave positions in the system under the constraint of the maximum number of simultaneously opened beams of the satellite, and on the basis, combines a tabu search algorithm and a graph coloring algorithm to jointly optimize the two sub-problems, so as to further improve the inter-beam interference avoidance performance of the same hop-beam time slot opened beam. The application can obtain a multi-satellite hop-beam scheme with minimum inter-beam interference, and the algorithm has low complexity and is convenient for actual system implementation.

The application provides a multiple layout splitting method, system, medium and program product. First, an initial splitting coloring operation is performed based on a saturation priority strategy to generate an initial layout splitting scheme. Then, the global exploration ability of a tabu search algorithm is utilized, and a preset target function is combined to perform multiple rounds of iteration update operations on an initial conflict node set to generate a multiple layout splitting optimization scheme. For ultimate conflict nodes that cannot be completely eliminated by the tabu search algorithm, a backtracking pruning algorithm is started to maximize the attempt to eliminate all ultimate conflicts to generate a final multiple layout splitting target scheme. The application combines the initial optimization ability of the saturation priority strategy, the global exploration ability of the tabu search algorithm, and the quality guarantee of the backtracking pruning algorithm to accurately split the multiple layout, guarantee the splitting quality and the lithography yield, improve the splitting efficiency, reduce the calculation complexity, and adapt to the demand for multiple layout splitting.

The application provides an improved tabu search topology optimization method of a marine wind farm power collection system, which is based on the positions of wind turbines to intelligently preliminarily group and sort, to form an initial connection scheme, to connect all the wind turbines in each group with the minimum cost, to calculate the group cable cost, to check whether the lines cross, to impose a penalty in the total cost if the lines cross, to ensure that the scheme is feasible, to compare the current scheme with the historical best, to update the record and intelligently exchange the wind turbine groups to explore a new scheme, to repeat the optimization process until the number of iterations is satisfied, and to finally output a globally optimal topology scheme. The application has the advantages of better optimization effect, significantly improved economy, higher calculation efficiency, stronger engineering practicability, better algorithm robustness, better scheme reliability, high design automation degree and strong auxiliary decision-making capacity.

The invention discloses a dry bulk storage yard truck scheduling method, system, medium and equipment, and relates to the technical field of truck scheduling, and the method comprises the steps: constructing a motion state conflict set based on physical space envelope overlapping judgment through extracting a motion state sequence of a truck on a driving path and a scanning volume corresponding to each state; then, converting a space exclusive constraint into a time sequence constraint, and constructing a mixed integer programming model taking minimization of the maximum completion time as a target; in the solving stage, the invention provides an iterative fixed optimization IFO algorithm fused with a tabu search mechanism, iterative local reconstruction is carried out on truck subset sorting to optimize an initial operation sequence, and real-time response to dynamic disturbance of the storage yard is realized in combination with a rolling time domain strategy. According to the method, the problem of path conflict caused by multi-vehicle movement behaviors in a complex storage yard environment is effectively solved, and the operation continuity and safety of an automatic storage yard are remarkably improved.

The application discloses a kind of Chinese construction automatic learning method based on correlation degree, which is divided into background statistical corpus, candidate construction generation corpus, MDL optimization corpus and determine the best correlation degree threshold corpus by corpus;Then the correlation degree of each information pair is calculated in the background statistical corpus, and the locally optimal correlation degree is searched on the small corpus for determining the best correlation degree threshold, so that the construction set obtained with the threshold has the best MDL evaluation index;Then the candidate construction set is generated using the locally optimal correlation degree on the larger corpus generated by candidate construction, and the correlation degree characteristics of candidate construction are calculated;Finally, the best MDL candidate construction set is searched by tabu search algorithm and variable neighborhood search algorithm on the MDL optimization corpus, and the Chinese construction set is obtained.The application can automatically learn to good quality Chinese construction, which can be directly applied to natural language processing technology, and has good application prospect.

This invention provides a dynamic optimization method and system for a shipboard assembly welding line based on digital twins. The method includes acquiring and preprocessing raw data to generate a model dataset, and establishing a three-dimensional digital twin model using the model dataset. During the twin synchronization cycle, a state observer combined with the three-dimensional digital twin model is used to map the physical entities of the field equipment to generate corresponding virtual twins. During the twin synchronization cycle, the state observer updates the state of the virtual twins and acquires equipment calibration difference data. When the equipment calibration difference data is greater than or equal to an optimization threshold, the welding process data and welding production line scheduling data are dynamically optimized using an improved genetic algorithm and a tabu search algorithm. The method and system provided by this invention can improve the production line efficiency and quality of the assembly welding line while reducing production line energy consumption.

The application discloses a text classification method and device based on a taboo search algorithm and a storage medium, and the method comprises the following steps: S1, collecting a text data set; S2, selecting an original text sample from the text data set, and generating a corresponding initial adversarial sample by using a Levy flight; S3, searching for an optimal adversarial sample in a search space by using the taboo search algorithm, and adjusting a search direction by using cross variation in the searching process; S4, training a deep learning model by using the original text sample and the optimal adversarial sample; and S5, inputting an actual text into the trained deep learning model to generate a text classification result. The deep learning model is trained by using the adversarial sample, so that the model remains stable and reliable under adversarial attacks, and the accuracy of text classification is improved.

The application discloses a part cutting path planning method considering scrap line selection and priority constraint, and first generates an initial scrap line candidate set according to preset heuristic generation rules, and obtains an effective scrap line candidate set through screening; on the basis, a greedy insertion algorithm is adopted to generate an initial solution of a cutting path and take the initial solution as a current solution; then, a plurality of path optimization operators are adopted to optimize the current solution, and a neighborhood solution set is generated; finally, a tabu search algorithm is adopted to search an optimal neighborhood solution from the neighborhood solution set, and take the optimal neighborhood solution as an optimal solution of the cutting path. The application solves the problem that in the existing part cutting path planning method, a scrap line generation and a cutting path planning are usually split into two independent steps, which easily leads to the problem that a locally optimal scrap line scheme hinders a globally optimal path and a large amount of unnecessary idle movement is generated.

This invention relates to the field of tunnel boring machine (TBM) design technology and discloses a tool layout method for a circular cutterhead of a TBM. The method includes: constructing a mathematical model of tool layout incorporating cutting force data from a CSM model; determining the optimization objective and constraints for minimizing eccentric force and eccentric moment; initializing a gray wolf population by mapping discrete permutations to continuous vectors using a continuous encoding strategy and calculating fitness values; executing a global iteration of the gray wolf optimization algorithm, using social hierarchy to guide population updates; embedding a tabu search strategy in the global iteration to perform local neighborhood search on the optimal individual to generate and selectively replace the optimal solution; and finally outputting the tool layout scheme and verifying its feasibility. This invention effectively solves the problem of tool layout easily getting trapped in local optima through the synergistic cooperation of the gray wolf algorithm and tabu search, improving the mechanical balance and solution efficiency of the cutterhead design, and reducing design and production costs.

This invention relates to a method for optimizing the layout of a forklift-type AMR (Automatic Warehouse Regulator) flexible high-density warehouse and for dynamic warehouse location scheduling. The steps are as follows: S1. Determine the optimal physical layout parameters of the warehouse, establish a comprehensive efficiency maximization model E, and use the NSGA-II algorithm to solve for the Pareto optimal solution set; S2. Construct an outbound co-occurrence matrix, introduce a time decay factor to handle dynamic business changes, and use the k-Means clustering algorithm to intelligently group materials and map materials to physical areas of the warehouse; S3. Integrate the selection of outbound material cages and the planning of the relocation path of obstructing material cages into an optimization problem, and solve it using a deeply customized tabu search algorithm; S4. Construct a directed graph model to transform the problem of matching inbound requests with candidate warehouse locations into a minimum cost maximum flow problem; wherein, the cost function is: cost = α × current outbound interference + β × estimated future outbound impact. This invention maximizes the overall operational efficiency of the warehouse.