157 results about "Transportation scheduling" patented technology

An apparatus and method of reserving conveyance, such as taxis and limousines, in which the pickup locations, times, and contract are established and logged electronically. The system is configured to increase the assurance that the conveyance will arrive properly on time and on location, and that the patron will also keep their end of the agreement. The system preferably configured for disincentives for either party to not follow in accord with the contract.

A time-phased forecasting and replenishment system (20) for a retail supply chain for inventory management, financial management, capacity planning and transportation planning. A computer(s) (28) create time-phased plans for one or more retail facilities, such as various types of retail stores (23) and/or various types of suppliers (24). The system calculates projected sales for each product at each facility and calculates projected replenishment shipments between facilities and suppliers a specified number of weeks into the future. The calculated forecasts and replenishments are done in ways that account for the unique needs of retail organizations, and allow efficient processing and storage of the large data volumes typical in many retail organizations. In particular the system has specified logic for handling low-volume products, and has a transportation and capacity planning component that benefits retail stores. Also, the system is designed to operate on a continuous basis if desired.

The invention discloses a method for solving a multiple-depot logistics transportation vehicle routing problem. The method comprises steps as follows: inputting multiple-depot problem basic parameters based on real-time traffic information, establishing a multiple-depot logistics transportation scheduling mathematic model based on the real-time traffic information, adopting a clustering analysis method, introducing the particle swarm optimization algorithm to adjust and optimize ant colony algorithm pheromones, optimizing ant colony algorithm heuristic factors with the particle swarm optimization algorithm, solving an optimal distribution route, and establishing a mathematic model according to the multiple-depot logistics transportation vehicle routing problem based on the real-time traffic information; taking distances between clients and parking lots as main factors, performing area division on the clients and the parking lots with the clustering analysis method, and converting a multiple-depot problem into a single-depot problem; introducing the particle swarm optimization algorithm to improve the ant colony algorithm to solve the model. The method has the better global and local optimization capacity and has higher efficiency and stability when solving the multiple-depot problem.

A computer modeling application is disclosed for finding the optimal solution to maximize total net margin, for the assignment of vehicles (e.g., especially vessels) in an available fleet to perform a set of voyages to transport cargo comprising one or more bulk products during a planning period, as well as an apparatus and method employing the same. The fleet can include term vehicles and spot vehicles. The vehicles, voyages, and cargos can be heterogeneous. In one embodiment, the vehicles are crude carrier vessels and the bulk products are different grades of crude oil. To increase speed, the model is broken into linear programming and mixed integer (linear) programming problems. The model can be run on a real-time basis to support complex scheduling operations.

Methods for scheduling a transportation operation such as the operation of an airline. The method desirably selects a demand (100) for transportation specifying an origin, destination, and time of arrival or departure, and selects resources from a database of available resources such as aircraft (508), crew, and departure gates. The resource selection desirably is conducted so as to optimize a result function such as contribution to margin or other financial result from the particular operation specified in the demand. Upon developing a schedule fragment (108), the specified resources are committed, and the database of available resources is modified (110) to indicate that the resources are no longer available at the relevant times. The system then treats another demand and repeats the process so as to develop a full schedule. The system can develop a feasible schedule, even for a complex transportation operation in a brief time, typically in minutes or less. Schedules can be developed using alternative strategies and assumptions, and tested against one another.

The invention discloses an IoT (Internet of Things)-based intelligent logistics system which comprises a real-time logistics tracking service system; and the intelligent logistics system is characterized by comprising a logistics management platform subsystem, a transportation scheduling and monitoring subsystem, a warehouse management subsystem and an e-commerce platform subsystem. The intelligent logistics system disclosed by the invention can be adopted for effectively completing the acquisition of logistics information, the scheduling of transportation and the effective management of warehouses, and can sense and monitor each logistics link in real time, thereby effectively saving the manpower cost and the time cost; and an e-commerce platform system is provided, so that the openness of logistics and the transparency of the information can be improved.

An electronic method for managing transportation from an origin location, the method including the steps of: receiving an activity indicator including an activity location and an activity start time; identifying at least a first airport (or other origin location), the first airport being within a first threshold measurement of the activity location; and identifying at least a first departing flight (or other mode of transportation) associated with the at least the first airport, the identified at least a first departing flight associated with a flight arrival time and being at least between the origin location and the at least the first airport; wherein the flight arrival time of the at least the first identified departing flight is prior to the activity start time.

The present invention discloses a coordinated production and transportation scheduling method and system based on an improved tabu search algorithm, and a storage medium. The method includes batching jobs, initializing algorithm parameters, generating an initial solution, generating a neighborhood solution set, performing mutation, crossover and selection on individuals, determining a candidate solution set; calculating a fitness value of an individual, updating the candidate solution set; updating a tabu list, and determining whether an algorithm termination condition is satisfied; if yes, outputting the global optimal solution; otherwise, returning to the step 4. The present invention is mainly aimed at the coordinated production and transportation batch scheduling problem with multiple manufacturers. The whole profit of an enterprise in the production and transportation phases can be maximized, and high quality services can be provided for customers of the enterprise with improved core competitiveness of the enterprise.

A method for scheduling work and delivery of material for items in a factory which includes obtaining a customer order, determining a current state of an available inventory of material from a plurality of material sources, generating a material request plan for producing the item using the customer order and the current state of the available inventory and executing the material request plan. The customer order includes an item ordered by a customer and the item has an associated quantity of a material to produce. The customer order also includes a desired shipping schedule. The generating a material request plan includes scheduling based upon the desired shipping schedule. The executing the material request plan takes into account the desired shipping schedule.

The invention discloses a highway transportation scheduling method capable of meeting the demands of timeliness and economical efficiency and improving the vehicle scheduling efficiency. The highway transportation scheduling method comprises the steps of: 1) inputting all initial order information and vehicle information to form an initial order set and a vehicle set; 2) merging initial orders in the initial order set to obtain a virtual order, and forming a virtual order set by the residual initial orders after all virtual orders are merged; and 3) selecting a proper vehicle from the vehicle set to transport the virtual order and the initial order in the virtual order set, wherein a strategy that the faster the order is served and the better the effect is, or the least vehicles are utilized can be adopted for vehicle selection. Limited transport vehicle resources are utilized under a plurality of constraint conditions such as limitations of transportation time and distance condition, demands on working time of a driver and the maximal loads of the vehicles; and the vehicles can be reasonably arranged and an optimal path is planned to finish an appointed transportation task within specific time through the optimized scheduling scheme.

An down-hole mobile broadband streaming media network facing an unmanned locomotive is disclosed. In the invention, traditional down-hole operation is combined with a broadband streaming media network. A camera installed on the locomotive is used to collect video data in real time. Simultaneously, locomotive state data and positional information data are acquired. Through a vehicle-mounted communication terminal, a trackside AP is connected into. A mobile locomotive access network is connected into in a real-time and dynamic mode. The mobile locomotive access network transmits data into a transportation scheduling local area network through an optical fiber. A ground locomotive operation server, a video server and a remote control operation bench are used to carry out remote control driving. A scheduling instruction issued by ground scheduling personnel and a road condition analyzer are used to identify a road condition and carry out autonomous driving. By using the network, cross-AP real-time transmission of multipath streaming media is realized; the remote control operation bench controls an instruction to carry out real-time response so that unmanned driving and autonomous driving modes are realized; safety of down-hole operation is increased; and exploratory work is performed for wireless communication network innovation and development of mine track transport.

The invention relates to a logistics transportation method and a system thereof. The logistics transportation method comprises the following steps of through a plurality of modes of communication, acquiring position information and state information of a plurality of shuttle machines transported on a plurality of transportation corridors, wherein the plurality of shuttle machines is used for loading logistics containers; the state information includes an idle state information and an operation state information; according to the position information and the state information of the plurality of shuttle machines, determining a scheduling strategy of logistics transportation, wherein the scheduling strategy includes a transportation scheduling instruction and transportation path information; and according to the scheduling strategy, through the plurality of modes of communication, sending a control instruction to the plurality of shuttle machines so as to make the plurality of shuttle machines carry out transportation on the plurality of transportation corridors. Efficiency and safety of the logistics transportation can be increased.

The invention belongs to the technical field of transportation scheduling, and discloses a truck formation transportation scheduling method, a scheduling system, a medium and a data processing terminal. A vehicle-mounted unit sends execution feedback to a platform after obtaining a preset path and an optimal speed. In an actual traffic scene, the vehicle-mounted unit builds a vehicle surrounding environment model by applying multiple sensors of a vehicle, decisions are made by combining real-time road section information sent by an intelligent road side system, and safe driving of the vehicle is controlled. The vehicle-mounted unit completes merging and grouping of vehicles in an allowable speed range of a road section and completes docking in allowable delay time, so that energy consumption is reduced, and task efficiency is guaranteed. The invention designs the formation transport organization method and system architecture of freight vehicles in combination with IVECS, and proposes to schedule the freight vehicles and merge the freight vehicles into a fleet set to travel together on a road, so as to achieve the purposes of energy conservation and emission reduction. Compared with a single vehicle driving scheme, the scheme of combining the vehicles into the queue can save energy consumption.

The invention relates to a time-varying demand associated logistics transportation optimized dispatching method based on a bee colony algorithm. The method comprises the specific implementation steps that (1) a distribution center acquires known demand information of a client; (2) an initial solution is constructed; (3) optimization is performed on the initial solution through an artificial bee colony algorithm based on taboo table thought; (4) a pre-loop passing through all the vertexes of a complete undirected graph G is obtained; (5) the distribution center collects time-varying information and acquires demand information of the time-varying client; (6) the pre-loop is adjusted according to a certain rule, and constraint conditions are satisfied; (7) the process is ended. According to the method, a final dispatching scheme based on time-varying demand associated with transportation dispatching is obtained.

The invention discloses a chaos immune algorithm based multi-vehicle assembly line logistics transportation scheduling method, and aims to solve the problem about logistics transportation scheduling of multi-depot and multi-vehicle assembly line production. The method includes: firstly, according to characteristics of an assembly line production mode, determining basic factors of the logistics transportation scheduling problem, wherein the basic factors include time windows, distribution periodicity, cargo relevance, multi-type depots and the like of production logistics transportation scheduling; secondly, establishing a mathematical model including an objective function and constraint conditions; thirdly, designing a chaos immune algorithm for the proposed mathematical model; finally, utilizing the designed chaos immune algorithm to solve the mathematical model. By applying the designed algorithm, the problem about logistics transportation scheduling of assembly line production of multiple vehicles and multiple distribution centers is solved, and solution quality of the algorithm is improved to a certain degree while rate of convergence is increased to a certain degree as well.

A transportation schedule planning support system receives an order of one or more types of products which requires a use-by date control, and transports the products from one or more stock-carrying bases to one or more delivery destinations. In the system, a user previously registers a transportation route candidate from a stock-carrying base to each delivery destination adoptable as a solution, as a base group. A necessary use-by date for a product to be delivered next is determined based on an actual delivery to each delivery destination. The number of vehicles allocatable to a transportation at each base according to a vehicle type, and a vehicle type not used in each base group are added to a restriction condition. A mixed integer programming is applied using an expected obtainable profit obtained by delivering each product as an objective function.

The invention discloses a multi-distribution-center logistics transportation scheduling method, and the method comprises the steps: obtaining the basic parameters of a multi-distribution-center logistics transportation scheduling problem, wherein the basic parameters comprises coordinates of logistics distribution centers, coordinates of customers, the number of distribution centers, the number of vehicles, the maximum traveling distances of vehicles, and the distribution start time of the vehicles; solving a mathematic model of the multi-distribution-center logistics transportation scheduling problem according to the basic parameters through employing an adaptive inertia weight parallel particle swarm optimization algorithm, and outputting an optimal logistics distribution path scheme. When the method is used for path planning, the method improves the convergence speed and precision, obtains an optimal logistics distribution path scheme, and meets the demands of customers. The invention also discloses a multi-distribution-center logistics transportation scheduling system, and the system has the above beneficial effects.

A new model for transportation planning vehicle scheduling (TPVS). A database table for shipment documents independent of an order for goods, e.g., a sales order is created. When an order for goods is received, the database table is populated with a shipment document corresponding to, but independent of, the order for goods. This shipment document is owned by the TPVS system.

The invention discloses a robust optimization-based emergency resource mobilization and transportation scheduling plan generation method, including step 1: considering the demand of the disaster area and the uncertainty factors of transportation time, and establishing the uncertainty parameters for the integration of emergency resource mobilization and transportation scheduling An optimization model, wherein the uncertainty parameter optimization model includes a total cost optimization objective and constraint conditions; Step 2: using a robust optimization method to process the total cost optimization objective and the constraint conditions under the uncertainty parameter conditions into a robust Stick corresponding total cost optimization objective and robust corresponding constraint conditions; Step 3: Solve the robust corresponding total cost optimization objective based on robust corresponding constraint conditions; Step 4: Output emergency resource mobilization and transportation scheduling plan. It has the advantage of being able to quickly and effectively generate emergency resource mobilization plans such as rescuers, transportation vehicles, and medical services, and transportation dispatch plans for rescuers and seriously ill patients after a major natural disaster occurs.

The invention provides a total tardiness transport plan scheduling algorithm based on improved particle swarm optimization. The algorithm comprises the steps of firstly, establishing a total tardiness value mathematic model based on input variables and defining the number n of to-be-processed works and the number m of machines, and the time pj required for processing of each to-be-processed work and the delivery term dj; secondly, solving a construction drawing according to the total tardiness value mathematic model; thirdly, based on the construction drawing and according to state transition rules and pheromone update rules, completing search and acquiring a solution making the total tardiness T minimum. Based on the ant colony algorithm and according to the characteristics of the total tardiness transport plan scheduling problem (P//T) of parallel machines, the improved Heuristic Ant Colony Optimization (hACO) is proposed and performance optimization research is performed on the algorithm to improve the determination accuracy of optimal solutions of events and guarantee the internal data processing and screening efficiency.

The invention provides a logistics freight transport system, including a client side subsystem, a transport side subsystem, a warehousing side subsystem and a monitoring center subsystem. The client side subsystem is used for realizing client registration and sending client information to the monitoring center subsystem, and sending logistics order-placing, transport order-placing and goods returning or changing note information to the transport side subsystem; the transport subsystem is used for receiving the logistics order-placing, transport order-placing and goods returning or changing note information to form a transport plan, sending the transport plan and transport vehicle fleet data to the monitoring subsystem, receiving inventory information sent by the warehousing side subsystem, and sending transportation process information and GPS positioning information to the monitoring center subsystem; and the warehousing side subsystem is used for sending warehouse basic information and inventory cost sheet information to the monitoring center subsystem, forming inventory information according to cargo storage and outlet situations, and sending the inventory information to the transport side subsystem.

A system and method is disclosed for managing salvage shipments in a transportation network. The system includes a transportation planner coupled with one or more entities in the transportation network. The transportation planner determines an optimized transportation plan for delivery and pick-up of shipments throughout the transportation network.

The shipping planning system decides the product, the shipping quantity and the price from which the maximum profit increase can be obtained based on the relational database between the price and the shipping quantity. The plan is made under the assumption that an available resource (inventory) is consumed firstly, an inventory planning resource is consumed secondly, and only insufficient resource is additionally obtained. The practical range of the profit increase by shipment of a certain product in the plan is evaluated by relative profit that is the marginal profit of the product subtracted by the Opportunity Loss by other products that share the resource.

Methods, systems, and processor-readable media for the stochastic optimization of public transport schedules. A real-world collection of transit instances can be derived from a transport system and fed as input to a two-stage stochastic program. A schedule offset can be relaxed in the two-stage stochastic program to allow the two-stage stochastic program to operate according to the real-world collection of transit instances. An optimized transport schedule can then be derived from the two-stage stochastic program for use by the transport system based on the schedule offset and the real-world collection of transit instances.