18 results about "Transportation distance" patented technology

The invention belongs to the technical field of port scheduling, and particularly relates to a container yard AGV scheduling method and system, and the method comprises the steps: S1, collecting and processing the data of a field environment; s2, setting a target function F according to the transportation distance D, the waiting time T, the weather influence W and the storage space storage factor C; s3, using an ant colony algorithm to optimize the transportation distance D and the storage space storage factor C; optimizing the waiting time T and the weather influence W by using a neural network; and S4, selecting a scheme with the minimum comprehensive objective function F according to the transportation distance D and the storage space storage factor C provided by the ant colony algorithm and the waiting time T and the weather influence W predicted by the neural network. The method has the advantages that different key independent variables are optimized through the ant colony algorithm and the neural network respectively, and optimization of the efficiency and stability of the whole dispatching system is facilitated. According to the method and the system, a brand new algorithm is constructed for a port environment, and real-time and dynamic optimization can be realized on path and resource scheduling.

The invention discloses a supply and demand allocation and transportation path optimization method for ardealite for filling in a region, which comprises the following steps: acquiring a to-be-allocated region of ardealite for filling, and establishing an ardealite supply and demand network directed graph in the region; on the basis of the network directed graph, constructing a supply and demand allocation and transportation path optimization model of ardealite for filling in the region; the optimization model comprises minimum transportation cost and maximum transportation flow; and iteratively searching the augmented chain by adopting a Ford-Fulkerson algorithm, searching an optimal path meeting the maximum transportation flow and the minimum transportation cost, and obtaining supply and demand allocation and transportation path optimization results of the ardealite for filling in the region. According to the method, the supply amount, the demand amount, the transportation distance, the transportation cost and the environmental constraint conditions of the ardealite are comprehensively considered, and an optimal allocation scheme and an optimal transportation path are generated by constructing a transportation allocation optimization model of the ardealite for filling.

The invention discloses a multi-target path optimization system and method for hazardous chemical substance road transportation, and the system comprises an optimization housing, and the interior of the optimization housing is fixedly provided with a path optimization system. Optimizing the Bayesian network model by using a Pearson chi-square test method and a Granger causal test method, and constructing a transportation accident consequence risk model by comprehensively considering accident severity, accident handling time, an accident influence area, accident road section population density and accident road section environment characteristic indexes; secondly, on the basis of dangerous goods transportation risk analysis, analysis is carried out according to the transportation distance, the transportation cost and simultaneous design cases; and finally, considering the finite rationality characteristics of decision makers, carrying out investigation and empirical analysis on the path planning principles and preferences of the dangerous goods transportation enterprises, effectively solving the multi-target dangerous goods transportation path optimization problem, and providing reference for the transportation line selection decision of the dangerous goods enterprises.

The application discloses a kind of considering the earthwork intelligent deployment method of multiple material and multiple bid section cooperation, comprising: S1, obtaining engineering basic data;S2, according to trunk road network data and site barycenter data in construction site division information, generate full field transport distance matrix;S3, the excavation area is divided into different constraint control type;S4, to the filling section and excavation area that exist internal affiliation, execute section internal deployment;S5, based on full field transport distance matrix and the full field resource state after internal deployment, introduce multiple decision variables such as cross-section deployment variable, responsibility abandoned variable and associated material unloading point assignment variable, and construct mixed integer linear programming model;S6, solve mixed integer linear programming model, determine optimal earthwork deployment scheme;The application can not only realize the collaborative optimization of rigid instruction and full field deployment, but also can clearly define the management rights and responsibilities of each contractor, improve the operability of earthwork deployment scheme.

The invention discloses a high-speed workpiece carrying device for a large press interval of a press line. Comprising a mounting bracket, a lifting box body which is arranged on the mounting bracket and ascends and descends on the mounting bracket, and a feeding cross beam which is arranged at the lower end of the lifting box body and is in sliding connection with the lifting box body, the follow-up sliding plate is arranged at the lower end of the feeding cross beam and slides on the feeding cross beam, the adsorption device is arranged on the follow-up sliding plate and used for adsorbing workpieces, a follow-up sliding block is arranged between the lifting box body and the feeding cross beam, and the upper end of the follow-up sliding block is connected with the lifting box body in a sliding mode. The lower end of the follow-up sliding block is in sliding connection with the feeding cross beam, a gear is arranged in the middle of the follow-up sliding block, and racks meshed with the gear are arranged at the upper end of the feeding cross beam and the lower end of the lifting box body. And with the same transportation distance, the length of the cross beam is reduced, the weight is light, the processing and manufacturing cost is reduced, the width of the lifting box body is increased, the overall strength of the device is high, and the feeding precision is ensured.

A super-long multi-spiral tunnel slag shaft structure and excavation construction method relate to highway underground engineering construction technology, in particular, the specific layout of the spiral tunnel and its structural type and its excavation construction method. It has a tunnel main tunnel composed of several spiral tunnels. The key technology is to set up a slag shaft near the intersection of the upper and lower layers of the spiral tunnel. The upper part of the slag shaft is connected to the upper layer of the spiral tunnel through an upper flat tunnel, and the lower part of the slag shaft is connected to the lower layer of the spiral tunnel through a lower flat tunnel. The beneficial effect of the present invention is that by setting up a shaft structure, the present invention can effectively save the slag transportation cost generated by the slag discharge distance of the spiral tunnel. A single spiral tunnel can save about 1.5 kilometers of transportation distance, effectively improving the slag discharge efficiency during the construction period of the super-long multi-spiral tunnel.

The invention provides an assembly type lining segment scheduling method and system and a process progress management method. The scheduling method comprises the following steps: establishing a database containing lining segment information of a storage yard area and storage yard inventory information; calling a map API (Application Program Interface) based on the construction point coordinate and the demand type of the newly added demand, and screening out a candidate storage yard region set meeting the stock type and quantity constraint in the database; integrating a multi-path planning interface, and generating the minimum transportation distance and the shortest transportation time between the construction point and each candidate storage yard area; establishing a dynamic weight distribution model based on a dynamic priority rule, and generating a priority sequence of the candidate storage yard areas; and scheduling the lining segments based on the priority sequence. The problems that in the prior art, management of lining segments stacked in a storage yard is disordered, and lining segments of specific types are difficult to dispatch rapidly are solved.

The invention discloses a goods damage guarantee digital management method and a storage medium, and the method comprises the steps: receiving transportation task information which comprises a goods type and a transportation distance; weight distribution is carried out on the risk coefficient of the cargo type, the risk coefficient of the transportation distance and the historical cargo damage rate associated with the cargo type, a basic risk score is calculated in a weighted mode, and a guarantee insurance type is matched according to the basic risk score; within the matched guarantee insurance type quota range, calculating a recommended guarantee quota according to the risk score linear difference value; calculating a basic insurance premium according to the recommended insurance quota and the basic insurance premium rate; and adjusting the insurance premium according to the credit score and the member level of the driver, and generating and pushing a guarantee scheme based on the adjusted final insurance premium and the recommended guarantee quota. Weighted calculation is carried out through multiple factors such as the cargo type, the transportation distance and the historical cargo damage rate, the guarantee limit matched with the real risk is dynamically generated for the transportation task, and the accuracy of the guarantee service and the user experience are improved.

This invention discloses a multi-objective vehicle routing optimization method that considers both loading rate and transportation mileage. The method involves: acquiring order data of orders to be delivered and vehicle rated load and current location data; constructing an order load feature vector based on cargo weight and volume; clustering orders according to load differences to form multiple order clusters; assigning an initial priority label to each order cluster; sorting the order clusters according to the initial priority labels; merging the order clusters based on their spatial location information and loading rate constraints to generate an initial vehicle route; constructing a multi-objective collaborative optimization route evaluation model to optimize the initial vehicle route, generating a set of alternative route schemes; and selecting the route scheme with the highest comprehensive score as the final route scheme output. This invention can effectively reduce scheduling complexity, improve vehicle loading and delivery efficiency, and enhance the stability and practical feasibility of route decisions.

The application relates to a double-evaporator system and a control method. Through the architecture of double-evaporator partition arrangement, a first evaporator directly corresponds to a driving area and a lower bunk area of a lower part of a cab, and a second evaporator directly corresponds to an upper bunk area of an upper part of the cab, so that the cold quantity transportation distance is shortened from the root, and the loss in the long-distance transportation process of the cold quantity and the coverage blind area are eliminated. Meanwhile, through the architecture of double-compressor parallel arrangement, the refrigeration power supply demand under different operation conditions of the vehicle is adapted, stable output of the cold quantity under full working conditions of driving, idling and parking is realized, the temperature difference between upper and lower areas of the cab can be controlled to be within 2 DEG C, the refrigeration response speed of the upper bunk area is improved, the pain point of insufficient refrigeration of the upper bunk area is solved, and the rest and driving comfort demand of drivers and passengers under a long-distance trunk logistics scene is fully met.

The invention discloses a route planning method suitable for a vehicle distribution task with uncertain driving time based on an evolutionary multi-task framework, which is applied to a vehicle distribution task consisting of a single warehouse, a task node with distribution time limitation and an undifferentiated vehicle with capacity limitation. The method comprises the following steps: 1, establishing a vehicle distribution task model; 2, generating an original task population meeting the uncertain driving time constraint and an auxiliary task population not meeting the uncertain driving time constraint; 3, generating a next-generation original task population and a next-generation auxiliary task population by adopting a dynamic interaction strategy; 4, updating the current-generation elite archive to obtain a next-generation elite archive; and 5, if a termination condition is met, generating a current optimal path planning scheme, otherwise, returning to the step 3 for execution. According to the method, the evolutionary multi-task framework can be utilized, so that the route planning scheme of the uncertain time vehicle distribution task can ensure that the total transportation distance is short, and can ensure that the constraint of uncertain time can be met in various scenes.

To provide a logistical assistance device with which it is possible to visualize CO2 emission reduction effects in logistics transportation and assist in verifying decarbonization effects.SOLUTION: A logistical assistance device 2 comprises: a transportation information acquisition unit 211 that acquires present transportation information; a transportation information generation unit 212 that generates improved transportation information on the basis of the present transportation record information; a transportation distance calculation unit 213 that calculates a transportation distance for article transportation on the basis of the present transportation information, improved transportation information, and travel distances regarding transportation; an environment related information calculation unit 214 that calculates CO2 emissions in each of a plurality of transportation modes, on the basis of the present transportation information, improved transportation information, and transportation distances; and an information presentation unit 215 that generates output information including CO2 emissions in each of the plurality of transportation modes and a written report that indicates CO2 emission reduction effects, and presents the output information and the written report. The improved transportation information includes information in which article transportation means and collection-delivery means are customized for each customer.SELECTED DRAWING: Figure 2

The embodiment of the invention provides a multi-target multi-crown-block scheduling method based on dynamic priority conflict resolution, and belongs to the technical field of control, and the method specifically comprises the steps: 1, obtaining historical data; 2, calculating the correlation degree of each task according to historical data, dividing each task into different priorities according to the correlation degree, and designing corresponding delay penalty functions according to the different priorities; step 3, taking minimization of completion time, delay penalty and passive transportation distance as optimization objectives, and constructing a multi-objective multi-crown-block scheduling optimization model; 4, based on the dynamic priority of the time window constraint calculation task, forming a comprehensive evaluation method of conflict resolution, and establishing a simulation model according to the comprehensive evaluation method; and step 5, based on the simulation model, adopting an improved MOEA / D algorithm to solve the multi-target multi-crown-block scheduling optimization model, and generating an optimal scheduling track and a task allocation scheme of a plurality of crown blocks. Through the scheme disclosed by the invention, the scheduling efficiency and accuracy are improved.

The invention discloses an intelligent application and payment method and system for special fees in a transportation process, and the method comprises the steps: carrying out the automatic charging processing of a processing application of dispute fees according to the emptying fees and vehicle guarantee fees of a driver who proposes the processing application, according to the positioning data of the driver, and in combination with a business rule corresponding to the dispute fees; and on-line automatic processing is carried out on dispute fees according to an automatic charging result. According to the method, the problem of online processing of special expenses generated by behaviors such as emptying, escorting, cargo weight increase and transportation distance increase in the transportation process of a carrier is solved, and the shipping processing time is accelerated; therefore, the quantity of customer service for asking for help by shipping is reduced, and new technical enlightenment is provided for the development of an online freight platform.

The utility model relates to an auxiliary device for earth-rock blending, and belongs to the technical field of earth-rock engineering. Comprising a machine body, a mounting base fixed to the bottom of the machine body, a bottom plate fixed to the bottom of the mounting base, four moving wheels fixed to the front face and the back face of the bottom plate correspondingly, and an automatic deploying and cleaning mechanism installed in the machine body and used for automatically deploying and cleaning the machine body. The moving assembly is installed at the top of the machine body and used for achieving the moving effect, and the automatic blending and cleaning mechanism comprises a blending and cleaning assembly which is installed at the bottom of the machine body and used for achieving the automatic blending and cleaning effects. According to the auxiliary device for earthwork allocation, transported earthwork can be effectively weighed in real time, key data such as loading and unloading time and transportation distance of each time can be recorded, the interior of the compartment can be conveniently, automatically and effectively cleaned, and the practicability of the auxiliary device for earthwork allocation is improved.

The invention discloses a full-life-cycle management system and a full-life-cycle management method for multi-dimensional dynamic charging. The method comprises the steps that an RFID chip is embedded in a cargo, and identification information including the unique ID of the cargo, the category of the cargo and the purchase date is written in the RFID chip; scanning the RFID chip through a cargo binding terminal, and associating information of a customer to establish a cargo electronic ledger; when the goods need to be transported in a cross-land mode, starting point information and destination information of the goods are obtained, a path optimization algorithm is called, and waybill data containing the transportation distance are generated; constructing a corresponding feature vector based on a transportation distance, a time period coefficient, energy consumption data and a vehicle capacity reciprocal in the waybill data; inputting the feature vector into a machine learning model obtained through historical waybill data training, and outputting predicted transportation cost; and comparing the first product result with the predicted transportation cost, and determining the final transportation cost according to the comparison result, the first product result being the product result of the basic unit price and the transportation distance.

The invention discloses an intelligent detection method and system for long-distance driving safety of a large carrying vehicle. The intelligent detection method comprises the steps of obtaining a target carrying task, and allocating carrying difficulty levels to the target carrying task according to the cargo weight and the transportation distance; according to the carrying difficulty level, selecting drivers with matched levels from a preset driver alternative library; in the driving process, physiological characteristic parameters, driving behavior performance parameters and driving time environment parameters of a driver are obtained in real time and analyzed, when it is judged that the driver is fatigue, early warning is started, whether the driver is fatigue or not is judged again within a preset adjustment period, if yes, early warning is started again, and if not, circulation is ended; in the driving process, a test mode is set for analyzing whether the driver is fatigue or not, and if yes, early warning is started. The core pain points that hidden dangers are difficult to find, risks are difficult to pre-judge, supervision is difficult to achieve in real time and losses are difficult to control in traditional transportation management are broken through, the livelihood requirements of life and property safety of people are guaranteed, the traffic transportation efficiency is improved, and high-quality development of the logistics industry is promoted.

To efficiently transport luggage to transport for a long distance, without increasing the travel distance for one driver.SOLUTION: A transportation management device acquires a first arrival scheduled time of first mobile bodies for transporting first luggage and a second arrival scheduled time of second mobile bodies for transporting second luggage at each transshipment point and each relay point, and determines a target mobile body for switching luggage with a first mobile body from second mobile bodies for which second arrival scheduled time is within a set time from the first arrival scheduled time at each transshipment point and each relay point.SELECTED DRAWING: Figure 2