182 results about "Integer linear programming model" patented technology

A method and apparatus for optimal transporting of cargo is provided. The method includes optimizing a plurality of transportation decisions and mechanically transporting cargo through movement of a plurality of vehicles in accordance with a set of optimized transportation decisions. The decisions include transportation routes and schedules for the transportation vehicles, allocation of cargo to be transported to one or more demand locations by the transportation vehicles, nomination of cargo pickup by the transportation vehicles from the one or more supply locations, the use of specialized transportation locations, and vehicle assignments for each of the transportation vehicles. The set of decisions is optimized by collecting data relating to the various transportation decisions, using the data collected as part of a mixed integer linear programming model, and obtaining a solution to the model to arrive at a set of optimized transportation decisions.

The invention relates to an overall wiring method for a super-large-scale integrated circuit under an X structure. The overall wiring method comprises the following steps of an initial stage: discomposing a multi-terminal wire network into a plurality of two-terminal wire networks by using a Steiner minimum tree method, and performing side connection on connectable two-terminal wire networks by using the X structure, namely performing initial wiring to obtain approximate wiring crowded distribution conditions; a main stage: selecting the most crowded area from the approximate initial wiring result as a current wiring area, establishing an integral linear programming model for the current wiring area, solving the integral linear programming model, continuously expanding the wiring area, and sequentially solving the wiring area until the wiring area is expanded to a whole chip; and an aftertreatment stage: redefining wiring side cost, and performing wiring on the two-terminal wire networks which are not communicated to one another by using a labyrinth algorithm based on the wiring side cost so as to obtain the final overall wiring result. By using the overall wiring method, the quality of a wiring scheme can be improved; and the overall wiring method is easy to implement, and is high in using effect.

The invention discloses a traction power supply system energy management optimization method integrating hybrid energy storage and photovoltaic devices. The traction power supply system energy management optimization method comprises the steps of: step 1, acquiring traction substation load process data and a typical light intensity scene; step 2, establishing an objective function of an optimization model; step 3, establishing constraint conditions of the optimization model, and linearizing the constraint conditions of optimization model; step 4, establishing a hybrid integer linear programming model according to the objective function obtained in the step 2 and the constraint conditions obtained in the step 3; step 5, and solving the hybrid integer linear programming model obtained in thestep 4, so as to obtain the optimal charge and discharge power of the hybrid energy storage device, the optimal photovoltaic grid-connected power and the optimal power flow power of a back-to-back converter in a power flow controller, thereby completing the energy management optimization of a traction power supply system. The traction power supply system energy management optimization method improves the photovoltaic permeability and train regenerative braking energy utilization rate, reduces the electricity cost of electrified railways, and is closer to the reality.

The invention relates to the field of intelligent networked automobiles, in particular to a rolling optimization method for signal intersection traffic signal lamp and vehicle trajectory control, andeach time interval comprises the following optimization steps: acquiring vehicle information in a target area; solving the mixed integer linear programming model by using the vehicle information in the target area to obtain the signal lamp state and the intersection arrival time of the vehicle; solving the motorcade head vehicle trajectory optimal control model by using the moment when the vehiclearrives at the intersection to obtain a motorcade head vehicle trajectory, and solving the motorcade following vehicle optimal control model by using the moment when the vehicle arrives at the intersection to obtain a motorcade following vehicle trajectory; achieving vehicle track control through the head vehicle track and the following vehicle track of the motorcade, and achieving traffic signallamp control through the signal lamp state. Compared with the prior art, the vehicle track and the traffic signal lamp at the signalized intersection are optimized at the same time, so that the signal lamp and the vehicle track are controlled more accurately.

The invention provides an optimized dispatching method for a power grid including pumped storage units. The method includes the following steps: step 1, aiming at minimizing the operating costs of allunits, establishing an objective function model; step 2, setting various types of constraint conditions according to the daily actual working conditions of a power grid system including the pumped storage units; step 3, obtaining a mixed integer nonlinear programming model for power grid optimized dispatching according to the objective function model and the various types of constraint conditions, and performing linearization on the nonlinear part of the model to obtain a mixed integer linear programming model for power grid optimized dispatching; and step 4, calling a mathematical optimization toolbox CPLEX solver to solve the mixed integer linear programming model. The dispatching method considers the start-stop costs of each unit and the rotational reserve capacity constraints that canbe provided by the pumped storage units under different operation conditions, also performs linearization on an expression to convert the model into the mixed integer linear programming model, can carry out fast and reliable solution by using a mature solver, and has a good engineering practical value.

The invention discloses a congestion dispatch bilevel programming method of considering a real-time operation risk. The method comprises the following steps of building an objective function of an upper model by employing the minimum comprehensive cost of congestion dispatch as the target, carrying out constraining by using constraint conditions of the upper model, and building an objective function of a lower model by employing the minimum operation risk cost as the target and carrying out constraining by using the constraint conditions of the lower model, thereby obtaining a congestion dispatch bilevel programming model; and converting the congestion dispatch bilevel programming model into a mixed-integer linear programming model by using a KKT optimality condition and a linearization method and solving the mixed-integer linear programming model by using a CPLEX to generate an optimal scheme for congestion dispatch. According to the congestion dispatch bilevel programming method, theoperation risk, caused by uncertainty wind power output, to a system can be quantified, power adjustment of the congestion dispatch and joint optimization of the rotating reserve capacity are achieved, the condition of unavailable rotating reserve capacity of the system can be reduced, and resource allocation is further optimized.

A comprehensive energy optimization scheduling method for a park considering the thermal load demand response of a building: inputting the structure and parameters of the integrated energy system of the park according to the selected integrated energy system of the park; establishing an optimal energy system optimization plan for the park considering the thermal load demand response characteristics of the building Model; linearize the relevant nonlinear constraints in the park integrated energy system optimization scheduling model, establishing a mixed integer linear programming model and callthe corresponding solver to solve; outputting the solution results, including operating costs, host start and stop instructions, operating conditions , power supply, energy supply device energy supply command and power, centralized energy station water supply temperature, building indoor temperature. The invention fully considers the transmission loss and delay of the pipe network, the room temperature can adjust the characteristics in the comfort range, and the coupling relationship between the energy station, the energy supply pipe network, the energy supply network and the building load, can better realize the demand side management. Economically and reliably meet the user's energy needs.

The invention discloses a knowledge graph construction method for intelligent power grid customer service questions and answers, and the method comprises the following steps: S1, carrying out the entity and assertion recognition of a question through an LSTM model, and outputting the entity and assertion of the question; S2, performing semantic enhancement processing on the entity and the assertion to obtain a matched enhanced text, and constructing a local knowledge graph; S3, based on the matched enhanced text, performing answer query to obtain a final answer of the question; and S4, constructing an integer linear programming model according to the satisfaction of the user to the final answer and the maintenance cost of the knowledge graph, and updating the local knowledge graph. According to the method, high entity and assertion recognition accuracy can be achieved, power grid domain knowledge is automatically mapped into the local knowledge graph, online updating of the service knowledge base is rapidly achieved, and high-accuracy answers are achieved with low response delay.

The invention provides a wind-water-fire joint robust unit combination method. Firstly, an uncertain set is established for the uncertainty of wind power output, and the uncertainty of the wind poweroutput is described in three aspects of a wind power output prediction interval, a time smoothing effect and a spatial cluster effect. Then, a mixed integer linear programming model for water and power dispatching is built by using a linearization method, and the model is integrated in a robust unit combination model considering wind and power dispatching to obtain a wind-water-fire joint robust dispatching model. Finally, a robust optimization model in two phases is solved by adopting a C&CG method. Compared with a traditional robust unit combination model, the wind-water-fire joint robust unit combination model has the advantages that the operation cost is reduced, and the starting number and the running time of thermal power units are reduced, so that the carbon emission is reduced, andthe environmental benefit is achieved; the wind power consumption capacity of a system is increased due to the addition of water power; and the problem of a unit combination containing cascade hydropower stations can be solved within a reasonable time range.

This invention provides a method of rolled paper cutting and integrated stock optimization in paper factory, comprising the following steps: step one, determining an initial size of a problem about rolled paper cutting and integrated stock optimization; step two, establishing a mixed integer linear programming model for rolled paper cutting and integrated stock optimization; step three, solving a problem about mixed integer linear programming for rolled paper cutting and integrated stock optimization that is combined by two steps above to obtain an optimum target value and scheduling project; step four, adding one level to the size of the optimization problem to compose an optimization problem in new size; step five, solving the optimization problem in new size to obtain a new optimum target value and scheduling project possibly; step six, if the target value obtained in step five is superior to the target value obtained in step three, repeating steps four and five, otherwise, outputting the scheduling project obtained in step five. This invention can obtain the optimum rolled paper scheduling project without excessively adding the problem size.

An intermittent distributed generation in-situ voltage reactive control strategy setting method comprises the following steps: according to a selected power distribution system, inputting the parameters, load level and network topology connection relationship of lines, the operation voltage constraint and branch current limit of the system, the type, access position, capacity and parameters of an intermittent distributed generation, the predicted operation characteristic curves of the load and the intermittent distributed generation in the operation optimization period, and the initial values of the reference voltage and reference power of the system; building an active distribution network intermittent distributed generation in-situ voltage reactive control strategy setting model; linearly converting a nonlinear objective function and constraint conditions in the model to transform the model into a mixed-integer linear programming model; using a mixed-integer linear programming solving tool to solve the mixed-integer linear programming model; and outputting the solution. According to the invention, the randomness and volatility of the load and the intermittent distributed generation are fully considered, the model is solved using a mixed-integer linear programming method, and thus, an intermittent distributed generation in-situ voltage reactive control strategy is obtained.

The invention relates to an automatic driving service unloading method based on edge calculation. The method comprises the steps of S1, enabling a vehicle with an automatic driving function to sense the surrounding environment through various sensors and obtains data; S2, querying and detecting a current network state and available resources through an API before the vehicle runs; S3, enabling theedge or the cloud to calculate unloading strategies in different network states through an ILP integer linear programming model, and store the unloading strategies as a lookup table; S4, when the vehicle runs, registering the current network state with the stored lookup table, and when the matching is unsuccessful, performing adaptive dynamic scheduling by using a heuristic algorithm, and takingthe nearest task unloading strategy in the lookup table as the reference of the heuristic algorithm for iteration; and S5, returning a calculation result to the unmanned vehicle by the edge server andthe cloud, and repeating the operation in the step S4 at the beginning of the next period. According to the method, the low-delay performance required by unmanned driving is ensured, the service quality is improved, and the response time of an automatic driving calculation task is effectively shortened.

The invention relates to a high-performance X-structural multilayer global wiring method in a super-large-scale integrated circuit. On the basis of an XGRouter wiring device, the method includes the steps of adding a wiring mode of a new type, combining a subgroup optimization algorithm with a maze wiring mode based on new wiring cost, adopting a reduction strategy for prewiring volume in an initial stage, designing a dynamic resource scheduling strategy, then introducing a multilayer wiring model, simplifying an integral linear programming model of the XGRouter, and finally constructing a high-performance X-structural multilayer global wiring device. A simulation experiment result in a standard testing circuit indicates that compared with other kinds of global wiring devices, optimal effects can be achieved on both the most important optimization targets including the two indexes--an overflow value and a line length total cost in multilayer global wiring.

The invention discloses a power grid operation mode optimizing method for controlling a short circuit current level. The method is characterized by comprising the following steps of 1) determining a candidate disconnection branch set S, and 2) establishing a disconnection combination optimization model based on a node voltage method. According to the invention, the model established based on the node voltage method is a mixed integer linear programming model and can be solved by calling a CPLEX optimizer; an optimal disconnection strategy can be quickly determined by virtue of the powerful computing capacity of the CPLEX optimizer. Finally, simulation verification is performed on the validation of the model by taking an IEEE39 (Institute of Electrical and Electronics Engineers 39) node system and Zhejiang Power Grid as examples.

The invention relates to a content caching method based on federated learning in a fog computing network, and belongs to the technical field of mobile communication. By deploying the content cache inthe F-RAN, rapid and repeated data access can be realized, and the network transmission flow is reduced. Due to the limitation of the cache capacity, the prediction of the popularity of the content and the caching of which popular contents are very important. Generally, most classical prediction methods need to collect personal user information in a central unit, and many user privacy problems arecaused. The invention provides an intelligent F-RANs example based on federated learning. Federal learning is applied to a demand prediction problem, and content popularity distribution in a networkcan be accurately predicted. In addition, in consideration of the content request of the user, the problems of storage resource allocation and content placement in the network are jointly optimized. According to the method, the joint optimization problem is expressed as an integer linear programming model, and the purpose is to minimize the total flow cost of the network.

The invention provides a virtual power plant operation modeling method, which comprises the following steps: 1) a robust mixed integer linear programming model with profit maximum of a virtual power plant in participation in power market operation as a target function is built, and a robust interval optimization method is adopted in the mathematical model to handle uncertainty of the electricity price; 2) with an upper limit and a lower limit of the electricity price as a boundary, the robust interval model is built; 3) an iteration number, an iteration step size and a robust coefficient are set; and 4) IBM CPLEX software is used for acquiring the optimal bidding result of the virtual power plant in participation in market operation. Compared with the prior art, the virtual power plant operation modeling method has the advantages of good economic benefits, high calculation efficiency and the like.

The invention relates to a double-layer-two-stage operation method for multiple virtual power plants participating in an active power distribution network. The method comprises: analyzing uncertaintyof wind-solar output; constructing a Lagrange function of the constraint condition containing the uncertainty random variable, performing robust peer-to-peer model transformation by utilizing a dual theorem so as to convert uncertainty into a conventional mixed integer linear programming model, and constructing a double-layer-two-stage coordination optimization model of a plurality of virtual power plants participating in the active power distribution network on the basis. A hierarchical energy optimization strategy is adopted, meanwhile, the relation between the safety of the active power distribution network and the economy of the virtual power plant is considered, the interaction power of the upper layer and the lower layer is coordinated and optimized, a power distribution network safety model is optimized through a particle swarm algorithm, and a virtual power plant economy model is solved through CPLEX. According to the method, the uncertainty influence of renewable energy sources can be effectively coped with, the operation robustness of the system is greatly improved, and coordinated and optimized operation of the virtual power plant and the active power distribution network is realized.

The invention discloses a multi-energy flow transaction-oriented energy hub bidding method and system. The method first establishes a multi-energy flow transaction-oriented energy hub master-slave game bidding strategy model; then processes the energy hub master-slave game bidding strategy model , get the mixed integer linear programming model; and according to the mixed integer linear programming model, calculate the bidding strategy and the maximum operating income of the energy hub; hot sale price. Using the method or system provided by the present invention, fully considering the multi-energy flow trading capabilities of energy hubs with combined heat and power storage and combined heat and power generation functions, a bidding strategy for energy hub operators oriented to multi-energy flow transactions is given, and energy hubs are improved. The income of the operating entity in the multi-energy flow trading market.

The invention discloses a green wave coordination control method and device for an on-road left-turn line tramcar. According to the method, a mixed integer linear programming model taking the maximumweighted sum of the two-way green wave bandwidths of social vehicles as an optimization target is designed; the constraint conditions comprise social vehicle green wave system constraints, tramcar green wave system constraints, interaction constraints between the two green wave systems and signal period duration constraints; and an optimal solution of social vehicle green wave bandwidth is obtained on the basis of preferentially satisfying tramcar green wave passage of the left-turn line. According to the invention, green wave optimization can be carried out on bidirectional social vehicles and tramcars, the traffic efficiency of the tramcars and the social vehicles on the left-turn line is considered, and the parking frequency and the delay level of the tramcars and the social vehicles atthe intersection are effectively reduced.

The invention discloses a power distribution network collaborative planning method considering DG correlation and EV demand response; according to the method, a wind-photovoltaic independent normal distribution sample is generated by adopting a monte carlo random sampling method and a wind speed illumination probability distribution model, and the wind-photovoltaic independent normal distributionsample is converted into a related sample by applying an improved correlation matrix method so as to calculate wind-photovoltaic output power; a multi-target double-layer mixed integer linear programming model is established, a planning layer carries out site selection and constant volume on a wind generator, a photovoltaic component and a charging pile, and a running layer takes the lowest cost of electricity purchasing, network loss, load fluctuation penalty, waste electricity penalty and the like into consideration based on the thought of a penalty function, and expresses the investment, the DG output, the power flow, the EV charging an discharging price and the like in a linear constraint mode; a Voronoi diagram is applied to partition a road network system to obtain the service rangeof an EV charging station so as to determine an upper limit of the EV response; and the time scale of the unified double-layer model is converted into a single layer for solving in a unified mode, soas to obtain the planning result of the wind generator, the photovoltaic component and the charging station.

The invention discloses a wireless sensor network relay node deployment optimization method and a wireless sensor network. The optimization method comprises the step of setting a sensor node deployment area according to the gathering area of the sensor, and distributing a corresponding control degree for each sensor node deployment area; acquiring an effective communication area of the sensor nodedeployment area, taking the overlapping area between any two effective communication areas as a relay node deployment area; taking the minimum deployment cost as a target, and the control degree corresponding to the sensor node deployment area as the constraint, establishing an integer linear programming model, and solving the model to obtain the number of the relay nodes deployed in the relay node deployment area; for a sensor node deployment area with the control degree larger than 1, grouping the sensor nodes in the sensor node deployment area according to the data size, wherein the numberof the groups is equal to that of the control degrees, each group of sensor nodes is respectively managed by different relay nodes. According to the invention, the deployment cost is reduced to the minimum, and the reliability of the communication network is improved.

The invention discloses a tramcar network green wave coordination control method and device. A mixed integer linear programming model constructed by the method aims to maximize the weighted sum of thebidirectional green wave bandwidths of social vehicles; wherein model constraints comprise intersection phase sequence constraints, social vehicle and tramcar green wave constraints, social vehicle and tramcar interaction constraints, intersection trunk line intersection constraints, network outer ring closed-loop constraints and the like; and the constraints are relaxed through a 0-1 variable representing whether the green wave of a road section is interrupted or not, so that the green wave bandwidth of a tramcar is ensured to meet the traffic demand while the green wave bandwidth of socialvehicles is expanded as much as possible. According to the method, tramcar green waves of the whole road network rather than a single line can be optimized, the green wave band can reflect the road flow demand, and green waves of part of the road section can be interrupted under necessary conditions so as to achieve a globally optimal solution. And finally, cooperative, efficient and smooth operation of the tramcar and the social vehicle in the whole road network is realized.