2236 results about "Transportation cost" patented technology

The invention provides a procurement supply chain collaborative intelligent management method and a procurement supply chain collaborative intelligent management system. Belongs to the technical field of supply chain management. Constructing a purchase demand prediction model; dynamically adjusting the purchasing strategy according to the prediction result; the record and the evaluation result are stored on the block chain; the system automatically sends order information to a supplier; the supplier confirms the order through the block chain platform and updates the production progress and the logistics information; the system adjusts an inventory strategy in real time; the logistics state is monitored in real time; the system analyzes data of each link of the supply chain in real time and identifies potential risks. Through dynamic path planning and real-time transportation optimization, the logistics path can be adjusted in real time according to traffic conditions, environmental factors and emergencies, the transportation time is shortened, the transportation cost is reduced, and therefore the overall efficiency of a supply chain is remarkably improved.

Disclosed in the present application are a container, an energy storage apparatus, an energy storage system and a charging network. The energy storage apparatus comprises containers. There are m containers, where m≥2, and the m containers are arranged in the direction of height of the containers. The size of each container in the direction of length thereof is consistent with the size of a standard container in the direction of length thereof, the size of each container in the direction of width thereof is consistent with the size of a standard container in the direction of width thereof, the size of each container in the direction of height thereof is smaller than the size of a standard container in the direction of height thereof, and the sum of the sizes of m1 adjacent containers among the m containers in the direction of height thereof is equal to the sum of the sizes of n standard containers in the direction of height thereof. The size of m1 containers in the direction of height thereof is equal to the size of n standard containers in the direction of height thereof, such that the space occupied by m1 stacked containers is the same as the space occupied by n standard containers, thereby improving the space utilization rate of container placement, and reducing the container transportation cost, thus reducing the use cost of energy storage apparatuses.

The present invention relates to the technical field of tableware, in particular to an easy-to-transport assembled table, including table legs disposed at each of four corners of a lower end surface of a table top and fixed by bolts, where the table top is assembled by at least one table plate. By adopting the present invention, the technical problem that an existing table is relatively large as a whole, inconvenient to carry, high in transportation cost and inconvenient to transport can be solved.

The present application discloses a container, an energy storage apparatus, an energy storage device, an energy storage system, and a charging network. The energy storage apparatus comprises containers, the number of containers is m, m≥2, and the m containers are arranged in the height direction of the containers. The dimensions of the containers in the length direction thereof are consistent with the dimensions of standard containers in the length direction, the dimensions of the containers in the width direction thereof are consistent with the dimensions of the standard containers in the width direction, the dimension of one container in the height direction is smaller than the dimension of one standard container in the height direction, and the sum of dimensions of adjacent m1 containers among the m containers in the height direction is equal to the sum of dimensions of n standard containers in the height direction. The dimensions of the m1 containers in the height direction are equal to the dimensions of the n standard containers in the height direction, such that the space occupied by the m1 containers when stacked is the same as the space occupied by the n standard containers, improving the utilization of container placement space, and reducing the transportation cost of the containers, thereby reducing the use costs of energy storage apparatuses.

The invention discloses an intelligent engineering vehicle scheduling method based on artificial intelligence, and the method comprises the steps: constructing a scheduling objective function which at least comprises the engineering vehicle transportation cost, the task completion time cost, the path congestion cost and the energy consumption cost; establishing a multi-dimensional task demand prediction model based on historical task data and real-time traffic data, and outputting a task distribution prediction value and a traffic state prediction value in a future time period; inputting the model into an engineering vehicle dynamic scheduling model established based on a deep reinforcement learning algorithm for iterative optimization; and generating a real-time scheduling instruction based on the optimized dynamic scheduling model, dynamically allocating task paths and resources of the engineering vehicle, and monitoring an execution state in real time to adjust a scheduling strategy. According to the method, efficient, economical and environment-friendly intelligent scheduling of the engineering vehicle is realized through construction of a scheduling objective function, multi-dimensional demand prediction, deep reinforcement learning dynamic optimization and real-time scheduling and monitoring.

The invention relates to an artificial intelligence-based cargo transportation path planning method and system for automatic warehouse logistics. The method comprises the steps of performing weighted scoring calculation based on customer historical transaction data and cargo attributes, and generating service label data for distinguishing a high-value hierarchy and a common hierarchy; a differentiation algorithm strategy is called according to the service label, an exclusive transportation path is distributed to the high-value goods, obstacle avoidance is optimized in real time, and adjacent orders are matched for common goods to be merged and distributed; in combination with real-time road conditions and storage scheduling data, through path weight dynamic calculation and genetic algorithm iterative optimization, generating a global transportation scheme considering both time efficiency and cost; customer preference parameters are updated in a closed loop mode based on execution feedback data, and system self-adaptive learning is achieved. According to the method, the problems that differentiated services, dynamic response to environment changes and low-efficiency resource utilization cannot be achieved in a traditional method are solved, the punctuality rate of high-value orders and common orders can be increased, and meanwhile the transportation cost of the common orders can be reduced.

The invention discloses a centralized unloading type power generation robot which comprises a mute box type diesel generator set and further comprises at least two sets of lifting supporting rod assemblies, and the lifting supporting rod assemblies are arranged on the two sides of the mute box type diesel generator set so as to lift the mute box type diesel generator set in the loading and unloading process. According to the centralized unloading type power generation robot, by arranging the lifting supporting rod assembly, the problem that a traditional generator set loading and unloading vehicle depends on hoisting equipment is solved, automatic lifting and unloading of the loading and unloading vehicle can be achieved in the environment without the hoisting equipment, the transportation efficiency is improved, the transportation cost is reduced, and it is ensured that the equipment can be rapidly transferred to the needed place to be put into use.

The present application discloses an optimization method and apparatus for a transportation strategy under a feeder logistics network, an electronic device and a storage medium. The method comprises: acquiring logistics information under a feeder logistics network, wherein the logistics information comprises information of each logistics node; inputting the logistics information into a digital twin model, by means of the digital twin model and by taking transportation rules of the feeder logistics network as a constraint condition and transportation cost minimization as an objective, performing route planning to generate a transportation strategy to be optimized, and simulating a transportation process of goods between the logistics nodes on the basis of the transportation strategy to be optimized, so as to obtain a simulation result; and on the basis of the simulation result, optimizing the transportation strategy to be optimized, so as to obtain an optimized transportation strategy. In the present application, on the basis of the computing power of the electronic device, the transportation strategy during logistics transportation can be quickly obtained; and by simulating the logistics transportation process, the reliability of the transportation strategy can be improved.

The invention provides a cross-border logistics order management method and a cross-border logistics order management system, and the method comprises the steps: carrying out the similarity comparison of package feature data and historical package feature data, and obtaining a similarity comparison result; if the preset similarity threshold is not exceeded, determining that the to-be-sent parcel is a target parcel; inputting the parcel feature data of the target parcel into a pre-trained digital twinborn model to obtain a digital twinborn body; carrying out analog simulation on the digital twinborn body based on the digital twinborn model, and generating a standard logistics track and a standard transportation cost; after the target parcel is delivered, an actual logistics track, actual transportation cost and current logistics environment information are acquired; and when the logistics deviation value exceeds a logistics abnormal threshold value or the cost deviation value exceeds a cost abnormal threshold value, generating alarm information. In the mode, automatic identification of repeated delivery, logistics abnormity and transportation cost abnormity can be realized, so that the intelligent and precise level of cross-border logistics order management is improved.

The invention relates to the technical field of intelligent logistics, in particular to a vehicle path planning method and system for tire enterprise distribution, a storage medium and a software product. The method comprises the following steps: firstly, performing entropy weight-fuzzy comprehensive evaluation based on order quantity, frequency and time window width to obtain customer priority, and constructing a target of'transportation cost + priority linkage soft time window punishment '; the method comprises the following steps of: selecting an ALNS damage / repair operator by taking Q-learning as a high layer under the condition of meeting load, volume and time window constraints, and matching greedy initialization, Metropolis acceptance and 2-opt fine tuning solution. The result shows that the total cost and the time window default are remarkably reduced under the same calculation budget, the punctuality rate of high-priority customers and the robustness of the solution are improved, and platform deployment is facilitated.

The invention discloses a double-row steel sheet pile cofferdam construction method, which comprises the following steps of: before construction, measuring the original riverbed elevation of a cofferdam piling area, organizing steel pipes to enter a site according to a cross-section diagram and a construction sequence of a cofferdam, timely removing and recording if stone blocks and the like at the river bottom are measured in the measurement process, and before construction, checking and maintaining all mechanical equipment, so that the construction efficiency is improved. After entering the field, the steel pipes are stacked according to specifications, varieties and classifications, before pile conveying, the models and the number of the steel pipes used during construction are determined, and the steel pipes are arranged strictly according to the designed section. Compared with a construction scheme of adopting a Larsen steel sheet pile cofferdam and a temporary construction platform, the construction cost, the rental cost, the earthwork transportation cost, the earthwork compaction cost, the earthwork filling excavation filling cost and the like of temporary facilities can be saved, building construction is carried out in a water area needing a large area, the construction period is long, and the construction cost is low. The method is more economical and reasonable when being used for constructing structures in water under the conditions of high water level and the like.

The invention relates to the field of logistics vehicle management, in particular to a centralized management method and system for intelligent vehicles. The invention discloses a centralized management system for smart vehicles. The centralized management system comprises a task receiving module, a portrait construction module, a vehicle screening module, a sign-in verification module and a queue management module. According to the method, the vehicle multi-dimensional portrait model is constructed, and the transportation cost, the transportation efficiency and the like are subjected to multi-dimensional matching calculation based on the multi-objective optimization algorithm, so that intelligent vehicle dispatching decision-making from experience driving to data driving is realized; according to the method, the historical operation data, the real-time state and the driver behavior characteristics of the vehicle are comprehensively considered, a global optimal vehicle dispatching scheme can be output, the vehicle dispatching accuracy and the resource utilization efficiency are remarkably improved, and the limitation that a traditional method only depends on a single factor for dispatching is overcome.

A handling truck comprises a mast assembly, a base, a moving assembly, and a connecting member. The base is fixedly disposed at the bottom end of the mast assembly, and the base is provided with a socket portion. The moving assembly includes a leg assembly and a connecting portion, wherein one end of the connecting portion is connected to the leg assembly, and the other end of the connecting portion is configured for socket engagement with the socket portion. The moving assembly is configured to drive the mast assembly to move on a plane. The connecting member is configured to pass through the socket portion and the connecting portion to achieve a detachable connection between the moving assembly and the base. The present application provides a handling truck capable of reducing packaging costs and transportation costs.

The invention relates to the technical field of warehouse management, and discloses a warehouse management system and method based on dynamic inventory prediction. According to the invention, market, sales, supply chain and warehouse internal data are collected in real time, a dynamic inventory prediction model is constructed in combination with a long short-term memory (LSTM) network, the future inventory demand can be accurately predicted, and the prediction precision is significantly improved; an inventory optimization strategy is generated based on a multi-objective optimization algorithm, so that the inventory holding cost, the stockout cost and the transportation cost are effectively reduced; and intelligent warehouse operation instruction generation and real-time monitoring are realized through the execution control module, and the response capability of an enterprise to market fluctuation and emergencies is enhanced. According to the system and the method, the warehouse management efficiency is improved, the operation risk is reduced, and an efficient and reliable solution is provided for modern logistics and supply chain management.

The invention discloses a dangerous goods transportation charging method based on risk assessment, and relates to the technical field of dangerous goods transportation charging, and the method comprises the following steps: collecting the data of traffic flow, accident occurrence frequency, environmental factors and the like of each road segment in a dangerous goods transportation network, and calculating a dangerous goods transportation charging result based on a population coverage risk model and an accident expected value calculation method; and evaluating the potential risk level of each road section. Through multi-dimensional data fusion and an advanced algorithm, real-time assessment and path optimization of transportation network risks are realized. A population coverage risk model and an accident expected value calculation method are adopted, high-risk road sections are accurately recognized, transportation tasks are reasonably distributed, and safety is improved. Meanwhile, the genetic algorithm is utilized to optimize the transportation path, balance the cost and risk, reduce the transportation cost and guarantee the safety. Global path distribution is optimized through a simulated annealing algorithm, excessive load of high-risk road sections is avoided, task distribution is dynamically adjusted according to risk prediction, reasonable resource allocation is ensured, and transportation efficiency and safety are improved.

An umbrella comprises a column having a middle portion; an upper nest; a lower nest; a plurality of long rods; a plurality of short rods each; a crank handle assembly disposed on the middle portion of the column. The lower nest has a plurality of first long rod grooves on a periphery of the lower nest; the crank handle assembly comprises a housing and a crank handle, correspondingly, the housing has a plurality of second long rod grooves. The umbrella of the present invention is simple and reasonable in structure, greatly reduced in size and convenience to store and carry, and reduces the cost for packaging and transportation.

The invention relates to the technical field of logistics and supply chain management, and discloses a one-station inspection platform-based product management method, which comprises the following steps of S1, constructing an optimal transportation problem model, defining a resource circulation relationship between a supplier and an order, and calculating an optimal scheme allocated to the order by the supplier by taking the minimum transportation cost as a target; s2, based on a game theory model, strategy interaction among a plurality of suppliers is considered, a supplier resource allocation strategy is optimized through a game, and balance of resource scheduling is ensured; s3, a Markov decision process is adopted, and order circulation and resource scheduling strategies are adjusted through real-time feedback so as to adapt to dynamic changes of service requirements; and S4, carrying out multi-objective optimization. According to the invention, through a dynamic optimization and real-time data feedback mechanism based on the one-station inspection platform, efficient resource scheduling and order circulation are realized, the maximization of the resource utilization rate is ensured, the delivery timeliness is improved, and the cost and the service quality are optimized at the same time.

The unmanned material transportation system comprises an intelligent equipment cluster and a remote centralized dispatching system, and the intelligent equipment cluster is connected with the remote centralized dispatching system; the intelligent equipment cluster comprises horizontal transportation intelligent equipment used for same-layer transportation of materials, an intelligent construction elevator used for cross-layer transportation of the materials and a stacking robot used for sorting, taking and placing of the materials. The remote centralized control system comprises a front-end interface and a rear-end server, wherein the front-end interface is used for issuing tasks and monitoring material processes and equipment states, the rear-end server is used for task scheduling, task path planning, task conflict monitoring and management and transmitting collected information to the front-end interface for display, and the front-end interface is connected with the rear-end server. And the intelligent equipment cluster and the back-end server are in two-way communication through the real-time communication module. Material sorting and transporting can be automatically completed, manual operation on a construction site can be reduced, the equipment efficiency is improved, and the transporting cost is reduced.

The invention relates to an intelligent logistics scheduling and resource distribution system based on multi-source data fusion, and relates to the technical field of logistics management technologies, and the system comprises the steps: collecting vehicle operation state data, road condition data, logistics order dynamic data and warehouse inventory change data in real time based on a multi-source heterogeneous interaction platform; constructing a multi-modal traffic logistics time series data set; based on a maximum priority scheduling algorithm, giving priority weights to the logistics orders in combination with logistics order timeliness demands and cargo features; based on the logistics order priority weight, path optimization is carried out by using a space-time hierarchical planning algorithm, and an initial transportation path set is constructed; real-time monitoring of the transportation process is achieved based on the digital twinborn technology, the path condition is sensed dynamically, the optimal transportation path is obtained through continuous adjustment, and an intelligent logistics scheduling and resource allocation scheme based on multi-source data fusion is generated. The method has the advantages that the resource allocation efficiency is improved and the transportation cost is reduced by optimizing the priority path and continuously adjusting the transportation path.

The present invention relates to the technical field of tableware, in particular, to an easy-to-transport three-spliced table. The three-spliced table includes table legs arranged at four corners of a table top, where the table legs and the table top are reinforced by a plurality of groups of reinforcing members; the table top is formed by splicing a first table plate, a second table plate and a third table plate side by side; and the table top of the three-spliced table is divided into three parts when being opened, which are not different from a table with a complete table top after being assembled through screws. During transportation, the packaging volume is reduced, the transportation cost is saved, and the risk of packaging damage and product damage during transportation is reduced.

A disassemblable table is provided, which belongs to the technical field of furniture. The problem of reducing the transportation cost of the table while ensuring the structural stability of the table is solved. The disassemblable table includes a table board and a plurality of table legs, where the disassemblable table further includes a ringlike connecting frame, the connecting frame is located below the table board and disposed among the plurality of table legs, a side wall of each of the table legs is provided with a U-shaped connecting clip, the connecting clips are clamped with an outer side wall of the connecting frame and bolted and locked through fasteners, a bottom face of the table board is provided with a ringlike fixing frame, and an upper end of each of the table legs is joined with an outer wall of the fixing frame and bolted and locked through the fasteners.

The invention provides a rounded-corner container transportation path dynamic optimization scheduling method and system, and the method comprises the steps: quantifying three constraints of the size, the gravity center and the loading and unloading priority of a rounded-corner container, converting the three constraints into a matching formula, a path constraint threshold value and a weight rule, and constructing a weighted multi-objective optimization function in combination with the transportation cost, the time and the cargo damage risk; a genetic algorithm and ant colony algorithm mixed framework is built, a constraint adaptation layer is embedded to filter invalid solutions, and the iteration efficiency is improved; two types of algorithm operators are improved, and a constraint satisfaction degree, a loading and unloading priority and a dynamic parameter adjustment mechanism are fused; dividing multiple regions into sub-region optimization by adopting a divide-and-conquer strategy, and adapting to a large-scale dynamic scene through cross-region collaboration and local re-optimization; a full-dimension verification scheduling scheme in iteration is carried out, algorithm parameters are automatically adjusted based on constraint violation information, and iteration is terminated or constraint relaxation is started according to preset conditions; an improved algorithm is integrated to a dynamic scheduling system, real-time data are connected, parameters are optimized through a self-learning module, and a manual intervention interface is reserved.

The invention discloses a multi-access-considered vehicle-unmanned aerial vehicle distribution path optimization method, relates to the technical field of vehicle and unmanned aerial vehicle collaborative distribution optimization, and aims to solve a path planning problem caused by complex constraints and multi-target optimization in urban logistics distribution. According to the method, firstly, multiple constraint conditions of vehicle-unmanned aerial vehicle cooperative distribution are analyzed, energy consumption cost and carbon emission factors are fused into a target function, an integer programming model with the minimum time and transportation cost as double targets is constructed, and carbon emission cost is considered in the transportation cost; secondly, solving a vehicle path and an initial solution by adopting an ant colony algorithm; and finally, a large-field search algorithm is used to solve the problem of vehicle-machine cooperation path optimization. According to the method, the vehicle and unmanned aerial vehicle cooperative distribution logistics efficiency is effectively improved, the total cost is reduced, and powerful support is provided for development of green logistics.

The invention discloses a dynamic logistics network path optimization method based on a chained state routing algorithm, and belongs to the technical field of logistics network optimization, and the method comprises the steps: firstly, building a node state evaluation model through a distributed state collection mechanism based on a chained state routing protocol, and generating a dynamic elastic network topology structure; secondly, when logistics network nodes change, a logistics path is optimized in combination with a transportation cost prediction model, an emergency response punishment mechanism and a path adjustment weight coefficient; and finally, optimizing an affected path in a node abnormal state by using a local path updating mechanism. Compared with a traditional logistics model, the method has obvious advantages in the aspects of path calculation cost and response time when processing a path problem containing failure nodes, and can effectively optimize logistics path planning, reduce transportation cost and improve system robustness and resource allocation efficiency.

The invention provides an Apple cold-chain logistics path optimization system and method considering vibration loss, and the method comprises the following steps: collecting data required by cold-chain logistics distribution, including client point information, real-time road condition information, vehicle vibration acceleration and vehicle driving information; establishing an apple vibration loss calculation model in the transportation process according to the characteristics of the apples; according to the vehicle transportation cost, the goods damage cost, the refrigeration cost, the time window constraint violation cost and the carbon emission cost, an Apple cold-chain logistics distribution path optimization model with the minimum total cost as the target is established; solving the apple cold-chain logistics distribution path optimization model by using an improved ant colony algorithm; according to the detected CO2 concentration, temperature and vibration loss, the method is used for monitoring the apple quality condition in real time, establishing a feedback adjustment mechanism, and giving loss reduction measures according to the apple quality condition. The optimal distribution path is selected in combination with an algorithm, and cost reduction and benefit increase of apple cold-chain logistics transportation are achieved.

The invention discloses an auxiliary decision-making method and system for regional coal market purchase, and belongs to the technical field of coal market purchase decision-making, and the method comprises the steps: building model input parameters through collecting the data of a fire coal demand plan of a power plant, the maximum supply of a supplier, a coal quality index, a purchase price and a transportation cost; constructing a mixed integer linear programming model taking the minimization of the total purchase cost as a target function, and setting a demand satisfaction constraint, a supply capability constraint and a coal quality standard reaching constraint; solving the mixed integer linear programming model by adopting a two-stage approximation algorithm; and converting the obtained approximate optimal solution into a visual purchasing scheme chart and report, and supporting a user to dynamically adjust the purchasing scheme through an interactive interface to generate a final purchasing decision. According to the invention, on the basis of comprehensively considering the coal quality, the purchase cost, the transportation mode and the supplier capability, the coal purchase plan is optimized, the cost minimization is realized, and the overall quality of coal purchase is improved.

A quadrotor is proposed than can both fly and roll. The proposed robot employs passively reconfigurable structures to enable the rolling, tightly coupling the attitude of the robot to the rolling cage. The benefits are precise rolling and turning control as well as improved rolling efficiency. The passively reconfigurable structures are enabled by pre-stretched elastic springs to generate a nonlinear restoring torque. The robot leveraged the superior maneuverability in the rolling mode to take photos of the surroundings at different tilting and panning angles to construct a panoramic image. Besides, the results of the power measurements show a significant reduction in the cost of transport brought by at low speed, equating to a 15-fold extension in the operational range.

The invention discloses a manned transport vehicle scheduling method and device, and relates to the manned transport vehicle scheduling technology, and the method comprises the steps: obtaining the vehicle information and map data of a target mining area, and generating a global scheduling scheme through the vehicle information and map data, the global scheduling scheme comprises the step of carrying out vehicle scheduling according to the determined number of vehicles to be allocated at each loading point and the determined number of vehicles to be allocated at each heavy-load transportation path; according to the method, the manned transport vehicles in the target mining area are scheduled according to the global scheduling scheme, the mining area vehicles can be accurately scheduled, accurate and balanced scheduling of the manned transport vehicles is realized, the overall efficiency of mining area operation is improved, and the transportation cost is reduced.

The invention discloses an intelligent calculation method and system for concrete sales, and relates to the technical field of building and logistics management. By dynamically adjusting the production plan, accurately predicting the customer demand and optimizing the production capacity and the raw material ratio, the problem of excessive or insufficient production caused by large demand fluctuation in traditional production is solved, the inventory cost is reduced, the production efficiency is improved, the traffic condition is monitored in real time and the transportation route is dynamically optimized in the transportation link, and the transportation efficiency is improved. The transportation efficiency and the delivery punctuality are obviously improved, the transportation cost is reduced, and the concrete quality is ensured; in the production process, the raw material ratio and the concrete state are monitored in real time through a sensor and a machine learning algorithm, production parameters are dynamically adjusted, the quality fluctuation problem caused by inaccurate ratio or untimely monitoring in traditional production is solved, and the stability of product quality is ensured.

The invention discloses a multi-logistics-vehicle dispatching method based on an accessibility matching cross genetic algorithm, and the method comprises the steps: building a multi-logistics-vehicle dispatching model with access constraints based on a scene that a customer has preference demands for logistics vehicle services due to the difference of logistics categories in practical application; a preference relationship of clients to logistics vehicles is described by using an accessibility matrix, crossover operation and mutation operation based on accessibility matching are designed, and a dispatching scheme of multiple logistics vehicles is optimized by embedding a genetic algorithm. Through the above operation, customer preference demands can be comprehensively considered in the iteration process, the total path of the multiple logistics vehicles and the path balance of the logistics workshops are optimized at the same time, and a globally optimal multiple logistics vehicle dispatching scheme is quickly found. According to the method, the solving efficiency of the multi-logistics vehicle dispatching problem with the access constraint is greatly improved, the dispatching efficiency of the logistics vehicles is effectively improved, and the transportation cost is reduced.