3results about How to "Maximize storage capacity" patented technology

The invention discloses a railway station container scheduling optimization method, system, equipment and medium, and belongs to the technical field of railway station container scheduling, and the method comprises the steps: building a railway container yard container space assignment optimization model based on a container space freedom degree yard information representation method and a container stacking optimization process, stacking the to-be-stacked boxes by using a box stacking algorithm from a box yard to a train to obtain the optimal stacking positions of the to-be-stacked boxes; extracting the to-be-fetched box by using a box lifting algorithm from a train to a box yard to obtain an optimal target box position of the to-be-fetched box; using a heuristic algorithm to solve the railway container yard container quantity balanced distribution model to obtain the optimal division of the container area container quantity; and solving the railway container yard container space assignment optimization model by using a heuristic algorithm in combination with optimal division of container area container quantity to obtain an optimal container space assignment mode.

The present invention discloses an intelligent load balancing method based on a zero-sample hybrid expert model, comprising the steps of: creating a task spectrum mapping relationship through zero-sample learning, generating virtual labels, refining the requirements of new tasks into resource requirement feature spectra through multi-dimensional feature cross-projection, and predicting the multi-dimensional resource requirements of new load balancing tasks; establishing a multi-perspective hybrid expert dynamic integration mechanism, configuring multi-perspective hybrid collaborative experts for tasks, applying a combination of several expert models to different demand dimensions, creating virtual image samples of new tasks, simulating resource requirements and their load effects in a virtual environment, and generating an initial resource allocation plan; in the face of dynamic load fluctuations, distributing task cells to nodes with sufficient resources; the method improves the robustness and efficiency of the system, simplifies the implementation process, and has broad application prospects and practical value.