217 results about "Integer programming model" patented technology

A CHP optimal dispatching model is a mixed integer programming model and is used for a district heating system (DHS) comprising a heat source, a heating network and a heat load, and the heating network comprises a heat transmission network and a heat distribution network. A plurality of heating areas is divided, and one day is divided into a plurality of time periods; the heat transmission loss of the heat distribution network is omitted, and a heat transmission network model taking transmission time delay of the heating network into consideration is established according to the heat transmission network; a terminal heat consumer model capable of reflecting indoor temperature is established; and a combined optimal dispatching model comprising conventional generators, wind power units, CHP units, electric boilers and heat storage tanks is established.

The invention relates to a dynamic adjustment-based express delivery distribution optimization method. The method includes the following steps that: express delivery dynamic information is obtained in real time, wherein the express delivery dynamic information contains the locating information of express delivery vehicles, goods delivery point information, goods taking point information and real-time traffic information; with minimum total distribution costs adopted as an objective function, a mixed integer programming model is adopted to construct a current distribution path according to the express delivery dynamic information, wherein the minimum total distribution costs contain the transportation costs of the vehicles, the fixed costs of the enabling of the vehicles, additional costs caused by the exceeding of maximum travel and penalty costs caused by the violation of time window constraints; and a simulated annealing hybrid genetic algorithm is adopted to optimize the current distribution path. According to the dynamic adjustment-based express delivery distribution optimization method of the invention, the current distribution path is optimized and dynamically adjusted according to the express delivery dynamic information, and therefore, the speed of express delivery distribution is improved, customer demands can be quickly responded, the distribution costs of an enterprise can be decreased, the utilization rate of the vehicles can be improved, urban traffic congestion can be reduced, and the operation efficiency of express delivery business can be benefitted.

The invention provides a crude oil blending scheduling method for crude oil blending multi-period optimization, belonging to the technical field of various crude oil blending. The method is characterized in that the mathematic model of the problem is induced; aiming at the non-linear mixed integer programming model induced from the problem, satisfactory solution of the problem is obtained by a high-effect mixed solving strategy. The method of the invention has the advantages that (1) the proposal takes improving the stability of the blending crude oil property as a main object, and takes improving the expected yield of the products as an object at the same time, can reduce the effects of excessively large fluctuation of blending crude oil property on the stability of distillation devices and subsequent devices of the distillation devices, and increase the expected yield of the products to a certain degree; (2) an algorithm structure of solving discrete decision variables and continuous decision variables by layers is adopted, thus improving the problems that the algorithm has low efficiency and poor searching performance, etc. which are caused by that the two groups of variables are optimized at the same time.

a method and apparatus is disclosed for scheduling construction projects based on the available finance using integer programming. This method renders CPM/PERT schedules of construction projects executable using bank overdrafts of specified credit limits. Conveniently, the method is organized in three stages; input preparation, schedule extension, and model formulation. Input preparation stage supports preparing CPM/PERT schedule and financial data of the project. Schedule extension stage supports developing a scheme for schedule extension. The scheme is a framework of the original schedule that allows a definite extension increment in the critical path of the CPM. Model formulation stage supports building an integer programming model for the scheme and involves the components of formulating an objective function, setting constraints, and searching for a model solution. The model solution determines the activities' shifts that fulfill the constraints of the specified credit limit while minimizing the schedule extension. A search for a solution of the model is performed. If no solution is found, a repetition of the last two stages of the method is performed after allowing longer extension increment.

The invention discloses a modeling optimization method based on a multilayer shuttle vehicle automatic storage system. The modeling optimization method includes the steps that the motion law of elevators and shuttle vehicles as well as various sorts of service time in the operating process of the elevators and the shuttle vehicles are determined; the number of layers of the multilayer shuttle vehicle automatic storage system, the depth of a roadway, the height of each single-layer storage rack, the width of each single cargo box, the speed and accelerated speed of each elevator, the speed andaccelerated speed of each shuttle vehicle, the cargo collecting and putting time at a time and the delivery task detailed information parameters are extracted, and a mathematical model of the multilayer shuttle vehicle automatic storage system is established; a mixed integer programming model by using obtainment of the shortest cargo collecting total time as the target is established; and a GUROBIlinear programming solver is used for solving the mixed integer programming model, and accordingly the shortest cargo collecting total time and the optimal cargo collecting sequence of the system canbe obtained. By adoption of the modeling optimization method, the system performance under various storage racks and equipment configurations can be estimated quickly, and decision support is provided for accurately designing the system, increasing the equipment utilization rate and reducing the operating cost.

The invention discloses an electric logistics vehicle scheduling method and an electric logistics vehicle scheduling system with a time window. The method comprises the steps of acquiring a distribution parameter of an electric logistics vehicle, and establishing a mixed-integer programming model according to the distribution parameter; acquiring a programming constraint parameter of the electriclogistics vehicle, and determining a programming constraint condition of the mixed-integer programming model according to the programming constraint parameter, wherein the programming constraint condition includes a programming requirement constraint condition and a charging constraint condition; performing optimal calculation on the mixed-integer programming model by use of an adaptive neighborhood search algorithm and a simulated annealing algorithm in combination with the programming requirement constraint condition and the charging constraint condition to obtain distribution path information; and completing optimization of electric logistics vehicle scheduling according to the distribution path information. According to the electric logistics vehicle scheduling method and the electriclogistics vehicle scheduling system with the time window, the distribution path of the electric logistics vehicle can be reasonably arranged to complete scheduling, the efficiency for a cargo distribution service is improved by virtue of the electric logistics vehicle, the electric energy is saved and the pollution to an environment is further reduced.

An Identification method for intelligent distribution network topology based on synchronous phasor measurement, which comprises the following steps of: 1) acquiring node quantity and number of a powerdistribution network, and inputting a termination condition parameter; 2) acquiring the measuring data of the synchronous phasor measurement device; 3) constructing a sensing matrix so that the linenumber of the power flow Jacobin matrix m=1; 4) calculating a voltage correlation coefficient vector; 5) iteratively solving the least squares estimation problem until the termination condition is satisfied; 6) judging whether the estimation of all the rows of the Jacobin matrix is finished, if yes, then entering into the step 7), otherwise m=m+1, then returning to the step 4); 7) constructing a topological identification 0 and1 integer programming model; 8) solving 0 and 1 integer programming model to obtain the network topology of the distribution network. The invention realizes the accurateidentification of the power distribution network topology based on the measurement information completely to avoid the dependence of the estimation problem on the line parameters and effectively reduce the error identification result caused by inaccurate line parameters.

The invention discloses a workflow application flexible resource supplying method in a cloud environment. A demand-based charging model based on a time interval, data transmission time, virtual machine starting time and software mounting (downloading) time are considered. The multi-rules based heuristic (MRH) method mainly includes the steps that A, deadlines of sub-tasks are divided, and the step A is mainly characterized in that through removing the constraint from the original problem that charging is performed according to the time interval, the original problem is simplified, then the integer planning model of the problem is solved, and therefore the deadlines of all the sub-tasks are obtained; B, according to a multi-rules based sub-task and virtual machine time slot matching method, the step B is mainly characterized in that three priority rules considering multiple factors are provided, and the tasks are matched with suitable virtual machine available time slots. Through the appropriate sub-task deadline division and the multi-rules based time slot matching method, the resource rent cost for a whole workflow application is greatly lowered.

The invention relates to a method for deployment and location selection of charging piles based on a 0-1 integer programming model with the aim of solving defects in the prior art. The technical scheme of the method for deployment and location selection of charging piles based on the 0-1 integer programming model is characterized by comprising following steps: step 1, collecting traffic flow of a target region; step 2, calculating average traffic flow of electric cars per day of each target region, calculating the charing efficiency of each target region at each position and obtaining the number of charging files needed to be constructed according to traffic flow and charging probability of each target region; step 3, finishing analyzing the 0-1 integer programming model by means of a 0-1 coverage model on the basis of the number of charging piles needed to be constructed at all target regions; step 4, orderly selecting locations and deploying charging files from high to low based on the evaluation value of Yi.

An embodiment of the invention provides an energy-saving method in a software defined network and an energy-saving control device. The method comprises the steps of utilizing the energy-saving control device to construct an expanded network which can visually display connection relations of links, single plates and a router according to an original network, establishing an energy-saving optimized 0-1 integer programming model of all inspected factors by mathematical abstraction on the basis of the expanded network, and adopting a elicitation type solving method when solving the integer programming model rather than software solving. Therefore, the computing convergence speed is improved, the total of the single plates used in the network is reduced through the integer programming model simultaneously, the energy-saving control device enables the unused single plates to sleep according to the use conditions of every single plate in the network, the energy effective utilization rate is improved, and total energy consumption of the network is reduced.

The invention relates to a pumped storage power station characteristic accurate simulation method for optimized operation of a wind power contained power grid system. The pumped storage power station characteristic accurate simulation method comprises the steps of: modeling a wind curtailment state of the wind power contained power grid system into a wind curtailment state linear function related to a binary variable; modeling relevant operating states of all pumped storage power stations in the system into a power station operating state linear function related to the binary variable on the basis of the binary variable; constraining the system through the combination of the two linear functions; and simulating output states of the pumped storage power stations when the system is in the wind curtailment state. The pumped storage power station characteristic accurate simulation method has the beneficial effects of conducting linear modeling on the situation that power generation by releasing water is forbidden by the pumped storage power stations when the system is in the wind curtailment state so that a model made by a power grid annual operating plan accurately considering pumped storage power station characteristics is still a mixed integer programming model, ensuring solving efficiency of the mode, being more inline with the actual power system dispatching condition and the actual operation conditions of the pumped storage power stations, and being capable of providing most intuitive judgment basis for dispatchers through calculation results.

The invention provides a mobile assistance WSNs routing method based on unequal clustering, comprising an initial phase, a clustering phase, an RPs (rendezvous points) determining phase and a routing phase. The initial phase is a network deployment phase and determines the movement track of a sink. The clustering phase considers factors such as the distance gradient between a point and a mobile sink, the rest energy of a candidate cluster head, etc. The RPs determining phase discusses the selection number and width of an RPs set, and specific sets, and simplifies a 0-1 integer programming model specific to the selection problem of an RP salve cluster head point set, wherein an approximately optimal RPs slave point set of an integer programming solution is obtained through a genetic algorithm. The routing phase employs multiple levels of routing, wherein the cluster head collects cluster member message data (including data fusion) and plays the role of a relay point, and PRs buffer messages transmitted by cluster head points into the mobile sink.

Online shopping optimization in this context means, in general, making the optimal business decisions with regard to an online or electronic commerce purchase. The method begins with extracting buyer's demand information from buyer-specified items or a previously-configured shopping cart. It then includes a product catalog search that, when provided with the items specified or selected by the buyer, returns exact or equivalent (i.e., replacement or substitute) items. With the catalog search results, the online shopping optimization method formulates the online shopping decision-making problem into a mathematical programming model, particularly a mixed integer programming model. The method optimally decides, from the universe of vendors and items within the system: 1) from which of the various vendors to buy, 2) what identical, replacement, or substitute items to buy, 3) what package sizes of these items to buy, and 4) how many of each item to buy. To summarize, the system systematically and quantitatively makes decisions for a buyer over various cataloged items in order to maximize or minimize an objective function subject to various constraints including the buyer's demands of the desired items, the minimum order requirements imposed by the vendors on the buyer's spent monetary amount, together with other types of buyer, vendor, buyer-and-vendors interrelationship, or among-vendors interrelationship constraints. Recommended optimized shopping carts are then presented to the buyer.

The invention discloses a single-frequency network radar multi-target tracking method. The method comprises a measurement interconnection module and a sequence tracking module. The measurement interconnection includes selecting a certain number of measurement and sending-receiving pairs to build low-dimensional association assumptions for association, quickly determining all of the association assumptions to remove incorrect association assumptions as for as possible, sorting association assumptions accepted in the last step, and solving to obtain second measurement after measurement interconnection on the basis of an overall association 0-1 integer programming model built according to sorted data in a single-frequency network. The sequence tracking is achieved based on the second measurement through Kalman filtering. The single-frequency network radar multi-target tracking method can be used for solving association fuzziness of measurement, a transmitting station and a target of a radar in the single-frequency network, greatly reduces the computation complexity by combining a heuristic method and an optimization model, achieves the multi-target tracking performance close to the known case of the association relationship and has popularization and application values.

The invention discloses a transfer robot picking task scheduling method for a movable goods shelf warehousing system, and belongs to the field of electronic commerce. The method comprises the following steps of constructing a picking task allocation and robot transfer sequence planning model with the minimum picking completion time of all orders as a target; and inputting information such as to-be-picked goods shelf information associated with all customer orders, time information about time required for replacing two goods shelves by a transfer robot, time information for manual picking of the goods shelves on a picking table, a determined time interval, and the number of the transfer robots and the picking tables into the picking task allocation and robot transfer sequence planning model, and obtaining a picking task allocation and transfer sequence planning scheme of the transfer robot based on existing integer programming model solution software. According to the method, the technical scheme is simultaneously provided for the picking task allocation and service sequences of the transfer robot, the walking distance of the transfer robot is reduced, the total picking time is reduced, the optimization effect is achieved, and the working efficiency of the movable goods shelf warehousing system is improved.

The invention relates to the technical field of power systems and automation thereof, and particularly relates to a virtual power plant double-layer optimization model considering network constraints.The method comprises the specific steps of establishing an upper-layer virtual power plant profit maximization model, establishing a lower-layer market clearing model considering network constraints,converting the double-layer optimization model into a mathematical programming model with balance constraints, and converting the mathematical programming model with the balance constraints into a mixed integer programming model. In order to overcome the defect that line transmission power constraint is not considered in current related research, internal optimization of the virtual power plant and interaction with a market operator and other conventional units are fully considered, a market bidding optimization model in which the virtual power plant participates is established, an optimization bidding strategy is generated under the condition that line power transmission is blocked, the superiority of the bidding strategy is embodied, the profit of the virtual power plant is improved, and the model is close to the practical situation. Scientific theoretical support is provided for the virtual power plant to effectively participate in the power market in future.

The invention discloses a shared bicycle parking device delivery quantity calculation method. Without considering man-made shared bicycle scheduling, layout parameters are set according to the numberof parked shared bicycles. On the basis of satisfying a certain degree of parking demand, the minimum delivery cost and space cost function are taken as goals to construct an integer programming model. The delivery number of shared bicycle parking devices at a planned place is determined. According to the method provided by the invention, under the premise of satisfying the parking demand of bicycles, the governance cost of the problem of shared bicycle chaos is reduced, and the road space utilization rate is improved; and the method facilitates the long-term sustainable development of sharedtransportation.

The invention discloses a modeling method for an island-division mixed integer programming model for an active power distribution network. The modeling method comprises the steps of establishing a target function of the island-division mixed integer programming model for the active power distribution network; establishing a branch current power flow constraint by taking a current real part and a current imaginary part as state variables, establishing a network topology reconstruction model, establishing a separation constraint model of the load switching state by dual-linear constraint and node injection current, and linearizing the quadratic component of the line current and the node voltage by a special order set 2; establishing a linearized power characteristic equation of a voltage-source inverter access type DG; establishing a linearized power characteristic equation of a doubly-fed induction-based wind generator; establishing a linearized power characteristic equation of a synchronous generator; and assembling the island-division mixed integer programming model for the active power distribution network by combination with the existing linearized constraint of the active power distribution network, and solving the island-division mixed integer programming model. The modeling method is capable of effectively lowering the solving complexity of the island-division of the power distribution network, and has the characteristics of high solving precision, high fitness, high engineering actual conformity, and the like.

The invention discloses an integrated scheduling method for a multi-roadway automatic stereoscopic warehouse based on a mixed integer programming model which comprises the steps that step 1, a tray/order arrives so as to perform step 2; if no tray/order arrives, performing the step 5; step 2, carrying out correlation analysis based on a K-Medoids clustering algorithm on arrived tray products making clustering analysis on arrived tray products, finding class clusters where tray products are located, solving an initial goods allocation range, wherein correlation analysis implementation process based on K-Medoids clustering algorithm is as follows: K-Medoids clustering algorithm is used for carrying out correlation analysis: step3, directly warehousing products ordered the same day and performing the step 6; if not, skipping to the step 4, directly warehousing products ordered the same day; step 4, stacking machine task distribution based on operation balance, step 5: distributing a sorting mode, and step 6: performing goods allocation and operation scheduling distribution; step 7, generating a stacking machine operation list until an optimal solution is not changed, otherwise, repeating the step 5 -step 7.

The invention discloses a running chart line addition optimization method based on a multi-target mixed-integer programming model in the high-speed railway operation management field. According to themethod, station line allocation, a departure time window of a departure station, a train stop scheme, acceleration/deceleration consumed time and other actual factors are comprehensively considered,simultaneous minimization of running time of newly added lines and adjustment amplitudes of existing lines is used as an optimization target, and running demands of the newly added lines and running demands of the existing lines are both considered. Through decomposition of an original large-scale problem in combination with a preprocessing algorithm, high-speed railway running chart line additioncan be efficiently realized.

The invention discloses a multi-size plate rectangular part optimal blanking algorithm for considering machinability, and relates to the technical field of rectangular part optimal blanking. The key points of the technical scheme are as follows: S1, constructing an integer programming model for machinability-oriented rectangular part optimal blanking; S2, adopting a blanking scheme generation algorithm: combining a value-corrected sequential heuristic algorithm with a layout mode generation algorithm, calling a GetPattern () function and a CorrectValue () function, and calculating the total cost of a blanking scheme according to a formula (2) in the integer programming model constructed in the step (1); and S3, analyzing an experiment result, comparing by adopting multiple groups of example experiments, and verifying the blanking scheme generation algorithm in the step S2. The processing process of related links in the blanking process is simplified and optimized conveniently, the actual production requirement is met, the blanking scheme has low cutting cost and good machinability while the high material utilization rate is maintained, the blanking efficiency is improved, and the blanking algorithm has important significance for long-term development of enterprises.

The invention discloses a workshop multi-row layout modeling and solving method. According to a workshop general layout, more constraint conditions are considered to establish a precise mathematical model conforming to an actual layout, and a genetic algorithm based on a hybrid coding technology is adopted to perform optimal solving. According to the method, first, based on a multi-row layout hybrid integer programming model, channels, spacing, horizontal and vertical placement and other actual factors are converted into constraint conditions to construct the precise mathematical model; second, by the adoption of the hybrid coding technology, a layout solution of a system arrangement method is embedded into an initial population of the improved genetic algorithm, reasonable parameter setting is performed, an appropriate operation strategy is selected, the algorithm is prevented from being trapped in a locally optimal solution, and search capability and efficiency are improved; and last, a more satisfying optimal layout solution is acquired after iterative optimization. By constructing the precise model and the solving method, an ideal workshop general layout which better conforms to engineering practice can be obtained.

The invention provides a vehicle scheduling and path planning method based on environmental protection and cost saving. Minimization of a fuel oil consumption quantity, a urea consumption quantity anda pollutant emission quantity is used as a planning goal to establish an integer planning model with time windows. According to the method, the fuel oil consumption quantity, the urea consumption quantity and the pollutant emission quantity are used as the goal to design a reasonable vehicle scheduling scheme for an enterprise through data which are input by the enterprise and of the number of and models of distribution-center vehicles, loadage of the vehicles, distribution-center and customer location information, time requirements of goods distribution, supply quantities and demand quantities of all points and priority levels of goods distribution, transportation costs of the enterprise are enabled to be reduced, pollution on environments is reduced at the same time, and sustainable social development is facilitated.

The invention relates to the technical field of logistics transportation, in particular to a battery swap station site selection and hybrid fleet path planning method and system. The method comprisesthe steps of obtaining alternative data information; constructing an integer programming model for joint decision of site selection of the battery swap station and distribution of the electric vehicleand fuel vehicle hybrid fleet; reconstructing the integer programming model into a main problem model and a sub problem model; for the model, an accurate branch pricing algorithm with an adaptive selection mechanism is designed, and seven acceleration solving operators are designed, so that adaptive calling of the operators for different enterprise distribution scenes is realized, and the solvingspeed is increased. And meanwhile, a precise label is adopted to expand a complete search solution space to obtain an optimal solution. The optimal distribution scheme and the optimal station building scheme can be quickly provided for large-scale hybrid fleet distribution systems of different enterprises under the condition of self-building a battery swap station, and real-time optimal scheduling of the enterprises is realized.

The invention discloses an LDPC code quadratic programming decoding method based on degree decomposition and an alternating multiplier method. The LDPC code quadratic programming decoding method mainly solves the problems of slow decoding speed in the existing LDPC code mathematical programming decoding and error floors existing in information transmission decoding. The implementation scheme of the LDPC code quadratic programming decoding method comprises steps of: firstly, performing equivalent transformation on maximum likelihood decoding of an LDPC code into a linear integer programming model based on a decomposition verification equation; secondly, adding a penalty term to an objective function of linear integer programming, and slacking the equivalent linear integer programming modelinto a secondary programming model; and establishing an augmented Lagrange function according to the secondary programming model, and carrying out iterative solution on the augmented Lagrange functionby adopting an alternating direction multiplier method to obtain decoded codes. Compared with the existing decoding method based on mathematical programming, the LDPC code quadratic programming decoding method improves the decoding efficiency. Compared with the traditional BP decoding, the LDPC code quadratic programming decoding method reduces the error floors, and can be applied to magnetic storage, optical fiber communication and satellite digital video.