118 results about "Transportation plan" patented technology

The invention relates to an electronic equipment intelligent transfer container management system based on the Internet of Things and Al, and the system achieves the real-time monitoring, risk prediction and automatic adjustment in a transportation process through integrating edge calculation, a federal learning framework, a risk prediction algorithm and a block chain evidence storage technology. The system adopts various sensors to monitor data such as temperature and humidity, vibration, air pressure, inclination angle and the like in the container, and carries out real-time processing through the edge calculation unit, so that the environment in the transportation process meets equipment requirements. Meanwhile, an LSTM and a random forest algorithm are used for predicting the equipment damage probability, and a transportation scheme is dynamically adjusted according to a risk assessment result. In addition, the block chain technology is used for recording key events and uploading the data to an alliance chain, so that the non-tampering and traceability of the data are ensured. The intelligent management system provided by the invention not only improves the safety and transparency of the equipment transportation process, but also optimizes the transportation path and reduces the energy consumption.

The invention discloses a chaos annealing ant colony-based adversarial blocking timeliness emergency material transportation toughness intelligent decision-making method, and relates to the technical field of intelligent emergency scheduling and optimization. The method comprises the steps of 1, extracting scene data and converting the scene data into model parameters; step 2, constructing a mathematical model for survivability optimization; 3, initializing algorithm parameters and generating an initial path; 4, dynamically adjusting the temperature and the pheromone volatilization rate; 5, generating an adversarial blocking perception path and implementing detour repair; 6, updating pheromone distribution based on an annealing criterion; and step 7, locking the critical path and outputting an optimal transportation scheme. According to the method, timely delivery of materials can be guaranteed in a complex road network blocking and emergency demand scene, the timeliness and toughness of an emergency transportation system are improved through a chaos annealing mechanism and an adversarial blocking simulation technology, the method can be widely applied to the fields of natural disaster rescue, public health event response and the like, and a scientific basis is provided for emergency decision making.

The invention discloses a reservation type vehicle and cargo matching method and device applying an AI model and a storage medium, and the method comprises the steps: receiving a cargo owner transportation plan, and generating a vehicle finding demand; obtaining reserved driver information, and determining a transport capacity pool to which a reserved driver belongs and a corresponding transport capacity classification attribute; the AI model with the built-in vehicle and cargo matching rule is combined with the transport capacity pool and the corresponding transport capacity classification attribute to intelligently match a target driver, and a transport task is generated to notify the target driver to receive an order and carry; and the intelligent matching process improves the priority of the allocated transportation tasks of the reservation drivers with the goods-fixing certificates. And receiving an activation signal of the order certificate, distributing the AI digital person to follow up the performance condition of the target driver in real time, automatically identifying the risk, and sending out a guide prompt. According to the invention, on the basis of an AI large model technology, reservation type vehicle and goods matching based on a goods fixing certificate is realized, the space-time matching efficiency of a vehicle source and a goods source is optimized, the vehicle and goods matching efficiency is improved, a driver is assisted in conveniently and rapidly completing a performance transaction in a full-service process through an AI digital person, and the service quality of the driver is improved.

The invention discloses a marine assembled box shipping management method based on an Internet of Things platform, and belongs to the technical field of logistics management. The method comprises the steps of obtaining a cargo list, extracting cargo attributes, analyzing chemical attributes and physical characteristics, and generating a conflict risk assessment report; constructing a time limit prediction model based on the multi-link time data, and optimizing the loading priority; a loading scheme is optimized through a space distribution and dynamic adjustment algorithm, so that the compatibility and the transportation timeliness of goods are ensured; and the shipping state is monitored in real time, emergency adjustment is triggered according to the delay risk, and execution of a transportation plan is ensured. The loading efficiency can be effectively improved, the transportation safety is guaranteed, the transportation risk and delay probability are reduced, and the logistics management level is comprehensively improved. The method is suitable for the fields of intelligent logistics, shipping assembly box transportation and the like, and efficient and accurate decision support is provided for shipping management.

The invention discloses an intelligent supply chain transportation management platform based on the Internet of Things, and relates to the technical field of the Internet of Things. Historical transportation data, real-time order information and production progress demands are utilized to construct an input feature matrix, and a time sequence prediction method based on a recurrent neural network is adopted to improve the accuracy of transportation demand prediction; low-efficiency distribution and lagging response of transportation resources are avoided, a multi-agent collaborative scheduling module sets a transportation agent agent based on a prediction result, the real-time position of each component is monitored, and possible transportation delay is predicted in combination with a time sequence model; the coordination agent dynamically adjusts the transportation plan based on a shortest path optimization algorithm; a customs agent processes cross-border customs clearance affairs in advance, and registers customs clearance states under the support of a block chain smart contract, so that customs clearance automatic check and an exception triggering mechanism are realized, and the stability and controllability of cross-border transportation are improved.

An apparatus for carbon emission optimization using machine-learning, apparatus including a processor and a memory containing instructions configuring the processor to receive an integrated logistics data collection, determine a projected carbon emission as a function of the integrated logistics data collection, generate a transportation plan as a function of the integrated logistics data collection and the projected carbon emission, continuously receive a current logistics datum from an external source, and iteratively modify the transportation plan based on the current logistics datum.

The invention relates to a cargo transportation path planning and tracking method. The method comprises the following steps: acquiring initial target intention data, transportation environment state data and an original transportation path evolution model of a cargo transportation task; according to the initial target intention data and the transportation environment state data, constructing an initial transportation planning path of the cargo transportation task; performing parameter initialization on the original transportation path evolution model according to the initial transportation planning path to obtain a current transportation path evolution model; performing target migration processing on the initial target intention data according to real-time environment sensing data of the cargo transportation task to obtain target migration intention data; inputting the target migration intention data into the current transportation path evolution model to obtain an updated transportation planning path; and tracking the execution condition of the cargo transportation task according to the updated transportation planning path. The method can effectively cope with complex and changeable transportation environments.

The invention relates to the technical field of internet-of-things encryption, in particular to a logistics in-transit data secure transmission system, which comprises a trajectory hash presetting module used for extracting longitude and latitude dotting data according to a logistics transportation plan, arranging the longitude and latitude dotting data according to a time sequence to generate a predetermined trajectory coordinate sequence, and transmitting the predetermined trajectory coordinate sequence to a database; and performing iterative hash operation on the predetermined track coordinate sequence in combination with a time slice index, and storing a check value output by the operation as a reference hash check chain. According to the method, the real-time reliability of each network node can be quantified, so that the evaluation result focuses on the recent behavior performance, finally, the low-trust node is moved out of the routing topology according to the dynamic score, and a safe and purified transmission link is actively constructed; according to the whole set of processing flow, security reinforcement is carried out on a path from a key generation source to data transmission, so that the confidentiality of data content is ensured, and the availability and integrity of data transmission are ensured by dynamically cleaning network infrastructures.

There is provided a relay transportation planning apparatus and method capable of devising a relay transportation plan(s) which enhances package transportation efficiency. A transportation plan is created by forming one or a plurality of transportation groups by gathering packages which have an at least partly overlapping transportation route and share a common time slot for transportation via the transportation route, based on package information, vehicle information, and driver information and allocating a transportation vehicle and a driver to each of the created transportation groups, wherein the transportation planning apparatus is designed to allocate a plurality of transportation vehicles which perform platooning or a transportation vehicle for towing a plurality of towed vehicles to the transportation group(s) when necessary.

The invention discloses a dispatching method and device for mine auxiliary transportation, equipment and a storage medium, and relates to the technical field of mines, and the method comprises the steps: obtaining the transportation demand information of mine auxiliary transportation, carrying out the clustering of the transportation demand information according to the type number of transportation carriers, obtaining a target transportation demand cluster, and carrying out the clustering of the transportation demand information; and inputting the target transportation demand cluster and the corresponding transportation carrier into the multi-type vehicle collaborative scheduling model to obtain a target transportation path and a target transportation time plan. And embedding the multi-type vehicle collaborative scheduling model into the initial digital twin model containing the mine auxiliary transportation virtual environment to obtain a target digital twin model. The target transportation path and the target transportation time plan are input into the target digital twin model, the transportation process is deduced, whether the transportation conflict exists or not is detected, and the transportation scheme is output under the condition that the transportation conflict does not exist, so that the efficiency and safety of mine transportation are remarkably improved, and the intelligent level of mine transportation is improved.

The invention relates to the technical field of supply and demand data matching, and discloses a supply and demand data dynamic optimization system and method based on a full life cycle, and the system comprises a decision module, a data analysis module, a supply module and a storage and transportation module. Analyzing the supply portal information and the appeal portal information in real time to obtain layout analysis data appeal information; evaluating and sorting the layout analysis data according to the appeal information to obtain a plurality of supply sorting tables; constructing an initial supply and demand plan according to the supply sorting table and the demand information, and inputting the initial supply and demand plan into a supply portal for rationality analysis to obtain dynamic adjustment data; the initial supply and demand plan is updated according to the dynamic adjustment data, the supply portal constructs a production list according to the target supply and demand plan, and the appeal portal generates storage data and a transportation plan according to the production list. According to the method, all data of the supply and demand parties are matched and optimized by constructing a full-period supply and demand management architecture, so that the supply and demand matching efficiency is improved.

The invention relates to the technical field of logistics data management and industrial cloud platforms, and discloses a logistics data management method and system based on a cloud platform. The method comprises the following steps: acquiring multi-source data and preprocessing the multi-source data to obtain a cleaned data set; processing the data by adopting a fuzzy logic algorithm to obtain an uncertainty quantitative index; when the index exceeds a threshold value, integrating the road condition and demand data based on a Bayesian network, and generating a prediction deviation correction value; a transportation plan is updated in real time, and an optimized route is obtained; a dynamic visualization report is generated after the decision accuracy is further verified; and finally, an adjustment instruction is output through closed-loop control. The method is especially suitable for transportation optimization of cold-chain logistics in complex scenes such as haze, and can effectively improve the accuracy and real-time performance of a transportation decision and the cargo fresh-keeping quality.

The application provides a multi-objective robust optimization method, system, storage medium and electronic equipment for production task planning of a multi-agent collaborative platform, and relates to the technical field of production task planning of a multi-agent collaborative platform. First, according to the production task planning resources of the multi-agent collaborative platform and a single-batch overseas order, a production task planning model with a manufacturing enterprise agent as the core is constructed under the premise of determining the sea transportation time. Then, an infinity norm ball uncertain set is designed for the sea transportation time of a large ship, a robust quadratic multi-objective model for cross-regional multi-agent production task planning is constructed, and the total delivery time deviation and total delivery cost multi-objective of the single-batch overseas order are optimized. The model considers the sea transportation plan prepared in advance by a shipping company agent and the long and uncertain sea transportation time. In addition, the model is converted into an equivalent model, a two-stage hybrid heuristic algorithm is designed for solving, and a reasonable and feasible production task planning suggestion is given for the single-batch overseas order.

The invention discloses a logistics intelligent vehicle distribution method with a real-time decision-making capability, and relates to the technical field of logistics transportation, and the method comprises the steps: receiving and analyzing transportation plan data, automatically merging transportation plans meeting merging conditions, and extracting the key information of the merged transportation plans; collecting driver data; jointly forming a project-level real-time matching rule R4 based on the dynamic matching rule R1, the static matching rule R2 and the enterprise customization rule R3; inputting the transportation plan data and the driver data into a matching model, performing multiple rounds of screening and priority ranking according to the project-level real-time matching rule R4, and outputting an optimal vehicle and cargo matching result; and a transportation task is automatically generated according to the vehicle and cargo matching result, and monitoring and early warning are carried out on abnormal conditions based on real-time data in the transportation process. Precise matching of goods and vehicles is achieved, and the automation level, matching accuracy and exception handling timeliness of logistics transportation scheduling are improved.

The invention discloses an emergency rescue intelligent scheduling system and method based on the Internet of Things, and relates to the technical field of rescue scheduling analysis, and the method comprises the steps: scanning terrain point cloud through a three-dimensional laser radar carried by a scout car, and obtaining an aerial image, road condition sensor data and tent hospital coordinates through an unmanned aerial vehicle to build a space-time aligned initial disaster situation map; generating a multi-modal fusion data set with a timestamp; analyzing feature vectors based on the multi-modal fusion data set; analyzing a risk entropy based on the feature vector in combination with the confidence weight of each device, and analyzing the blocking probability of each grid unit based on the risk entropy; splitting a transportation planning path and an actual transportation path of the material supply truck, analyzing the similarity degree between a transportation planning path section and an actual transportation path section, and marking road sections according to the similarity degree; and updating the attribute data of the contained grid units based on each road segment mark. The accuracy of subsequent transportation path planning is improved, and the overall transportation efficiency is improved.

The invention relates to the technical field of intelligent production control, in particular to a port cargo transportation method based on transportation route planning, and the method comprises the steps: obtaining a cargo transportation demand of a port; carrying out preliminary planning of a transportation route based on a port and a cargo transportation destination; loading and unloading characteristics of each port are further considered, and a transport network topological graph is constructed; carrying out optimal configuration through edge computing nodes; the transportation route is dynamically adjusted in combination with real-time weather and ocean conditions, the technical problems that fine optimization cannot be carried out in port cargo transportation planning only through static data analysis, the phenomenon of resource shortage or idling often occurs, and the overall operation efficiency is affected are solved, the purposes of balancing carbon emission minimization and resource utilization rate maximization are achieved, and the economic benefit is improved. The technical effects that berth allocation and operation time windows are optimized, efficient operation of berths and loading and unloading equipment is ensured, waiting time and idle resources are reduced, and the resource utilization efficiency is improved are achieved.

The invention relates to the technical field of flow field data processing, solves the technical problem that interpolation precision and reliability are reduced due to the fact that data distribution characteristics cannot be accurately captured in a traditional interpolation method, and particularly relates to a flow field data interpolation method based on an optimal transportation theory. Comprising the following steps: dividing flow field data into N sub-regions and carrying out normalization processing; randomly extracting two batches of data as two discrete data distributions, and constructing discrete distributions according to probability quality; establishing a cost function for measuring data direction information and data value information included in the flow field data; establishing an optimal transportation plan for converting a flow field data interpolation problem into a discrete distribution handling problem, and solving an optimal transportation matrix to obtain an interpolation result; and carrying out reverse normalization on the interpolation result to an original numerical range and carrying out smoothing processing. According to the method, through optimization of the optimal transportation theory, the real physical behavior of the flow field can be better reflected, and the accuracy and credibility of the interpolation result in practical application are improved.

The invention discloses a distributed purchase and inventory cooperative control system based on multi-agent collaboration, and relates to the technical field of purchase and inventory cooperative processing, and the system comprises an intelligent purchase unit, an intelligent inventory unit, a logistics transportation unit and a cooperative processing unit. The data acquisition unit is used for acquiring data and extracting features after the data acquisition is completed, the intelligent inventory unit is used for monitoring the inventory state, the logistics transportation unit is used for establishing a purchase transportation scheme, an inventory transportation scheme and an emergency scheme, and the purchase transportation scheme is used for planning a transportation mode and a transportation path during purchase. According to the invention, in the cooperative processing process, the corresponding purchasing scheme, transportation scheme and inventory scheme can be formulated according to the types of different materials, the accuracy in the implementation process is ensured, the emergency scheme is established to deal with the problems generated by abnormal conditions, and the stability in the control implementation process is improved.

Embodiments of the present application disclose a transportation planning method and device based on road freight. The method comprises: performing multi-dimensional parameter matching of a business attribute of a target order and each selectable rate rule to obtain a rule set; when there are at least two mutually conflicting candidate rate rules in the rule set, determining the priority of the mutually conflicting candidate rate rules according to a judgment factor to obtain an optimal rate rule with the highest priority; determining the freight amount of the target order, a target vehicle executing the target order, a target driver, and transportation information based on the optimal rate rule; writing the freight amount into the target order or a settlement document, and sending the transportation information to a target device; during the freight process, if a preset dynamic recalculation trigger condition is met, recalculating the freight amount of the remaining transportation mileage to obtain an incremental fee; taking the achievement of the freight target of the target order under the condition of minimizing the incremental fee as an optimization target, and updating and optimizing the transportation planning.

Embodiments of the present application provide an LNG marine transportation path planning data processing method, device and electronic equipment. The method comprises: obtaining decision reference data associated with LNG marine transportation path planning, the decision reference data comprising at least annual transportation plan data, ship data, route data, and port state data; constructing a mixed integer programming model and defining a target function and a constraint function associated with LNG marine transportation path planning in the mixed integer programming model; and outputting LNG marine transportation path planning data based on the decision reference data through the mixed integer programming model. The technical solution of the embodiments of the present application can improve the accuracy of LNG marine transportation path planning data processing.

1. The name of the design product: graphical user interface of logistics service platform for electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: interface change state diagram 1. 5. The use of the graphical user interface: the present design is used for the interactive operation of the logistics service platform. 6. The human-computer interaction mode of the graphical user interface: the main view interface is the main interface of the software, and there are "single competition square", "transportation plan", "transportation execution", "transportation settlement", "contract management", "transportation center", "dispatching center", "user center", "statistical analysis", "service evaluation", "basic data" and other function keys. Click the "transportation plan" button in the menu bar at the top of the main view interface, and the interface changes to the interface shown in interface change state diagram 1; click the "chemical industry and gas" button in interface change state diagram 1, and the interface changes to the interface shown in interface change state diagram 2; click the downward arrow to the right of the "chemical industry system docking" button in interface change state diagram 2, and the interface changes to the interface shown in interface change state diagram 3.

The invention belongs to the field of transport scheduling, and particularly discloses a transport vehicle scheduling method and system based on a large language model and a storage medium, and the method comprises the steps: obtaining order information through the large language model based on an adjusted order text; acquiring required vehicle information based on the order information, and packaging the order information and the required vehicle information into a transportation application; a plurality of current transportation applications are sequenced, transportation files are formed according to vehicle conditions, and one transportation file corresponds to one vehicle; screening the transportation files to obtain the transportation files meeting the transportation conditions; combining the screened transportation files to obtain a plurality of transportation schemes, and screening the transportation schemes according to a preset target to obtain K transportation schemes; and according to the real-time text indication, determining a final transportation scheme from the K transportation schemes through a large language model. According to the invention, the transport plan of the transport vehicle can be adjusted in real time according to the change of order information in the supply chain, and the influence caused by plan adjustment is minimized.

A product transportation plan changing device (13) comprises: an input unit (13a) that receives operation information including an input value including an initial product transportation plan and a product shipment plan and each piece of facility information; a transportation destination changing unit (13e) that, when it is determined that there is a transportation destination that does not satisfy a constraint condition using each transportation destination product reception amount upper limit value and an entry work available time calculated on the basis of the input value and the operation information, changes the transportation destination that does not satisfy the constraint condition to another warehouse building for the transportation work selected according to a predetermined first priority order; and an allocation changing unit (13g) that changes the transportation vehicle having a high transportation work load to another transportation vehicle when an evaluation value indicating the variation in the work load between the transportation vehicles exceeds an allowable upper limit value.

The invention provides a train path and marshalling plan optimization method and system under the condition of considering whole-train priority, and belongs to the technical field of train operation management, and the method comprises the steps: constructing a marshalling station sub-network of commercial vehicle train transportation and a supernetwork based on the marshalling station sub-network through employing a traffic flow path of a historical transportation plan; according to actual operation requirements, marshalling constraints and optimization targets are determined, and a train path and marshalling plan comprehensive optimization model is established; and solving the train path and marshalling plan comprehensive optimization model by using a commercial solver to obtain an optimized train transportation route and a pairing relationship between goods and trains on each road section, and further obtaining a marshalling plan of the commercial vehicle. According to the method, train traffic flow path planning and train marshalling planning are combined, a train path and loading plan optimization model under the multi-starting-point and multi-terminal-point condition is established, the matching relation between the train traffic flow path and the train and the matching relation between the train and the train on each road section are decided, and overall optimization of railway commercial vehicle transportation is achieved.

The invention relates to the technical field of railway transportation management, aims to solve the problems of fragmentation of traditional railway transportation plan management data, low pre-judgment accuracy, cooperative imbalance and inaccurate feedback, and provides a railway transportation plan dynamic management method and system. The method comprises the following steps: multi-source heterogeneous data is subjected to edge preprocessing (sliding window filtering and LZ4 compression) and heterogeneous fusion and then is uploaded to an alliance chain evidence (delay is less than or equal to 3 seconds); bIM-GIS digital twinborn simulation is constructed, and an improved LSTM (the accuracy rate is greater than or equal to 92%) is used for pre-judging abnormity; evaluating the priority by combining double matrixes (demand urgency-resource constraint) with an analytic hierarchy process; performing game theory benefit weight and distributed particle swarm optimization scheduling; and performing hierarchical closed-loop feedback iteration. The system comprises a data fusion evidence storage module, a twinborn simulation pre-judgment module and a hybrid storage module. According to the invention, active pre-judgment and collaborative optimization of the transportation plan are realized, the data credibility, the pre-judgment precision and the management efficiency are improved, and interests of multiple parties are balanced.

The utility model discloses a meat duck slaughtering and transferring device, relates to the technical field of meat duck transferring, and comprises a bottom plate, the four corners of the upper surface of the bottom plate are fixedly connected with stand columns, the upper portions of the four stand columns are fixedly connected with a first hanging frame, and the left side and the right side of the first hanging frame are rotationally connected with second hanging frames through hinges; limiting grooves are formed in the middles of the front side and the rear side of the bottom face of the second hanging frame, rotating grooves are formed in the outer sides of the four stand columns, rotating rings are rotationally connected to the interiors of the rotating grooves through rotating shafts, supporting rods are fixedly connected to the surfaces of the outer sides of the rotating rings, and the tail ends of the supporting rods extend into the limiting grooves. The method has the advantages that the requirements of large-batch and small-batch meat duck transfer can be met at the same time, the transportation plan and scheduling are more flexible, the volume can be adjusted according to actual requirements, the transportation path and the loading plan can be optimized, and therefore the overall transportation efficiency is improved.

The invention relates to the field of primary and secondary allocation processes of product oil, in particular to a combined optimization allocation method for integrating primary and secondary logistics of product oil, which comprises the following steps of: constructing a basic combined allocation model of the primary and secondary logistics of the product oil; and according to the basic combination dispatching model, a corresponding combination optimization dispatching result is obtained based on an iterative greedy algorithm, a primary and secondary logistics combination optimization model is constructed on the basis of the whole-link dispatching process of the refined oil product from a refinery plant to a gas station, and a resource dispatching scheme is solved by using the improved iterative greedy algorithm. According to refinery resource supply data and gas station demand data, the method can simulate, measure, calculate and optimize a whole-link resource allocation scheme of product oil primary and secondary logistics before and after optimization, and quantitatively evaluate indexes such as whole-link logistics operation cost, a primary sub-transportation mode proportion and a secondary radiation range of an oil depot. And a foundation is laid for reasonably optimizing a primary and secondary resource allocation scheme from a global perspective in the future.

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.

The invention provides a transportation plan adjustment method and system for robot process automation, and the method comprises the steps: carrying out the cross-platform data capture of a gasoline information page through a robot process automation technology, and obtaining the data information of the information page; based on a natural language processing technology and an optical character recognition technology, basic transportation information and reference gasoline data of gasoline are read from a transportation contract, and a transportation risk allocation coefficient is set; estimating resource loss data generated in the transportation process by using a loss calculation engine based on the basic transportation information, the current accurate gasoline data, the transportation risk allocation coefficient and the reference gasoline data; and adjusting the transportation plan by using the resource loss data and the current accurate gasoline data. The latest current accurate gasoline data are integrated into the transportation plan, so that the transportation plan can reflect the latest transportation plan, and disputes and complaints of clients are avoided.

The present invention provides a dual-objective medical waste transportation method based on improved RSA-VNS, which relates to the technical field of path optimization. In the present invention, first, the medical waste transportation tasks and vehicle scheduling resources are obtained; secondly, based on the medical waste transportation tasks and vehicle scheduling resources, with the minimization of cost and storage risk as the optimization objectives, a dual-objective medical waste transportation model is constructed; finally, the improved RSA-VNS algorithm is used to solve the dual-objective medical waste transportation model, and the Pareto external archive is output to decode and obtain the optimal medical waste transportation plan. By comprehensively considering the start service time of medical institutions, the type, intensity and the possibility of spreading diseases of medical waste, the storage risk of medical waste is effectively quantified, and the model is more in line with the characteristics of the recycling and transportation problem of medical waste. In addition, the proposed hybrid algorithm effectively improves the algorithm convergence speed and solution diversity, and also strengthens the local convergence ability in the late stage of the algorithm.