98 results about "Demand point" patented technology

The invention discloses a construction optimizing and operating method of an automatic fixed-point picking-up system of a logistics express. A system optimizing scheme containing a picking-up machine layout, a customer demand point attribution division and an express delivery line is generated according to the geographical position, demand amount and relevant logistics cost of a demand point of city express customers. When the system operates, a delivery center classifies expresses according to an automatic picking-up machine service range of the delivery center and the expresses are delivered by delivery workers according to an optimized delivery line scheme; and meanwhile, picking-up information is sent to the customers. After the customers pick up the expresses, the information is fed back to the delivery center by a picking-up machine so as to finish the whole express delivery task; otherwise, the customers are manually called to pick up the expresses; and if the customers cannot be contacted, the expresses are sent back to sending places to finish the delivery task. By virtue of the operation of the system, the abutting problem of time and space of the delivery workers and picking-up persons can be effectively solved in the express delivery process, so that the express delivery cost is reduced, the whole efficiency is improved, and the low carbonization and greening of the logistics express are realized.

The present invention relates to a logistics delivery route planning method based on geographic positions. The method comprises the steps of obtaining the geographic positions of a delivery center and the demand points, and the shortest distances between the delivery center and the demand points and between any two demand points; according to the geographic positions of the demand points, dividing the demand points into different regions; according to the saved mileages, determining the delivery routes taking the delivery center as the starting and ending point and the demand points as the target points of each region, wherein the saved mileages are the saved shortest actual distances. The logistics delivery route planning method based on the geographic positions firstly divides the demand points of which the straight-line distances are shorter into the regions roughly, then distributes the deliver routes for the demand points of each region according to the actual saved mileages, so that each delivery route is optimal, and further the purpose of reducing the transportation cost is achieved. The present invention also discloses a logistics delivery route planning system based on the geographic positions.

The invention provides an urban centralized charging station planning method based on an improved K-means algorithm. The method comprises the steps that a centralized charging station location map is established according to the geographical location information and the charging demand of each charging demand point in an area to be planned; for the centralized charging station location map, a charging station planning scheme is acquired based on a method combining a graph theory central point and a K-means clustering algorithm; and the construction cost of a charging station, the charging cost of a user and the operation annual income of the charging station are used as evaluation indexes to optimize the charging station planning scheme. The urban centralized charging station planning method based on the improved K-means algorithm has the advantages that fast location of the charging station is realized based on the clustering idea; the quantitative evaluation indexes are used to realize the optimal location planning of the charging station; and a scientific basis is provided for location planning and planning scheme evaluation of the charging station.

The invention relates to method and device for planning a logistics distribution route. The method and device are that a distribution point and a demand point are treated as nodes, and the directly-arrived shortest routes between the distribution point and the demand point and between the demand points are treated as the edges, so as to construct a route connection map; task sub-maps in which the total distribution quantity of the nodes included is not greater than the preset transportation quantity tolerance are divided according to the distribution quantity of each demand point node and the distance of each edge; the minimum support tree for all the nodes included in the task sub-maps is constructed; a loop including the longest supporting tree and the longest path is selected from the loops formed by the minimum supporting trees and the distribution point nodes as a main distribution route; return routes are provided for hanging nodes outside the main distribution route. With the adoption of the method an device, the distribution route is reasonable; the demand points are reasonably adjacently combined by a self-organization manner, and the task sub-maps are divided; therefore, the method and device are applied to large-scale distribution route planning, and can effectively reduce the distribution time and increase the distribution load factors.

The invention relates to a logistics distribution route planning method with a time window based on a cuckoo algorithm, which comprises the following steps: firstly, according to a logistics distribution vehicle route planning problem with a time window to be solved, a customer data model is established, demand point data is set and a straight line distance between demand points is calculated; according to the actual demand of logistics distribution, a VRPTW model is established, which increases the penalty of time cost if it arrives earlier than the time window, and dispatches other vehicleslater than the time window to improve the quality of service. The cuckoo algorithm is used to find the optimal distribution order iteratively; finally, the number of vehicles needed, the distributionroute of each vehicle, the value of the objective function and other results are output to complete the route planning. The invention adopts the cuckoo algorithm with strong global searching ability,good robustness and few parameters to select the optimal distribution path, which is more reasonable than the traditional distribution path planning method, and is favorable for the logistics enterprise to reduce the transportation cost and improve the service quality and efficiency.

The invention discloses a charging station location method considering the traffic running state of an urban road network, comprising the following steps of S1 obtaining the OD travel data of the region, the vehicle holding quantity and the electric vehicle proportion, the distribution law of the initial electric quantity and the charging electric quantity, establishing the regional road network diagram, considering the traffic running state of the road network, and carrying out VISSIM dynamic traffic assignment simulation to obtain the vehicle traveling track, speed and distance data; 2 assigning an initial electric quantity and a charging electric quantity to each vehicle, and combining that data of the vehicle travel track, the speed and the distance, screening and obtaining the distribution of the demand point in the area; 3 aiming at minimizing that construction and operation cost of the regional builder and the detour cost of the user, and taking the charging demand of the user as a constraint condition, and obtaining the optimal quantity of the char station construction; S4 determining the final location of the regional charging station according to the distribution of the regional demand points and the optimal number of charging stations. This method provides a reference for the determination of the number and location of charging stations, and has practical significance.

The invention discloses a logistics dispensing center addressing method based on simulation software. The method comprises the following steps: selecting a candidate place of a dispensing center; determining a capacity upper limit, a fixed investment and a flow rate; determining a transportation rate; constructing a logistics cost model and a shortest-distance model; constructing a simulation model; operating the simulation model; optimizing a minimum logistics cost; according to relation relations among the address of a primary election dispensing center, multiple demand points needing dispensing of the primary selection dispensing center and multiple resource points supplying goods to the primary selection dispensing center, constructing the simulation model; completing operation of the simulation model through connecting rules, working modes, system functions and distribution functions which are provided by the simulation software; and the simulation software, according to the constructed shortest-distance model, optimizing a shortest distance, and obtaining an optimal dispensing center address. According to the invention, optimal configuration of a system is obtained by use of a self-carried optimization algorithm module OPTIMIZER, and finally, a logistic dispensing center satisfying conditions of the minimum logistics cost and the shortest distance in a dispensing process is obtained.

The invention relates to the technical field of logistics distribution, particularly a method and a device for planning logistics distribution nodes. The method comprises the following steps: constructing a connected graph by taking demand points as nodes and a direct reachable shortest path between demand points as sides; dividing the connected graph into connected sub graphs as many as the distribution modes according to the business volume of each demand point; planning a distribution path according to each connected sub graph, and continuously updating and optimizing to obtain optimal positions of distribution nodes; calculating to obtain current operation profit; increasing the quality of the distribution nodes, repeating the steps until the operation profit gain is smaller than or equal to zero, outputting the quantity and the positions of the distribution nodes corresponding to the maximal operation profit. According to the technical scheme adopted by the invention, the distribution node planning strategy can be quantized, so that irrationality due to planning according to experience and intuition is avoided, the resources are further reasonably utilized and the distribution cost is reduced.

The invention relates to a Hadoop-based shared bicycle parking site selection method which comprises 1) shared bicycle demand point prediction based on a distributed clustering algorithm; 2) a sharedbicycle parking site selection model based on multi-objective optimization; and 3) a model solution algorithm based on a NSGA-II algorithm; the algorithm is implemented by Hadoop, and after a population is initialized, the evolution process of each generation is completed by MapReduce. The Hadoop-based shared bicycle parking site selection method is expected to improve the rationality and the accuracy of the shared bicycle parking site selection, and to achieve standardized shared bicycle management. For a large amount of generated shared bicycle travel data, the method establishes a demand prediction model based on travel data, and predicts a shared bicycle demand point through a Hadoop framework and a clustering algorithm.

The invention provides a fresh agricultural product distribution route optimization method and a storage medium. Each demand point submits information such as own position coordinates, the quantity ofgoods to be distributed and required distribution time and range to a system, and a fresh agricultural product distribution route multi-objective optimization model is established with minimum distribution cost and maximum customer satisfaction as optimization objectives. Meanwhile, the model is solved with an adaptive genetic algorithm, and a distribution route optimization scheme is obtained. Avehicle speed characteristic model under different weather conditions and in different time periods is established; a time window penalty cost function of fresh agricultural products is established;the fresh agricultural product distribution route multi-objective optimization model is established; distribution routes can be planned according to the road conditions during distribution, and accordingly, the purposes of minimum distribution cost and maximum customer satisfaction are achieved.

The invention provides an electric power material distribution center location selection method. The method comprises the following steps that A, a destination region is divided into sub-regions; B, distribution centers are arranged at different logistics nodes in each sub-region, and the sum of weighted distances from suppliers and the distribution centers at different positions in the sub-regions to a demand point is determined; C, the position of the distribution center corresponding to the minimum weighted distance in each sub-region is determined as the position of the distribution center of the sub-region. By the adoption of the electric power material distribution center location selection method, the characteristics of a supplier inventory management pattern and a joint inventory management pattern can be considered, and a proper location of an electric power material distribution center is determined based on the virtual inventory technology and the time satisfaction degree; therefore, complex electric power distribution system requirements are met, resources are optimized, and the service quality is improved.

An automatic transmission fluid (ATF) filtration system that combines both coarse filtering mesh and microfine depth filtering elements simultaneously to remove a wide range of particulate matter, but also maintains an unrestricted flow of ATF to the pump to ensure its volumetric efficiency is disclosed. In the present invention ATF at system pressure is delivered via a hydraulic circuit to a microfine depth filtering element for depth filtration (i.e. several layers of filter media) and, thereafter, is passed into the intake of the coarse filter element or, alternatively, between the intake of the coarse filter element and the pump intake. Because ATF flow through the coarse filter element is continuous and independent of the microfine depth filter element, the volumetric efficiency of the pump is maintained in all phases of operation even at the highest demand points such as at cold start-up, hot idle, and high volume / demand situations.

The invention provides an aerial rescue response method based on an unmanned aerial vehicle. The invention discloses a method for treating natural disasters. The method comprises the following steps: in an initial stage of natural disasters, predicting the material demand of a disaster area affected area, determining the latitude and longitude coordinates of a demand point of the disaster area, determining a material putting place, and transporting disaster relief materials to the demand point of the disaster area by utilizing an unmanned aerial vehicle, thereby improving the initial rescue efficiency after natural disasters occur, and meeting the urgent demand of wounded personnel in the disaster area on medical materials at the initial stage after disasters; through flight path planning of the unmanned aerial vehicle, shooting main road traffic damage conditions, detecting disaster situations of a disaster area, feeding shot videos back to the emergency rescue command center so as to enable the emergency rescue command center to conveniently plan a ground rescue route and make a decision on an emergency scheme.

The invention discloses a distribution task scheduling optimization method of an intelligent electric meter, which belongs to the research field of distribution methods of electric energy metering devices. The method of the invention combines the actual situation of the provincial metering center, and transforms the distribution task scheduling problem of the electric energy metering device into a vehicle path planning and vehicle scheduling problem in which a distribution center uses different types of distribution vehicles to deliver to multiple demand points. This problem also takes into account the constraints of customer needs and geographical location, vehicle capacity and time constraints. This plan comprehensively considers multiple factors such as the demand type, delivery time, delivery space, and vehicle capacity of the metering device distribution of the provincial metering center, and designs an optimization algorithm for the distribution task scheduling of the metering device, thereby reducing the burden of traditional manual formulation of the metering device delivery plan. Many disadvantages provide strong support for timely, economical, efficient and accurate distribution of metering devices.

The invention relates to an improved reinforced immune algorithm-based agricultural internet-of-things resource allocation method. Related information of resource demand points and supply points in agriculture is obtained by adopting an internet-of-things technology, and the supply points perform efficient resource allocation on the demand points through allocation vehicles by utilizing an improved reinforced immune algorithm; and the improved reinforced immune algorithm is an algorithm obtained after an immune algorithm is improved by utilizing a reinforcement learning thought, the improvement refers to the initialization of a Q table according to the distances between the resource supply points and demand points where the vehicles are located, the Q table is updated according to an antibody with a minimum fitness value currently in each iteration, mutation of the antibody is guided by using the current Q table in a mutation stage, and meanwhile, when the Q table is continuously updated in the same position, the Q table is adjusted to escape from local optimum. The method has the characteristics of strong learning capability, high self-adaptivity, numerous allocation objects and high response speed.

The invention relates to a water pump frequency conversion speed regulation control method, device and system. The method comprises the steps that the maximum theoretical flow and corresponding water pump lift, and the minimum theoretical flow and corresponding water pump lift of a water pump water supply or closed-type water circulation system are obtained; according to the maximum theoretical flow and corresponding water pump lift, and the minimum theoretical flow and corresponding water pump lift, a pipe feature theoretical curve is drawn; the current fed water pressure value and the current discharged water pressure value of a water pump in the water pump water supply or closed-type water circulation system are detected, and the actually measured lift of the water pump is calculated; the current flow of the water pump in the water pump water supply or closed-type water circulation system is detected, and according to the pipe feature theoretical curve, the theoretical lift corresponding to the current flow is obtained; and according to the actually measured lift and the theoretical lift, the frequency of the water pump is adjusted until the actually measured lift after the frequency is updated and the theoretical lift after the frequency is updated are the same. The method does not need to arrange a sensor on any demand point, easiness and practicability are achieved, and the energy conservation effect is good.

The invention discloses a multi-computing-based software project test quantitative evaluating method and system. The multi-computing-based software project test quantitative evaluating method comprises the steps of: aiming at demand points of a software test project in each stage, presetting a test case; allocating a stage score and a demand point score for each stage according to a total score of the software test project; testing a software product by using all unsanctioned test cases in a stage to which the current test belongs, recording the quantity of sanctioned or unsanctioned test cases of the software product in the local test; when the software product passes all test cases in the stage to which the current test belongs, scoring the stage according to a preset scoring formula; and when the software product completes all stages of test, accumulating according to stage scores obtained in all stages, so as to obtain an evaluating fraction of the software test project by a software manufacturer. By adopting the method and the system, the staging evaluation of the project can be realized through a quantitative evaluating factor, and the software completing quality and the project test evaluating level are improved.

The invention provides an emergency material storage site selection optimizing method based on a box uncertainty set, and relates to the technical field of the emergency service facility site selection optimization in the uncertain environment. The method comprises the following steps: setting parameters of a robust optimization model and uncertain demand of a method thereof; constructing the robust optimization model; randomly generating the position of each demand point and the corresponding demand quantity thereof, and providing random robust disturbance; to obtain a global optimum fitnessvalue and an optimal solution, namely emergency material storage position coordinates. According to the provided emergency material storage site selection optimizing method based on the box uncertainty set, because the model has the non-convex, non-linear and multi-constraint features, and has the NP-hard feature mathematically, a coding method of an artificial bee colony algorithm is designed forsolving the robust optimization model, the robustness is good in the different scales and the different disturbance demands, the scientific site selection of the emergency material storage in uncertain factors is realized, and a risk is avoided in the greatest degree under the uncertain situation.

The invention relates to a high-speed rail hub accessibility calculation method based on an improved two-step mobile search method, a high-speed rail hub accessibility spatial distribution fairness evaluation method based on a variable coefficient and a Spearman level correlation coefficient, and a newly-added high-speed rail hub accessibility influence method based on the improved two-step mobilesearch method. According to the method, a two-step mobile search method is improved, the traffic cost of facility points and demand points is effectively measured, and in the accessibility analysis process, by improving a search carrier of a spatial action domain, a calculation method of a road traffic condition and attributes of a search radius, analysis better conforms to the actual situation,and the accuracy of accessibility measurement and calculation is improved. According to the method, the influence of the high-speed rail construction on the spatial balance of reachable distribution is analyzed by applying the variable coefficient and the Spearman level correlation coefficient while the reachability is analyzed to be improved, so that residents can enjoy more high-speed rail services and the services can be distributed in a balanced manner in space due to the arrangement of the high-speed rail.

The invention discloses a logistics distribution center site selection method and device for a community fresh food chain store. The method comprises the following steps of evulating distribution center site selection suitability from the perspective of multiple land suitability evaluation factors by utilizing multiple GIS spatial analysis methods; determining the weight of each factor by using anAHP analytic hierarchy process, and comprehensively evaluating the land suitability by using a grid overlay analysis method to obtain a distribution center candidate position; predicting online and offline demands of demand points (community fresh chain stores) by using house prices, population, urban thermal data and the like; and based on the candidate positions and the demand quantity of the demand points, establishing a P-median model, and solving by using a greedy take-away heuristic algorithm to obtain a final site selection result of the distribution center. According to the invention,various factors of the supply point and the demand point can be comprehensively considered, and scientific and reasonable site selection is carried out on the logistics distribution center of the fresh food chain store, so that the layout rationality of the logistics distribution center is improved.

A method for use in designing a utility network to provide a utility to a geographic area. A computer system determines a demand point within the geographic area at which to provide the utility. The computer system also determines a source point to provide the utility to the utility network. A connection path through the geographic area is determined, connecting the source point to the demand point. In addition, a bill of materials may be generated, indicating a set of equipment required to convey the utility from the source point to the demand point along the determined connection path.

The invention provides a dynamic vehicle path optimization method based on a fuzzy rolling time domain control strategy. The method specifically comprises the following steps: Step 1, initializing fuzzy rolling time domain control; Step 2, acquiring customer information; Step 3, planning a path; Step 4, rolling a window; and Step 5, performing residual processing; the dynamic vehicle path optimization method has the beneficial effects that compared with rolling time domain control, first-in-first-out, nearest neighbor and other methods, the fuzzy rolling time domain control method provided bythe invention reduces the delivery distance and the total waiting time of customers on the aspect of processing the dynamic vehicle path problem, and is more reasonable and effective. According to themethod, the threshold of the time window of the traditional rolling time domain is blurred, the problem that a traditional rolling time domain cannot plan demand points near a time window as a wholeis solved, so that the neighborhood search capability of the traditional rolling time domain is improved, and the fuzzy rolling time domain control strategy is suitable for solving various dynamic problems such as dynamic vehicle path problems.

The invention discloses an emergency repair resource optimization decision-making method which mainly resolves the problems that maintenance resource shortage and resource conflict often occur in each maintenance task during the process of collaborative maintenance support in war. Features and demands of battlefield emergency repair resource allocation are analyzed under the condition of continuous consumption, so that two decision-making objectives can be determined, namely time from receiving a task to resource reaching a demand point is short and the number of support points which are put to use is minimum, a double-layer optimized decision model with multiple support points, multiple demand points, and multiple resources of battlefield emergency repair is established, and an algorithm is raised. The method can be adopted to allocate resources in a scientific and reasonable mode, and can greatly improve use ratio of battlefield emergency repair resources particularly under the condition that supply and demand contradiction of battlefield emergency repair is obvious.

The invention discloses a public benefit donation material distribution method and device, computer equipment and a storage medium. The public benefit donation material distribution method comprises the steps: obtaining supply information of a donator, and converting the supply information into a supply vector; acquiring demand information of a recipient, and converting the demand information intoa demand vector; according to a preset donation material distribution model, mapping the supply vector and the demand vector into a multi-dimensional coordinate system defined by the preset donationmaterial distribution model, taking a coordinate point where the supply vector is located as a supply point, and taking a coordinate point where the demand vector is located as a demand point; calculating the distance between the supply point and the demand point in the multi-dimensional coordinate system to determine the most matched donation recipient and the donation recipient, and generating adonation distribution record; and storing the donation distribution record in a preset donation database, the preset donation database being used for disclosing the donation distribution record. According to the technical scheme, the problem that donation supply cannot be accurately matched with donation requirements is solved.

The invention relates to an offshore emergency material optimal scheduling method and system. According to the offshore major accident emergency material optimization scheduling method considering multiple demand points provided based on the hybrid heuristic algorithm, according to actual conditions, offshore emergency material transportation is carried out on emergency optimization ships of all accident points, and proper materials are assembled for each ship each time when the ship is sailing so as to achieve the optimal transportation efficiency; and meanwhile, considering that the stock ofthe emergency base is limited, the corresponding land supply material transportation scheme needs to be optimized according to the dispatching condition of the marine emergency materials, so that theminimum transportation time of the land supply materials and the minimum total cost of the system are realized.

The invention discloses a method and system used for calling movable type energy storage devices. The method includes measuring the residual electric quantity of each energy storage device; receivingpower supply demand instructions sent by power supply demand points, and ordering the power supply demand points from large to small according to the demand electric quantity in the power supply demand instructions; determining the ordering sequence of the power supply demand points as the priority of the power supply scheduling of the power supply demand points; ordering the energy storage devices from near to far according to the power supply demand point of the current highest priority; and selecting the energy storage device that is nearest from the power supply demand point, and selectingthe energy storage devices according to the sequence of the residual electric quantity from large to small until the energy demands of the power supply demand points are met.

The invention discloses a business mode and method based on stereoscopic vision interaction and user behavior artificial intelligence application. A digital lightweight technology is adopted to realize virtual display, data acquisition is performed on interaction behaviors, logic sequences and the like of users and the users, and the data acquisition results are compared with historical users to form decision algorithm system application conforming to the users, so that user data capture is provided for brands to realize precision marketing and potential demand trend analysis, customized application and the like; the invention belongs to a visual and artificial intelligence application business mode and method. Front-end and rear-end investigation of different personalities and preferencesis creatively met for brands, and cognitive enhancement and improvement experience on user demand points are formed; different user personality multi-dimensional data acquisition and algorithms are integrated through artificial intelligence, user optimal experience and decision logic feedback are provided in real time, the practicability of user time cost is reduced, and social popularization andapplication are achieved through artificial intelligence. A user is creatively provided for brand real feedback data capture, potential demand tendency data visualization novelty application solutionis provided, and the social resource intensive configuration utilization rate is improved.

The invention relates to an electric vehicle charging station planning scheme acquisition method considering different load increases. The electric vehicle charging station planning scheme acquisitionmethod comprises the following steps: 1) acquiring digital features of three travel laws, including an initial state law, a state transition law and a charging information law; 2) simulating the obtained three laws by using a roulette method, and screening charging demand points; 3) establishing a mathematical model based on constraint conditions of traffic constraint, power distribution networkconstraint and economic constraint; 4) solving the mathematical model by adopting a genetic algorithm, setting a fitness function by taking the lowest cost as a principle, setting a death penalty to remove a scheme which does not conform to the distribution network constraint and the cost constraint, and selecting a candidate station set conforming to the traffic constraint; and 5) according to the selected candidate station set conforming to the traffic constraint, planning the charging demands in different load growth modes. Compared with the prior art, the electric vehicle charging stationplanning scheme acquisition method has the advantages of saving resources, ensuring the rationality of the planning scheme, and being high in applicability and the like.

The invention relates to an intelligent logistics method mainly comprising material supply and automatic library operation. Material supply comprises three-level pulled replenishment information acquisition, supplier replenishment operation, real-time material tracking, actual delivery, and system docking. Automatic library operation comprises shelving storage and sorting. Timely supply of materials from a supplier to a warehouse and then to a demand point and whole-process tracking can be handled, materials are traced, and a win-win situation of supply and demand sides is achieved. The whole process is controlled by an information system without manual intervention. Multi-system integration is adopted. Data information is automatically triggered to a corresponding person in charge. The intelligent logistics method is a successful operation of an intelligent logistics module.

The invention relates to an intelligent contract demand matching method and device based on a block chain, computer equipment and a storage medium. The method comprises the following steps of performing keyword identification on historical contract information and historical demand information of a demand initiator and obtaining demand points, according to key points according to requirements of users, matching out an initial smart contract meeting user requirements; sending corresponding information and contract confirmation messages to both parties participating in the contract so that bothparties can reach a consensus about the smart contract; when two parties finish cooperation of contract confirmation decisions, confirming the contract; when the encrypted information carrying the contract confirmation information is sent; decrypting and verifying the encrypted information; if the verification is passed, creating the smart contract, meaning that the whole process of the smart contract can be exeucted. A user does not need to consume too much energy to select the smart contract, the proper contract can be quickly matched according to the demand key points of the user, the smartcontract is reasonably created from multiple aspects, and efficient and reasonable construction of the smart contract is realized.