1746 results about "Transportation cost" patented technology

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 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 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 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.

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 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.

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 fuselage-free unmanned aerial vehicle, an aviation container and a modular transportation system and method, and aims to solve the problems of high transportation cost of traditional aviation goods and low transportation efficiency of land goods. The aircraft is not provided with a warehouse and adopts a flying wing type layout or a conventional layout, wings in the flying wing type layout or the conventional layout are used for generating lift force and enter a straight wing flight mode after taking off, and the wings are provided with power systems, flight control systems and mounting structures used for being detachably connected with the streamline aerodynamic configuration aviation containers. Through the dynamic combination mode of the aircraft and the containers, the single aircraft can achieve the operation cycle of circularly transporting at least three containers. Through continuous container reloading operation, the aircraft can keep a continuous flight state without waiting for a loading and unloading process. And meanwhile, the container can be quickly circulated among different aircrafts through the modular design. According to the transportation mode, optimal configuration of transportation resources is achieved through efficient cooperation of the aircraft and the container.

The invention provides a multi-center hybrid fleet joint scheduling method based on an improved genetic variable neighborhood algorithm, and the method comprises the steps: building a joint scheduling model with the minimization of vehicle transportation cost, charging cost and overtime penalty cost as a target, and building constraint conditions; a genetic algorithm is adopted for optimization, and a joint scheduling scheme with the lowest total cost under the constraint condition is obtained; performing variable neighborhood local search on each generation of optimal individuals after genetic manipulation; executing a dynamic disturbance operation; and judging whether the maximum number of iterations is reached or not, if so, ending the process, and obtaining a multi-center hybrid fleet joint scheduling scheme, otherwise, repeating the previous steps. According to the invention, a joint scheduling mechanism is introduced to realize transportation resource sharing, and the overall resource configuration is optimized; a joint scheduling model is constructed based on a hybrid motorcade, an electric vehicle charging strategy is optimally designed, an improved genetic algorithm and a variable neighborhood algorithm are used for optimization solution, and customer service satisfaction experience can be 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 provides a dynamic optimization and visual decision-making system for port and navigation multimodal transport knowledge graph collaboration, and solves the problems of high transport mode conversion cost, difficult information sharing and the like. Aiming at the defects that a traditional static data warehouse (such as Hadoop) is insufficient in real-time performance, a general data fusion framework (such as Apache NiFi) is poor in field adaptability and the like, the system innovatively constructs a multi-source heterogeneous database, integrates port production, economic association, infrastructure and freight data, and realizes accurate path planning and personalized logistics scheme recommendation through an intelligent algorithm. The system adopts a React + ECharts + ShadcnUI technology stack to realize knowledge graph visualization, practice shows that the operation efficiency can be remarkably improved, the transportation cost is reduced, and technical support is provided for sustainable development of ports.

The invention discloses an electric power material efficient dispatching and logistics optimization method for an emergency scene, and belongs to the field of power grid material dispatching and transportation. According to the material dispatching requirements of the power system under different disaster levels, a hierarchical response mechanism is provided, and the hierarchical response mechanism comprises a single-bin quick response mode, a multi-bin collaborative supplement mode and a whole-network centralized support mode. A mathematical optimization model including supply, transfer and demand nodes and transportation paths is established, and improved optimization algorithms such as Sine mapping population initialization, differential variation disturbance and elitist retention, dynamic reverse learning and the like are introduced to improve the solving efficiency and the diversity of solutions. Under the assumption that node positions, material requirements, vehicle parameters and the like are known, the model realizes full-process optimization of supply distribution, transportation paths and resource scheduling. The method can effectively improve the emergency material dispatching efficiency, reduces the transportation cost and the material shortage risk, and has a good practical application value.

The invention discloses a port horizontal transportation tool dynamic intensive scheduling decision method, and relates to the technical field of port logistics transportation management, and the method comprises the steps: firstly collecting port transportation related data in real time, then determining the weight based on the port transportation related data, calculating the priority coefficient of each transportation task, sorting the coefficients from large to small to form a task sequence, and carrying out the scheduling of the task sequence; according to the vehicle state data and the task sequence, constructing a multi-objective optimization function which aims at minimizing the total task completion time, minimizing the total transportation cost and maximizing the vehicle average load rate, and solving and generating an optimal scheduling scheme by adopting an improved genetic algorithm; the task priority is determined, so that emergency and important tasks can be preferentially processed, and the task execution reasonability is improved; a multi-objective optimization function can overall plan efficiency, cost and resource utilization, the problem that traditional scheduling only focuses on a single objective is solved, and the port green and efficient development requirements are met.

The invention relates to the technical field of waybill price trial calculation, and discloses a waybill self-adaptive trial calculation method and system based on a dynamic transportation price rule engine, and the method comprises the steps: obtaining the transportation demand data and idle vehicle data of a user; calculating the theoretical unit freight of each idle vehicle based on the dynamic transportation price rule, the transportation demand data and the idle vehicle data; screening alternative vehicles, and constructing an alternative vehicle set; outputting the transport vehicle combinations and the theoretical transport cost of each transport vehicle combination through iterative optimization; correcting the theoretical transportation cost based on historical waybill data, and generating probability distribution of order receiving prices; generating a recommended price interval based on the probability distribution of the order receiving prices; and based on the order price selected by the user, performing feedback optimization on the generation of the recommended price interval. According to the invention, through intelligent matching of the transportation resources, accurate waybill price reference can be provided for the user.

The invention provides a lifting formwork vehicle which comprises a base, a frame body and an integrated module, the frame body is arranged on the base, and the integrated module is arranged on the frame body; the base is used for realizing the walking of the lifting formwork vehicle; the frame body comprises a telescopic vertical rod and a lifting system and is used for achieving lifting of the integrated module. The integrated module is composed of a keel frame and a template and installed at the top end of the frame body. The module size of the frame body can be adjusted by the universal telescopic frame of the mold frame vehicle, and one-to-more functions are achieved. The vehicle body can be folded and combined, the occupied area is reduced, and transportation cost is reduced. The vehicle body is simple to assemble and the integrated module is fast to install. The base and the frame body are easy and convenient to disassemble and assemble, the procedure that workers climb up and down is reduced, and the labor intensity is lowered.

The invention relates to the field of collaborative management scheduling, in particular to a digital supply chain collaborative scheduling method and system based on digital twinning, and the method comprises the steps: calculating the estimated stock of any production area; calculating an influence coefficient of any production area; obtaining a plurality of optional transportation paths of any production area, calculating the transportation risk of any production area in any optional transportation path based on the influence coefficient and the transportation loss rate, and obtaining the optimal transportation path of any production area; and obtaining an estimated supply quantity of any production area according to the estimated stock quantity, calculating a first product of the estimated supply quantity and the normalized transportation risk, taking an accumulated value of the first products of all the production areas as a transportation cost function, responding to a maximum value of the transportation cost function, obtaining an actual supply quantity of any production area, and completing collaborative scheduling. According to the technical scheme of the invention, the efficiency and precision of cooperative scheduling can be improved.

The invention discloses a dynamic scheduling method for a concrete transportation tank truck, and relates to the technical field of intelligent scheduling. According to the method, the position and state information of the concrete transportation tank truck is acquired in real time, the demand data of each construction site is combined, the clustering algorithm and the priority algorithm are utilized to generate the efficient demand list and the scheduling plan, and the scheduling efficiency problem under the condition that multiple construction sites are required at the same time is solved; the optimal driving path is determined through a Dijkstra algorithm and real-time traffic data, congestion is effectively avoided, fuel consumption and vehicle loss are reduced, and therefore the transportation cost is reduced; besides, a multi-objective optimization model and a genetic algorithm are adopted, fuel consumption, vehicle loss and an unloaded driving rate are comprehensively considered, a task allocation scheme is dynamically adjusted, the flexibility and robustness of the scheduling method are improved, the timeliness and reliability of concrete supply are ensured under variable traffic and demand conditions, and the scheduling efficiency is improved. And finally, optimization of the concrete transportation process is realized.

The utility model discloses a detachable cabinet-entering lathe bed and laser cutting equipment, and relates to the technical field of laser cutting equipment, the detachable cabinet-entering lathe bed comprises a middle frame, a left lathe bed and a right lathe bed; the left side and the right side of the middle frame are detachably connected with the left bed body and the right bed body through locking assemblies correspondingly. The split type design is adopted, compared with a traditional integrated lathe bed, the split type lathe bed is high in flexibility and can be split into a container, the middle frame can serve as an equipment packaging frame, other parts of equipment can be placed on the middle frame, and therefore the equipment packaging cost is saved, and meanwhile the transportation cost of the equipment is reduced. In addition, foot cups are arranged at the bottoms of the middle frame, the left bed body and the right bed body, so that high rigidity and supporting force are guaranteed. In the installation process, the middle frame can directly sit on the ground, then the middle frame is fixed to the left lathe bed and the right lathe bed through the locking assemblies, tools such as cranes and forklifts are not needed, and installation is convenient and time-saving.

The disclosure relates to the technical field of chair bases and particularly relates to a detachable chair base. The detachable chair base includes a chair underframe. A first supporting mechanism and a second supporting mechanism are connected to a surface of the chair underframe and a connecting mechanism is mounted above the first supporting mechanism and the second supporting mechanism through a mounting seat. The mounting seat includes a lower connecting plate. According to the disclosure, a first support leg and a second support leg are clamped with each other, so that the first support leg and the second support leg are connected and fixed to the chair underframe through a first screw and a second screw. The chair underframe is fixed and mounted through a plurality of groups of screws, so that the transportation of the chair underframe in parts is facilitated, and the transportation cost is lowered.

The invention discloses a data processing method. The method comprises the following steps: constructing a linear programming model; a decision variable of the linear programming model represents the number of products transported from a production site to a sales site, the constraint conditions at least comprise a product production capacity constraint for at least one production site and a product demand constraint for at least one sales site, and the target is at least one of the minimum product production cost and the minimum product transportation cost; determining at least two groups of initial solutions corresponding to the linear programming model; solving the linear programming model in parallel based on the at least two groups of initial solutions by using an interior point method so as to iteratively update the at least two groups of initial solutions; for at least one solving process corresponding to each group of initial solutions, the updated solution of the initial solutions is determined based on solving information of at least one group of initial solutions except the initial solutions; the solving information at least comprises value boundary updating information of the decision variable; and taking the updated solution as a target solution of the linear programming model in response to the condition that the updated solution corresponding to the at least one initial solution meets the convergence condition.

The utility model relates to the technical field of forage grass processing equipment, in particular to a chassis assembly of a collecting and bundling machine. Comprising a chassis frame, a lower bundling box, a hydraulic oil tank, a knotter connecting frame and a traction head, the chassis frame is horizontally arranged, the lower bundling box is of a rectangular frame box body structure, the lower bundling box is vertically arranged, the lower bundling box is vertically and fixedly connected to the upper portion of the rear end of the chassis frame, and the knotter connecting frame is fixedly connected to the lower bundling box; the hydraulic oil tank is fixedly connected to the front portion of the chassis frame, and the traction head is fixedly connected to the front end of the chassis frame and located in front of the hydraulic oil tank. The structure is compact, the length and the weight are moderate, the transportation cost and the manufacturing cost are reduced, the operation difficulty is reduced, and the operation efficiency is improved.

The invention discloses a logistics vehicle scheduling method and system, electronic equipment and a storage medium, and relates to the technical field of intelligent logistics, and the method comprises the steps: in a cloud center layer, an initial vehicle scheduling scheme is generated based on a dynamic vehicle scheduling model, and the dynamic vehicle scheduling model aims at minimizing the transportation cost; and the edge node layer receives the real-time traffic data and the order information, and dynamically adjusts the initial vehicle scheduling scheme to generate a dynamic scheduling scheme. And the vehicle-mounted terminal layer receives the dynamic scheduling scheme and performs path optimization based on the sensor data to obtain the execution state of the vehicle-mounted terminal. The execution state of the vehicle-mounted terminal is fed back to the edge node layer and the cloud center layer to update the dynamic vehicle scheduling model, a target vehicle scheduling scheme is determined based on the updated dynamic vehicle scheduling model, and the target vehicle scheduling scheme is used for scheduling multiple logistics vehicles. Through cloud side-end cooperative processing, the decision-making quality of logistics vehicle scheduling and the system response speed are improved.

The present disclosure relates to and discloses a swivel sofa chair convenient to transport, and relates to the technical field of furniture equipment. The swivel sofa chair includes: two armrest supporting portions, a backrest portion, a front baffle portion, a connecting frame, a base, and a seat cushion. The backrest portion is spliced with rear ends of the two armrest supporting portions, the front baffle portion is spliced with front ends of the two armrest supporting portions, and therefore an accommodating cavity with openings in a top and a bottom is formed. In the present disclosure, the two armrest supporting portions, the backrest portion, the front baffle portion, the connecting frame, the base, and the seat cushion can be respectively packaged, thereby greatly reducing packaging volumes needed during transportation, facilitating the transportation of the sofa chair, and reducing transportation costs of the sofa chair.

The utility model discloses a modularized deep-sea aquaculture net cage and an aquaculture system based on modularized assembly. The modularized deep-sea aquaculture net cage comprises pile legs, a lifting installation unit, a modularized net cage body and a gear and rack lifting unit. The outer side of the pile leg extends in the axial direction to form a rack, the lifting installation unit is provided with an inner ring part and an outer ring part, the lifting installation unit is movably arranged on the pile leg in a sleeving mode through the inner ring part, the modularized net cage body is constructed by a plurality of modularized net cage face modules, and all the net cage face modules are detachably installed on the outer ring part; the gear and rack lifting unit is installed on the lifting installation unit, a climbing gear is arranged at the power output end of the gear and rack lifting unit, and the climbing gear is in meshing transmission with a rack on a pile leg. The assembly parts of the whole aquaculture net cage are high in generalization degree, rapid installation is met, the assembly parts are high in transportable degree, the transportation cost is low, and expansibility is high.

The embodiment of the invention provides an intelligent decision-making method and device for cross-border logistics, electronic equipment and a storage medium, and is applied to the technical field of logistics decision-making. The intelligent decision-making method for cross-border logistics comprises the steps of collecting heterogeneous logistics data according to user demand information, performing language entity alignment processing on the heterogeneous logistics data to obtain standardized shipping data, performing transportation cost evaluation according to the standardized shipping data to generate comprehensive cost data, performing path search according to the comprehensive cost data through a heuristic algorithm to obtain an initial feasible path set, and performing multi-target optimization screening processing on the initial feasible path set to generate an initial logistics planning scheme set; and carrying out risk simulation and TOPSIS preference sorting on the initial logistics planning scheme set to obtain an optimal logistics planning scheme and a corresponding reported value. According to the invention, through cost evaluation, constraint path search, multi-target optimization and risk quantification, a more accurate transportation scheme is provided for the user, and the cross-border logistics operation efficiency is improved.

The invention discloses an autonomous moving traffic cone robot and a control method, and belongs to the technical field of traffic cone robots. A traffic cone robot capable of moving autonomously comprises a base, an inflatable traffic cone cover is installed on the base, an inflation cavity is formed between the traffic cone cover and the base, the outer wall of the traffic cone cover is coated with reflective paint, a guide shaft and an inflation assembly are arranged on the base, and the guide shaft is used for guiding the expansion direction of the traffic cone cover. The inflating assembly is used for inflating and deflating the inflating cavity; through the design of the inflatable traffic cone cover, the traffic cone cover can be contracted after being deflated, the equipment size is greatly reduced, the single-time transportation number is increased, and the transportation cost is reduced; by means of the synergistic effect of the guide shaft and the inflation assembly, the expansion direction of the traffic cone cover can be accurately controlled, and day-and-night efficient warning is achieved in cooperation with outer wall reflective paint and built-in LED lamp beads; the buffering air bag on the outer wall of the base is communicated with the inflation cavity and can rapidly expand to form protection when being impacted, and the equipment damage risk is reduced.

The invention discloses an intelligent boxing method and system based on space optimization in an automatic loading and unloading scene, and relates to the technical field of logistics automation, and the method comprises the steps: obtaining the basic information of a to-be-loaded box body, measuring the space size of a loading container, and initializing the constraint condition of boxing; calculating an initial boxing plan based on a three-dimensional space optimization algorithm, and establishing a spatial index mechanism; and guiding the loading equipment to place the current box body, detecting the actual placement position of the box body, updating the position information of the loaded box body, recalculating the boxing plan of the remaining box bodies, and repeating the steps until the loading of all the box bodies is completed. The method is specially designed for an automatic loading and unloading scene, can be seamlessly integrated into intelligent equipment such as a loading and unloading robot, and provides key algorithm support for logistics automation; the logistics transportation cost is effectively reduced by improving the loading efficiency and the space utilization rate; through a real-time detection and dynamic adjustment mechanism, the system can automatically deal with abnormal conditions in the loading process.