9 results about "Transportation distance" patented technology

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 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.

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 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.