89 results about "Constraint satisfaction" patented technology

A method is provided for scheduling a meeting. The method includes receiving a request from an organizer to schedule a meeting, executing a constraint satisfaction algorithm to determine at least one meeting data set comprising a value for at least one variable in a set of variables. The meeting data set defines at least one of a proposed time, room or participants for the meeting. Executing the constraint satisfaction algorithm involves performing a backtracking search within a solution domain to determine the meeting data set for the set of variables that satisfies a set of meeting constraints. If no meeting data set is determined, the set of variables and the solution domain can be revised. A next backtracking search can be performed to determine the meeting data set for the revised set of variables in the revised solution domain that satisfies one or more of the meeting constraints.

A computer-implemented method for solving a constraint satisfaction problem (CSP), which is defined by variables and constraints applicable to the variables, and which has states corresponding to respective sets of values of the variables. The method includes assigning cost functions to the constraints so that the states have respective costs determined by application of the cost functions to the respective sets of values of the variables, the respective costs defining a problem topography of the CSP having global extrema corresponding to solutions of the CSP. The constraints of the CSP are reformulated so as to perform at least one of increasing a density of the solutions in the problem topography and smoothing a gradient of the problem topography. One or more of the solutions of the CSP are found by applying a stochastic CSP solver to the reformulated constraints.

The invention discloses a combined scheduling method of satellite-ground measurement and control resources of a low-mid-orbit satellite constellation based on orbit determination constraint satisfaction, and belongs to the field of combined scheduling of the satellite-ground measurement and control resources. The method comprises the steps of (1) building a visible geometry model, (2) building a visible link model, (3) building the constraint condition of orbit determination, (4) carrying out preprocessing, (5) determining a resource distribution principle, (6) building a combined scheduling model of the satellite-ground measurement and control resources, and (7) carrying out algorithm solution. Compared with the prior art, the method has the advantages that the scheduling result is reasonable, the scheduling process is efficient, and the scheduling method is high in universality. The air-and-ground-based integrated scheduling of the measurement and control resources is achieved. The transition from ground-based measurement and control to air-and-ground-based combined measurement and control in China is achieved.

Methods, systems and apparatus for modeling a target system includes defining a constraint satisfaction problem (CSP) that characterizes the target system in terms of a set of variables, each having a respective input domain, and initial constraints applicable to the variables. The variables are partitioned into at least first and second sets. An abstract solution is found to the CSP, including a given assignment of the variables in the first set. A reduced domain of at least one of the variables in the second set is computed, so as to be compatible with the abstract solution. A redundant constraint on the abstract solution is determined responsively to the reduced domain. A concrete solution to the CSP is then found, using the abstract solution and the redundant constraint.

A method and system for combining a feedback control and a feedforward control in a linear MPC to minimize effect of model uncertainty. An externally computed feedforward signal, which is more accurate and reliable, can be utilized in association with the MPC. A steady state relation between system parameters can be determined in order to compute the feedforward signal for a set of actuators associated with a non-linear system. A feedback MPC controller can then be designed. A state observer can be configured as an unknown input observer to estimate the effect of the feedforward signal. A strategy for manipulating the constraints of the MPC feedback signal can be implemented. A resulting control action for the actuators can be provided as a sum of corresponding feedback and feedforward signal while ensuring the constraints satisfaction.

In one embodiment, the invention includes sorting a set of constraints based on weights associated with each constraint, the constraints being capable of being satisfied based on values selected for corresponding associated parameters, selecting a constraint that is unsatisfied and that has the greatest weight, selecting parameters associated with the constraint and finding parameter values to satisfy the constraint, after satisfying the selected unsatisfied constraint, selecting a further unsatisfied constraint having the next greatest weight and finding values for associated parameters to satisfy the further constraint, and repeating the selecting of further constraints and the finding of values for associated parameters.

A facility providing systems and methods for managing and optimizing energy consumption and/or production is provided. The facility provides techniques for optimizing energy-consuming and energy-producing systems to meet specified demands or goals in accordance with various constraints. The facility relies on models to generate an optimization for an energy system. In order to use generic models to simulate and optimize energy consumption for an energy system, the generic models are calibrated to properly represent or approximate conditions of the energy system during the optimization period. After the appropriate models have been calibrated for a given situation using one or more modeling parameter sets, the facility can simulate inputs and responses for the corresponding system. The facility uses the generated simulations to generate a plan or control schedule to be implemented by the energy system during the optimization period.

A system and method for constraining generic types is disclosed. In brief, the subject invention provides a pattern type for defining a set of one or more parameter constraints. Rather than being confined to a predetermined set of hard-coded constraints in an execution engine, a pattern type can be specified as an extensible constraint mechanism for generic type parameters. According to one aspect of the invention, the pattern type can manifest itself as a class including one or more properties and/or features. The shape of the pattern type can then be compared or matched to instantiated type parameters to determine constraint satisfaction.

The invention discloses a self-adaptive large neighborhood search method for AEOS (agile earth observation satellite) scheduling. The method comprises following steps: Step 1, a constraint satisfaction model of AEOS scheduling problems is established; Step 2, an initial liquid is solved and taken as a current liquid; Step 3, adjustment is performed in a neighborhood of the current liquid: a deletion operator is selected, part of masks is deleted, and a destruction liquid is obtained; an insertion operator is selected, masks are inserted into the destruction liquid, and a new liquid is obtained; Step 4, the benefit of the new liquid is calculated and compared with benefits of the current liquid and an optimal liquid, and the current liquid and the optimal liquid are updated; Step 5, operator scores are updated according to operator performance; operator weights are updated after iteration is performed preset times each time; Step 6, the optimal liquid is output if an end condition is met, otherwise, the Step 3 is executed. Aiming at the time-dependent characteristic of the AEOS scheduling problems, the constraint satisfaction model of the AEOS scheduling problems is established by adopting the maximum observation benefit as a target, a liquid framework based on self-adaptive large neighborhood search is provided, and a conflict-free scheduling scheme is generated.

A method for automatically generating test programs includes receiving a description of a system under test, expressed in terms of variables associated with the system and conditional constraints including semantics applied to the variables, and receiving a definition of an event to be tested in the system. The method generates an ECondCSP over the variables responsively to the definition of the event and to the conditional constraints, such that at least some of the semantics of the conditional constraints are preserved in the ECondCSP when one or more of the variables to which the semantics are applied are inactive. The ECondCSP is solved to generate a test case for the system.

The present invention provides systems and methods that automate the presentation of e-content in a high quality, magazine-like manner, and are customizable to the taste of individual users and/or the audience.

The invention discloses a moving target single-satellite task planning method based on a constraint satisfaction genetic algorithm, which comprises the following steps of: firstly, calculating a visible time window according to model characteristics and constraints of a satellite and an observed target to form an initial task sequence; Secondly, constructing an objective function and a genetic algorithm model, and introducing a conflict elimination operator to calculate a conflict sequence; Thirdly, optimizing and solving the task sequence to obtain a conflict-free task sequence meeting the constraint; And finally, calculating a satellite task observation scheme and a satellite maneuvering angle. According to the method, the satellite earth observation efficiency can be improved, limited satellite resources are reasonably utilized, and the capture observation task of the moving target is completed.

The invention discloses a VERNA-genetic algorithm (GA) gasoline concoction optimized dispatching method. The VERNA-GA gasoline concoction optimized dispatching method comprises that first of all, a gasoline concoction dispatching model aiming at profit and constraint satisfaction is constructed according to information of blending component oil, product oil and market supply and demand under conditions of a concoction model with high prediction accuracy and production dispatching constraint, then a VERNA-GA method is adopted, wherein a calculation structure of the VERNA-GA method comprises operations of selection, cross and mutation of a main group and operations of infection, copy and deletion of a virus group, parameter set and searching and optimization of formula are carried out according to an algorithm parameter value range provided in the VERNA-GA gasoline concoction optimized dispatching method, and gasoline concoction optimized dispatching production is carried out according to the formula. The VERNA-GA gasoline concoction optimized dispatching method provides concoction optimized dispatching schemes for gasoline of one day and a plurality of days, is in no need of formula experience, when the formula is randomly searched in the production constraint range, the formula which is reliable in quality and high in profit can be rapidly found out, and operation and expansion of optimized dispatching scale are easy.

A method for automatically generating test scenarios for a plurality of business rules created to form a ruleset for a business domain. A plurality of decision variables is extracted from a business object model associated with the business domain using a computer system. The plurality of business rules is parsed using a syntactic parser operating on the computer system to extract at least one condition expression and an assignment action. A collection of mutually exclusive constraint satisfaction problems is built from the decision variables, condition expressions, and assignment actions using a constraint problem generator operating on the computer system. A plurality of test scenarios is generated automatically from each identified constraint satisfaction problem in the collection using a constraint solver engine operating on the computer system.

The invention discloses a medical personnel intelligent scheduling and emergency-processing method. The method comprises the steps of: scheduling intelligently according to various conditions of a problem after inputting information or reading existed information, wherein the information includes number of medical personnel, various requests of each medical personnel, contract limitation, shift covering requirements, shift distribution condition and distributed time length; and finally turning back to a nurse scheduling sequence, and giving a limitation satisfying condition and various performance indexes needed by the scheduling. The medical personnel intelligent scheduling and emergency-processing method, disclosed by the invention, has the advantages of solving the scheduling and dispatching problems well, having a practical significance for managing personnel, greatly lightening workload of a user, improving work efficiency of staff, bringing convenience for life of workers and even promoting the development of a new generation of management scheduling industry.

The invention discloses a voltage and power flow combined control method considering running cost for an active power distribution network. The method comprises the following steps of: (1) automatically detecting/forecasting voltage and power flow in the network, and judging whether an overrun phenomenon occurs or not; (2) building a case library applicable for voltage control of the active power distribution network; (3) retrieving the case library by a nearest neighbor method in a case-based reasoning when the voltage of arbitrary one bus in the power distribution network is recognized to exceed the limit by the system, and searching out N voltage control methods with highest similarity, wherein N is an integer more than 1; (4) calculating a power flow constraint method by a constraint satisfaction algorithm when the power flow of arbitrary one circuit in the power distribution network is recognized to exceed the limit value by the system; (5) carrying out on-line simulation test on the control method; and (6) optimizing the running cost. By the embodiment of the invention, the safety margin requirement for running of the power distribution network is satisfied in real time, and the running reliability and activeness of the power distribution network is effectively improved; and meanwhile, guidance is provided for running and short-term planning of the power distribution network, and favorable economic benefit and social benefit are achieved.

A method for solving a constraint satisfaction problem includes receiving a set of variables having respective input domains and a set of relations among the variables, and building a network of one or more hyper-arcs representative of the set of relations, each hyper-arc corresponding to one of the relations and linking nodes in the network corresponding to the variables that are subject to the relation. For each of the hyper-arcs, the variables are assembled in a hierarchy based on the relation corresponding to the hyper-arc. The input domains of the variables in the hierarchy are reduced, so as to determine respective output domains of the variables that are consistent with the relations.

A method and apparatus subsamples, in a constraint satisfying manner, an image for subsequent processing of the subsampled image. The subsampling is based on constraints provided for the subsequent image processing. A subsampling factor or pair of factors are determined for the image and the image is subsampled by the subsampling factor(s). The constraints comprise at least time constraints, uncertainty constraints, accuracy constraints or implementation constraints. When time constraints are given, the constraints specify a function of the time needed for the subsequent image processing along with at least a maximum and a minimum time that the subsequent image processing should take. When uncertainty constraints are specified, the constraints give a function of the uncertainty in the subsequent image processing and at least a maximum and a minimum uncertainty required from the subsequent image processing. When the constraints specify accuracy constraints, the constraints specify a function of the accuracy of the subsequent image processing at least a maximum and a minimum accuracy required from the subsequent image processing.

The invention discloses a PPI network comparison-oriented graph matching constraint solving symbol method. According to the method, a CSP model is established (a constraint condition with a shortest path is established) by utilizing a constraint relationship in a graph structure; by adoption of a graph-based backtracking algorithm, an OBDD symbol technology and each included symbol operation, theaim of solving subgraph isomorphism problems is achieved; and finally, the technology is imported in to a PPI network comparison problem, the problem is solved and a PPI network comparison-oriented graph matching constraint solving symbol technology is given. According to the method, the graph-based backtracking algorithm which is used for solving constraint satisfaction problems is combined, theOBDD symbol technology is adopted, advantages of an operation method are developed, and a graph matching symbol algorithm is applied to the protein mutual action network comparison problems in the field of biological information according to a constraint symbol solving technology which is used for solving sub-graph isomorphism, so that the problem solving efficiency can be improved to a certain extent and the state space complexity is reduced.