141 results about "Multimodal transport" patented technology

The invention relates to a multimodal transport cargo tracking method and device, equipment and a medium. According to the method, a standardized data set containing time-space attributes is generated by obtaining original circulation data of different transportation modes and hub nodes; on the basis of the timestamp continuity of the data set, constructing a cargo circulation association graph marked with transportation mode switching points; performing path feature clustering according to continuity identifiers in the map, and generating a standard path template library in combination with a geographic information library; matching and identifying a common path section through a real-time cargo track and a template library to form a cargo grouping tracking label; when the transportation duration in the group exceeds a threshold value, calculating an alternative path combination and outputting a track correction instruction; and generating a track synchronization instruction based on the instruction simulation resource topological relation, updating the association graph and outputting a dynamic track report. Continuous visual tracking of goods in the whole transportation process is achieved, the track path is automatically corrected under the abnormal working condition, and the timeliness and accuracy of logistics state feedback are improved.

The invention discloses a logistics full-process optimization method based on multimodal transport digital development, and belongs to the field of logistics, the logistics full-process optimization method based on multimodal transport digital development comprises the following steps: formulating a unified data exchange standard, and defining a standardized digital format for each type of documents; on the basis of a unified data exchange standard, a unique digital main document which runs through the whole transportation process is created for goods transported each time, and the digital main document serves as a unique digital certificate of the ownership of the goods and a transportation contract; the method has the beneficial effects that a trusted data closed loop capable of automatically circulating, checking and responding to exceptions is constructed by formulating a unified data exchange standard, creating a digital main document running through the whole process, constructing a cloud collaboration platform and embedding an intelligent rule engine; therefore, a traditional mode of multimodal transport depending on manual coordination is converted into an efficient, automatic and transparent digital operation mode.

The invention relates to the technical field of intelligent logistics and operation planning optimization, and discloses an import and export multimodal transport intelligent stowage service method based on a hybrid planning algorithm, which comprises the following steps: establishing an intermodal transport node operation impact database and an intermodal transport network diagram, and defining a node stacking operation state set; according to the force transmission attribute of the corner column of the container, the discrete stacking hierarchy is mapped into vertical pre-pressure, and the node working condition inherent frequency of the container-cargo combination is calculated through a pre-pressure and rigidity correlation model; in combination with node pulse dominant frequency data, constructing a response gain index including resonance interval intensity and parameter fluctuation sensitivity; and establishing a multimodal transport stowage optimization model, bringing the index into a target function, and carrying out collaborative solution on a cargo loading layout, a transport link and a node stacking level. Resonance risks caused by discrete stacking and lateral impact coupling can be effectively recognized and avoided, and a stowage scheme with high structural safety is output.

The invention belongs to the technical field of emergency material multimodal transport scheduling, and particularly relates to an emergency material multimodal transport scheduling optimization method considering risk sensitivity, which comprises the following steps of: A, constructing an emergency material multimodal transport network in which a trunk line and a tail end are coordinated, mapping trunk line transport and tail end transport into a multimodal transport network diagram, determining nodes, feasible line sets and parameters thereof; b, establishing an emergency material multimodal transport scheduling optimization model considering risk sensitivity, and establishing a risk-sensitive scheduling optimization model based on an emergency material multimodal transport network and the obtained parameters; and C, generating a model solving result and a scheduling scheme, converting the scheduling optimization model into a solvable form, generating an executable scheduling scheme, verifying the result, and forming a complete technical closed loop. The method has the advantages that the adaptive capacity and robustness of the emergency logistics system under extreme situations such as path blocking are remarkably improved, and the method is suitable for popularization and application. And important decision support is provided for scientifically coping with disaster rescue.

The invention relates to the technical field of comprehensive traffic planning and logistics optimization, in particular to a multimodal transportation junction transportation path collaborative optimization system and a method thereof.The multimodal transportation junction transportation path collaborative optimization system comprises a data layer, a model layer, an application layer and a feedback layer, the data layer comprises a data acquisition module and a data processing module, the data acquisition module mainly acquires node basic data, network topology data, freight demand data and cost aging data, and the processing content of the data processing module comprises standardization processing, space-time alignment, abnormal value cleaning and data storage processing; and the model layer is used for multi-objective optimization model and intelligent algorithm processing. According to the method, the multi-objective optimization model is constructed, so that the scientific site selection of the transit hub, the intelligent matching of the transportation mode and the path and the collaborative optimization of the whole link cost and the time efficiency are realized, meanwhile, various resource constraint conditions are met, and the overall operation efficiency of the multimodal transportation network is improved.

The invention relates to the technical field of intelligent logistics, in particular to an intelligent logistics collaborative scheduling method based on multimodal transport dynamic optimization, which comprises the following steps of: acquiring high-speed and railway transport data through the Internet of Things, generating an all-road-condition data set, evaluating and eliminating an overload path, matching resources according to task timeliness and cargo attributes, sequencing, continuously tracking and dynamically adjusting, and performing collaborative scheduling. And finally, optimizing and generating an optimal scheduling scheme. Traffic monitoring equipment and a sensor are used for collecting flow, speed, load and cargo information of a path, a transportation data set is generated, path load is evaluated according to the flow, bearing capacity and speed, available paths are screened, resources are distributed according to task priority and path load, task progress is tracked in real time, and the priority and resources are adjusted. And path selection is optimized according to the traffic state, so that task timeliness and resource utilization maximization are ensured.

The invention is suitable for the technical field of intelligent logistics scheduling, and provides a cross-border multimodal transport path dynamic planning method, device and equipment and a storage medium. Multi-source real-time data is acquired and fused, policy information in the multi-source real-time data is analyzed and quantified, and the real-time data is obtained; according to the method, an unstructured policy text is converted into a dynamic constraint condition which can be understood by a multi-objective optimization model, so that dynamic optimization of path planning is realized, changes of an external policy environment can be responded in real time, a generated path scheme achieves a better balance in multiple objectives such as compliance, cost and timeliness, and the path planning efficiency is improved. And the accuracy, timeliness and anti-risk capability of the planning result are improved.

The invention relates to a multimodal transport highway-railway path dynamic planning method, which comprises the following steps of: acquiring multisource dynamic data of highways, railways and connection points in real time, predicting data in a specified time period in the future, and preprocessing the data to generate a dynamic database; a space-time coupling objective function with the shortest total transportation time, the lowest total transportation cost and the highest highway-railway connection efficiency as the cooperation objective is constructed; introducing a fitness dynamic calibration mechanism to correct a target function value; setting a decision window by taking the current moment as a starting point, solving a local optimal path in a rolling manner, and generating an initial scheme including a road real-time navigation path, railway dynamic shift matching and a connection point resource reservation time slice; setting a three-level early warning threshold based on the predicted value, and triggering a hierarchical adjustment mechanism to generate an adjustment scheme; and evaluating the time / cost change rate and the execution feasibility of the adjustment scheme, and executing after reaching the standard. The prospective performance, the dynamic adaptability and the landing reliability of path planning are effectively improved, the transportation cost and delay are effectively reduced, and the highway-railway combined transportation efficiency is remarkably improved.

The invention belongs to the technical field of port multimodal transport scheduling, and particularly relates to a port multimodal transport collaborative scheduling system and method based on real-time data. According to the invention, through the data access and standardization module, the emergency judgment module, the scheduling adjustment measure generation module and the visual presentation and interaction module, automatic judgment and strategy matching of four types of emergencies such as ship delay and storage yard congestion are realized, and an overall scheme of multimodal transport cooperative scheduling is determined. Cooperative scheduling of ship-port-railway-road multimodal transport is facilitated, manual intervention is reduced, response time is shortened, and emergency processing efficiency and safety are improved. Dynamic visualization of full-chain data is achieved through the collaborative dispatching board, differentiated permissions are configured for port dispatchers, railway dispatchers and cargo owners, data safety is guaranteed, the efficient collaborative effect of multiple subjects is achieved, collaborative barriers caused by information asymmetry are solved, and information sharing and collaboration are promoted.

The invention relates to the technical field of intelligent logistics and transportation management, and particularly discloses a multimodal transport goods source allocation system based on data analysis. The system comprises a data access and fusion module, a data quality governance and enhancement module, a time-space association and flow calculation module, a critical path and hub identification module and a dynamic transport capacity allocation decision module, and multi-source data integration, quality governance, time sequence association verification, critical path identification and dynamic transport capacity allocation are carried out. The accurate description of the flow direction of the goods source and the dynamic adaptation of the transport capacity resources are realized, and the operation efficiency and reliability of the multimodal transport system are improved.

A facility for receiving and storing transport containers, in particular containers (4), in seaports and inland ports or intermodal terminals, from external or internal means of transport (5) and for issuing the transport containers, in particular containers (4), to external or internal means of transport (5), comprising a transport container high-bay warehouse (1) for receiving, storing and issuing transport containers, in particular containers (4), wherein the transport container high-bay warehouse (1) has a plurality of transport container storage locations (7) arranged in blocks next to and above one another and storage aisles (8) for storage and retrieval machines (9) running between the block-arranged transport container storage locations (7), characterized in that the facility comprises at least one traffic route (3) for external or internal means of transport (5), which is arranged parallel to the storage aisles (8),and at least one stationary crane track system (2) arranged in the plant, which is arranged perpendicular to the at least one traffic route (3) and the storage aisles (8) and bridges the at least one traffic route (3) and the storage aisles (8) or an area (11) of the plant arranged in alignment with the storage aisles (8).

The application provides a low-carbon multimodal transport network design method considering consignor path selection, comprising: obtaining freight demand data, multimodal transport network topology, parameters of each transport mode, network node transfer time and cost; obtaining consignor preference data covering all origin-destination points in the planning period, brand effect, utility coefficient of transport time and transport cost, low-carbon subsidy data; based on the obtained data, constructing freight flow batch transport constraints, low-carbon subsidy constraints, consignor path selection constraints and multimodal transport network constraints respectively; establishing an objective function for the purpose of pursuing lower carbon emission cost on the premise of not paying a large amount of low-carbon subsidies; under the constraints, using a particle swarm optimization algorithm embedded with CPLEX to solve the objective function to obtain a low-carbon multimodal transport network design scheme. The method can accurately depict the consignor path selection behavior and realize the dual improvement of transport efficiency and environmental benefit.

This invention discloses a supply chain management method and system based on adaptive optimization using traceable containers. The method collects multi-dimensional supply chain data in real time using standardized traceable containers, including inbound volume, outbound volume, inventory, transportation location, environmental parameters, and carbon emission estimates; calculates data volatility and reliability to determine the importance of data collection time; integrates target smoothing parameters and uses reinforcement learning to correct predicted demand; generates multimodal transport schemes using K-D tree matching and the dragonfly algorithm; optimizes production and transportation scheduling based on simulated annealing algorithm, embedding carbon footprint constraints to minimize total green costs; and forms an adaptive closed loop through container feedback to improve system robustness. This method achieves real-time tracking, adaptive optimization, and sustainable development of the supply chain, and is suitable for complex and ever-changing supply chain environments.

This invention relates to the field of multimodal transport route planning technology and discloses a route planning method for multimodal freight transport. The method includes constructing an initial decision tree based on dynamic historical trajectories, where branches are sequenced path nodes, nodes are tool call chains, and leaf nodes are resource consumption profiles. By matching real-time constraints and cost objectives, iterative pruning and branch injection operations are performed on the decision tree to generate an optimized decision tree. After obtaining a set of candidate solutions through deduction, multi-dimensional robustness stress tests are conducted on them to simulate path stability and resource fluctuations under preset disturbances, selecting a subset of feasible solutions. Finally, the optimal solution is dynamically selected based on the real-time status and converted into an operation command. This method can adapt to changes in dynamic constraints and proactively ensure the robustness of solution execution.

The application discloses a kind of intelligent sorting scheduling method and system for multimodal transport scene, it is related to warehousing technical field, the method includes: the transport mode identifier of real-time acquisition multiple transport vehicles, the physical attribute information of corresponding goods and the running state information of stereoscopic sorting system;Multi-modal transport rigid rule information is parsed, and the dynamic boundary condition of multi-modal transport is generated;Transport mode identifier, physical attribute information, running state information and dynamic boundary condition are imported into deep reinforcement learning model;Output according to the goods gravity center parameter dynamic allocation warehousing level goods shelf allocation strategy, and the equipment task sequence of control AGV handling robot motion;Automatic generation sorting execution instruction, to correspond driving stereoscopic sorting system is sorted goods.The application forms "safe storage-time limit coupling-space coordination" technical closed loop, significantly reduces the comprehensive logistics cost of multimodal transport whole link.

Disclosed is a tagless payment management apparatus in which boarding and alighting are detected in a tagless manner by a user terminal carried by a passenger and a tagless device of a station, and travel route information is determined by extracting the location information of the passenger according to the movement of a transportation means by receiving base station information of a mobile carrier from the user terminal, thereby enabling accurate intermodal fare settlement based on an actual travel route of a passenger when settling the payment fare per operating agency of public transportation means capable of transfer.

The invention provides a multimodal transport alternative path and transport scheme generation method based on road network node interruption. The method comprises the following steps: acquiring road network interruption information; if the road network interruption information is updated, for each original path, judging whether the original path comprises the road network interruption information or not; if yes, marking a break point in the original path, constructing an upstream candidate loading and unloading point set and a downstream candidate loading and unloading point set based on a first constraint condition, and selecting a loading and unloading node from each of the upstream candidate loading and unloading point set and the downstream candidate loading and unloading point set by adopting an upper-layer model by taking the minimum duration as a first objective function; inputting the selected first loading and unloading node and the selected second loading and unloading node into a lower-layer model, wherein the lower-layer model adopts a genetic algorithm to construct a multimodal transport replacement path set; and when the transportation unit travels to one end of the path, determining a final path based on the consumed time of each path, and constructing a multimodal transportation scheme.

The application provides a multi-modal intermodal unmanned carrier scheduling method and system, which comprises the following steps: creating a multi-source information collection network and transmitting historical transportation data collected by the multi-source information collection network in real time to a preset edge computing node; standardizing the historical transportation data by the preset edge computing node to generate corresponding standard transportation data in real time, and obtaining a plurality of vehicle models corresponding to the carrier in real time; training a corresponding deep learning scheduling model according to the standard transportation data and a preset neural network in real time, and extracting the position change characteristics and the operation law characteristics corresponding to each vehicle model by the deep learning scheduling model in real time; generating a scheduling priority sequence corresponding to the carrier according to the position change characteristics and the operation law characteristics in real time, and sending a corresponding scheduling instruction to each carrier according to the scheduling priority sequence. The application can improve the use efficiency of the carrier and the transportation efficiency.

An autonomous cargo transporting system transports the cargo on a body of water using the natural current of the body of water to deliver cargo to a downstream port. The cargo system is asymmetric since cargo is delivered downstream using the current but the cargo system is disassembled (drastically reducing the weight) for a multimodal return trip back up the body of water.

This invention discloses a method for optimizing last-mile delivery routes using an "air-ground-rail" collaborative system, belonging to the field of multimodal transport and route optimization technology. The method includes the following steps: S1, constructing an "air-ground-rail" collaborative delivery network model; S2, data collection and preprocessing; S3, constructing a mathematical model for optimizing the "air-ground-rail" collaborative delivery route: setting constraints and constructing the delivery route optimization mathematical model based on the constraints; S4, solving for the optimal route using the model: solving for the optimal route using an accurate solver. This invention constructs a three-tiered, progressive, collaborative, three-dimensional delivery network of subway-freighter-drone, realizing a collaborative mode of subway passenger and freight transport + freighter transfer + drone precision delivery, effectively solving the flexibility and efficiency bottlenecks in urban last-mile delivery. By using deep learning optimization algorithms for route optimization, it improves transport capacity utilization and reduces overall operating costs and carbon emissions.

The application relates to a multimodal transport planning method and device, computer equipment, medium and computer program product. The method comprises the following steps: constructing a coal transport network topology graph according to nodes and transport edges in a coal transport network; the number of nodes and transport edges is multiple, and the transport edge is a transport path between nodes; obtaining node parameters of the nodes and transport parameters of the transport edges in the coal transport network; constructing a target optimization model based on the coal transport network topology graph, the node parameters, the transport parameters and a preset optimization target; determining the transport path, the transport mode corresponding to the transport path and the transport quantity of each type of coal based on the target optimization model. The method can plan a transport path, a transport mode corresponding to each transport path and a transport quantity of different types of coal that can meet the actual demand of a user under the premise of meeting the actual transport condition, so that the actual demand of the user can be met, and the overall transport efficiency is improved.

A computer-implemented method for predicting passenger flow patterns during service disruption in a metro network of a multimodal traffic network. The method comprises the following steps: providing first information associated with the subway network; providing second information associated with an alternative traffic mode of the metro network in a multimodal traffic network; providing third information associated with a topological structure of a part related to service interruption in the subway network; providing fourth information associated with an estimated offload start station-destination station (ODS) demand pattern for the service interruption; providing fifth information associated with predicted irregular routing of passengers in the multimodal traffic network during a service interruption; and predicting a passenger flow pattern associated with the service interruption by computationally simulating based on the first information, the second information, the third information, the fourth information, and the fifth information collectively.

The invention relates to a method for controlling a self-propelled and autonomous rail platform adapted for the transport of at least one container, the method comprising a step of piloting the rail platform according to a piloting mode called long distance mode (E1); and when the rail platform is in an arrival zone, a step of piloting the rail platform according to a piloting mode called last meters mode (E2), comprising the following steps: • identification of a target truck with which a transshipment operation is to be carried out (E3); • determination of a position of the target truck; • positioning of the rail platform according to the position of the target truck; and • control of a transshipment device that includes the rail platform in order to load a container onto the rail platform from the target truck or in order to unload a container from the rail platform onto the target truck (E5).The invention also relates to a railway platform adapted to carry out such a process. Figure for the abstract: Figure 2.

The invention discloses a whole industry chain production and marketing collaborative balance system and method considering value maximization in the technical field of production management. The method comprises the following steps: acquiring supply data, demand data and storage and transportation data; based on the supply data, the demand data and the storage and transportation data, a linear programming model including coal mixing quality cost optimization, multimodal transport path distribution optimization and dynamic inventory balance is constructed with group profit maximization as a target, and an interior point algorithm is adopted for solving to obtain a production and marketing balance plan and operation income prediction in the future N + 12 months; and outputting the production-marketing balance plan and the operation income prediction. According to the method, dual control of quality and cost is realized through a coal mixing quality cost optimization formula, and the problem of excessive or insufficient quality caused by empirical matching in a traditional method is avoided.

This invention discloses an attachment for loading and unloading multimodal transport containers, comprising: a first frame; a tilting frame rotatably connected to the first frame; a rotary drive mechanism drivingly connected to the tilting frame; a lifting frame connectable to the multimodal transport container, the lifting frame being slidably connected to the tilting frame for lifting; and a lifting cylinder connecting the tilting frame and the lifting frame. The lifting cylinder includes a cylinder body and a piston rod slidably connected to the cylinder body and drives the lifting frame to rise and fall. The piston rod of the lifting cylinder is inclined downwards towards the container relative to the sliding direction of the cylinder body. The lifting cylinder has a clamping part that gradually moves inwards to tightly engage the container during the process of the lifting frame being raised by the lifting cylinder. This invention's attachment not only enables the loading and unloading of bulk materials from containers in multimodal transport through a rotary drive structure, but its lifting mechanism also enables lifting to raise the container and clamps it during the lifting process, improving the stability and firmness of the container during loading and unloading.

The invention relates to the technical field of combined transport management, and discloses a multimodal combined transport waybill automatic matching method and system.The method comprises the steps that waybill key information is extracted through a multimodal OCR technology and converted into a unified format through a standardized processing model, then space-time geocoding and multimodal combined transport line simulation are carried out, and the multimodal combined transport waybill key information is obtained; according to the method, path clustering processing is carried out based on a graph convolutional neural network, path selection is optimized by using an ant colony algorithm, a path scheme is updated in real time through a combined transport decision platform, optimization analysis is carried out in combination with real-time data, and an optimal combined transport scheme is finally generated. The intelligent and automatic level of multimodal transport is effectively improved, and the problem that an optimal scheme is difficult to provide for complex multi-waybill multimodal transport in the prior art is solved.

The invention relates to the technical field of multimodal transport, and discloses a multimodal transport capacity management method and system, electronic equipment and a storage medium. In the multimodal transport capacity management method, a first message of in-transit goods is acquired, and the first message comprises goods basic information and goods transport information; acquiring a second message about the waterway transportation ship, wherein the second message comprises the residual warehouse capacity and the route; analyzing the first message and the second message to obtain that the first in-transit cargo meets the transportation requirement of the first waterway transportation ship in the next transportation section, and generating a first scheduling scheme; a first transport tool where the first in-transit goods are located is dispatched to drive into the transfer site, and a first waterway transport ship is dispatched to transfer the first in-transit goods. According to the technical scheme of the invention, the scheduling management waterway and land transportation modes are joined into multimodal transportation, the multimodal transportation mode is guided to organize services, the transportation capacity and the transportation efficiency of the multimodal transportation are optimized, and the effects of reducing the logistics cost and improving the organization efficiency are realized.

The invention relates to the technical field of distribution service, in particular to a multimodal transport logistics collaborative management and control system, which comprises a task triggering coordination module, a handover sequence constraint module, a transport rhythm monitoring module, a state gap complementation module and a label propulsion adjustment module. According to the method, through sequential comparison of task path segments and node time, in combination with task state updating conditions, scheduling differentiation step items are extracted, a task waiting list with control effectiveness is generated, handover promotion after previous uncompleted tasks is blocked according to a state undertaking sequence, rhythm breaking path segments are identified, and state blank fields are complemented. And the continuous conduction direction of the tail-section label is adjusted according to the path capacity, so that task state evolution and path section propulsion are kept in a consistent rhythm, the phenomena of node conflict, task suspension and information disjunction in a transportation chain are reduced, and a transmission system with continuous rhythm and coordinated time sequence is promoted to be formed between path sections. And the conduction stability of transportation scheduling and the smooth cohesion of tasks among the nodes are enhanced.

The invention discloses an intelligent logistics management method based on multimodal transport digital development, and belongs to the field of logistics, and the method comprises the following steps: carrying out the digitization of the size of a cargo and transportation tool loading space before the transportation is started, building a database, and carrying out the digitization of the size of the cargo and transportation tool loading space; the data recorded in the database comprises cargo parameters and transportation tool loading space parameters; according to the technical scheme of the invention, based on the database, digital trial assembly is carried out on the to-be-transported goods through virtual simulation, and the method has the following beneficial effects: before the goods are transported, the digital trial assembly is carried out on the to-be-transported goods through virtual simulation based on the established database, so that a final transportation scheme is obtained. A transportation route, a transportation tool, a cargo loading position and a specific reinforcement scheme are determined before transportation, secondary loading and unloading requirements caused by load changing in the midway of transportation can be effectively avoided through preposed decision making, the loading and unloading operation complexity is reduced, the transportation time cost is reduced, and meanwhile the cargo damage risk is reduced.