619 results about "Pareto optimal" patented technology

Server load-balancing operation-related data, such as data associated with a system configured for global server load balancing (GSLB) that orders IP addresses into a list based on a set of performance metrics, is tracked. Such operation-related data includes inbound source IP addresses (e.g., the address of the originator of a DNS request), the requested host and zone, identification of the selected “best” IP addresses resulting from application of a GSLB algorithm and the selection metric used to decide on an IP address as the “best” one. Furthermore, the data includes a count of the selected “best” IP addresses selected via application of the GSLB algorithm, and for each of these IP addresses, the list of deciding performance metrics, along with a count of the number of times each of these metrics in the list was used as a deciding factor in selection of this IP address as the best one. This tracking feature allows better understanding of GSLB policy decisions (such as those associated with performance, maintenance, and troubleshooting) and intelligent deployment of large-scale resilient GSLB networks.

Some embodiments implement systems and methods to monitor CDN performance from the end user's perspective. To achieve full end-to-end monitoring, the systems and methods monitor the performance of Anycast routing for routing an end user to the optimal PoP of the CDN and monitor the performance of different routes that deliver content from the optimally selected PoP back to the end user. Systems and methods are also provided to leverage the monitored performance in order to automatically optimize the performance of the CDN by optimizing or modifying Anycast routing and by performing route grooming as needed to ensure that the optimal route is selected to deliver content to different sets of end users that request content from a particular PoP.

Techniques are provided for reducing feedback while maintaining performance in a MIMO-OFDM system. The disclosed techniques employ finite-rate feedback methods that uses vector quantization compression. The disclosed methods/techniques generally involve: receiving a plurality of symbols from a plurality of sub-carriers at a receiver; selecting a plurality of indices of codewords corresponding to a codebook of pre-coding weighting matrices for the sub-carriers based on vector quantization compression of the codewords; and transmitting the selected indices over a wireless channel to a transmitter. Finite state vector quantization feedback makes use of a finite state vector quantizer (FSVQ), which is a recursive vector quantizer (VQ) with a finite number of states. In finite state vector quantization feedback, optimal precoding matrices (beamforming vectors) are selected sequentially across subcarriers. In a trellis-based feedback method, the optimal precoding matrices are selected at the same time for all subcarriers by searching for the optimum choice of matrices along a trellis using the Viterbi algorithm (dynamic programming).

To achieve optimal selection of new access points for mobile devices (10) being located in a mobile communication environment (14), according to the present invention there is provided a method of assisting handovers for a mobile device in a mobile communication environment. It is proposed to proactively deploy a handover decision mechanism in relation to a handover and in view of the operational context of the mobile device (10). This proactively deployed handover decision mechanism is then used to determine a new access point for the mobile device (10).

A method, computer program product, and information handling system for generating mixed-mode operations in the compilation of program code for processors having vector or SIMD processing units is disclosed. In a preferred embodiment of the present invention, program instructions making up the body of a loop are abstracted into virtual vector instructions. These virtual vector instructions are treated, for initial code optimization purposes, as vector instructions (i.e., instructions written for the vector unit). The virtual vector instructions are eventually expanded into native code for the target processor, at which time a determination is made for each virtual vector instruction as to whether to expand the virtual vector instruction into native vector instructions, into native scalar instructions, into calls to pre-defined library functions, or into a combination of these. A cost model is used to determine the optimal choice of expansion based on hardware/software constraints, performance costs/benefits, and other criteria.

The invention relates to a power distribution network double layer planning method considering the time sequence and the reliability. The method comprises: according to the meteorological files and the load power statistical data, obtaining the typical daily power time sequence curves of the wind electricity, the photovoltaic output and the load in different seasons; based on the opportunistic constraint planning method, creating a power distribution network framework and a distributed power capacity double layer planning mathematical model, including the objective function and the constraint condition; using the particle swarm optimization algorithm to solve the model and using the minimum spanning tree algorithm to ensure the radiation and connectivity structure of the distribution network during the iterative process; and obtaining the target network framework and the Pareto optimal solution set of the distributed power capacity so as to generate the best planning scheme. The invention solves the problems that unnecessary investment into the a power distribution network incurred by the fact that a traditional power distribution network planning method containing a distributed power supply cannot reflect the typical output characteristic of a distribution type new energy; and 2) that by incorporating the power distribution network power supply reliability into a model target function, the reliability target can be realized at the planning stage.

Selection of certain views of a multidimensional database to materialize may be accomplished using an efficient and effective solution. A set of all potential views may be stored in a structure. A path in the structure may then be traversed in an indicated direction through the structure, the path including two or more potential views and beginning at an indicated view. Then two or more immaterialized views in the path may be compared to each other to determine which immaterialized view is the optimum choice for maximizing benefit if selected to be materialized. Then the traversing and comparing may be continually iterated through, each iteration utilizing an indicated direction different than the last, each iteration also utilizing an indicated view set at the optimum choice determined by the last iteration, the iterating continuing until it converges on a single view. That single view may then be selected for materialization.

Disclosed are systems and methods of eliminating or reducing interference resulting from harmonics of local oscillator frequencies of mixers. In one embodiment, a determination is made as to a zone or zones in which harmonics result in undesired spur generation. Inter-tuner spurs and intra-tuner spurs may be identified such that frequency information of the identified spurs may be utilized to define a plurality of exclusion zones. LO frequencies may subsequently be efficiently selected in view of the exclusion zone information. Embodiments may also determine a score for identified spurs which may be used to optimally select from within a set of spur-generating local oscillator frequencies.

The invention provides a route planning method based on a multi-target glowworm swarm algorithm and belongs to the technical field of route planning. The method includes: modeling a route planning problem, initializing the multi-target glowworm swarm algorithm, updating the glowworm position, determining a non-inferior solution set, updating an external archived file, judging whether a preset maximum iteration number is achieved or not, and determining a Pareto optimal route. The basic glowworm swarm algorithm is improved based on the Pareto dominant conception, and global searching and parallel computing capacities of the glowworm swarm algorithm are well used. Multiple route performance indexes are considered simultaneously during planning, a group of Pareto optimal solution sets can be obtained by planning once, and high flexibility is achieved. Further, the route panning method is different from traditional route planning methods for a single target and route planning methods of using a weighing method to convert multiple targets into the single target, and can better meet practical requirements of route planning.

A multiobjective evolutionary algorithm unit feeds a set of parameters of an individual to a search history storage device in a fitness estimating unit and to an optimization target. The optimization target outputs a set of sampled values of fitnesses on the basis of the set of parameters of the individual. The search history storage device stores the set of parameters of the individual and a set of sampled values as a search history. The fitness estimating module computes a set of estimated values of true fitnesses on the basis of the search history stored in the search history storage device for output to the multiobjective evolutionary algorithm unit. The multiobjective evolutionary algorithm unit determines a Pareto-optimal population in accordance with a genetic algorithm on the basis of a plurality of sets of estimated values.

The invention discloses a high-rigidity and light-weight design method considering uncertainty of a slide block mechanism of a press machine. The high-rigidity and light-weight design method comprises the steps of: establishing a high-rigidity and light-weight design model considering the uncertainty of the slide block mechanism of the press machine; adopting an optimized Latin hypercube sampling method for a test design, obtaining a target function response value corresponding to each sample point through collaborative simulation and building a Kriging agent model; converting an uncertain target function into a certain target function based on an order relation of interval numbers; and calculating a target function interval by utilizing an internal structure analysis way, finding a Pareto optimal solution collection of a converted certain optimal problem by utilizing a multi-target genetic algorithm, if the precision requirement is not satisfied, performing important sampling at the place where the extreme value of the target function interval locates, and updating the target function sample collection and the agent model to perform iterative optimization. The high-rigidity and light-weight design method considering uncertainty of the slide block mechanism of the press machine, disclosed by the invention, has the advantages of establishing the uncertain optimization model of the slide block mechanism according with the practical project for solving and really realizing the light-weight and high-rigidity design of the slide block mechanism.

A system provides via multiple communications channels flexible nutritional counseling that encourages users to adhere to a sensible diet. The system may recommend a compliant meal having nutritional content that is within certain dietary parameters applicable to the user. However, the system may also recommend a non-compliant meal having nutritional content that is not within the dietary parameters, but is a sensible choice in view of constraints that make it impossible or infeasible to select a compliant meal. Thus, the system may recommend a meal that is not an optimal selection, but that is a best selection from among a set of non-compliant options. Accordingly, the user has flexibility to deviate from optimal choices as practically necessary or desirable. The user confirms meals actually consumed, and the system can account for an indulgence when recommending a next meal, and/or send a motivational message to the user encouraging compliant behavior.

Some embodiments implement systems and methods to monitor CDN performance from the end user's perspective. To achieve full end-to-end monitoring, the systems and methods monitor the performance of Anycast routing for routing an end user to the optimal PoP of the CDN and monitor the performance of different routes that deliver content from the optimally selected PoP back to the end user. Systems and methods are also provided to leverage the monitored performance in order to automatically optimize the performance of the CDN by optimizing or modifying Anycast routing and by performing route grooming as needed to ensure that the optimal route is selected to deliver content to different sets of end users that request content from a particular PoP.

The invention discloses a multi-target reactive power optimization method for an electric system, which belongs to the field of reactive power optimization for electric systems. The method includes: modifying the Memetic algorithm to adapt to multi-target optimization, applying the modified Memetic algorithm to the problem of multi-target reactive power optimization for the electric system, and working out a Pareto optimal solution of the multi-target problem; and judging whether algorithm convergence conditions are met or not, and if yes, completing optimization and outputting optimization results. The multi-target reactive power optimization method has the advantages that the algorithm for solving the problem of multi-target reactive power optimization is provided, the method is more suitable for solving the multi-target problem while giving play to existing advantages of the Memetic algorithm which integrates local searching and evolutionary computation and has high global search capacity and the like, and searching efficiency is improved while algorithm robustness is improved.

Price comparison sites on the Internet, which allow users to compare prices across multiple shops (or in other words allow shopping meta-search), are very popular today. However, these price comparison sites perform optimizations for only one item at a time but not for combinations of more than one item which can be purchased from more than one dealer. In other words, If the user wants to buy for example multiple books at the same time or for example a number of computer parts at the same time, he has to search for the best shop for each item separately, and then any attempt for example to optimize the shipping costs by aggregating more than one item from the same shop have to be done manually by the user, which can take quite a long time, and the user many times will not succeed to reach the best option or even close to it. The present invention describes a system and method for automatic finding of one or more acceptable or near-optimal suggestions for dividing the order between various vendors (preferably in terms of at least item prices plus shipment costs) in price-comparison sites when the user buys more than one product at the same time, preferably by using efficient and practical heuristics, and preferably with automatically offering additional complementary services when needed. The invention solves many problems that are involved in accomplishing this in an efficient and practical manner, and also describes additional preferable features.

System and processes for optimal selection of teeth for dentures based on the anatomical measurements and bite impressions of the patient. This information is applied in an iterative manner to rules that balance the anatomical and aesthetic considerations to select the best teeth for a patient. The system may also use this information in an iterative manner to rules that balance the anatomical and aesthetic considerations to design the optimal denture base for the patient as well.

The invention discloses a flexible job-shop scheduling multi-objective method. The specific implementation procedures of the flexible job-shop scheduling multi-objective method are that: establishing a model for a multi-objective flexible job shop; optimizing the model by using an ant colony algorithm, and evaluating the result to check whether the scheme is the optimal scheme; and improving a pheromone updating rule according to the optimal scheme, and increasing convergence rate of the algorithm to obtain a Pareto optimal solution of a multi-objective flexible job shop scheduling problem. Compared with the prior art, the flexible job-shop scheduling multi-objective method effectively reduces workshop production cost, shortens the processing time, improves qualified rate of products, is high in practicability, and is easy to popularize.

Concurrent Gradients Analysis (CGA), and two multi-objective optimization methods based on CGA are provided: Concurrent Gradients Method (CGM), and Pareto Navigator Method (PNM). Dimensionally Independent Response Surface Method (DIRSM) for improving computational efficiency of optimization algorithms is also disclosed. CGM and PNM are based on CGA's ability to analyze gradients and determine the Area of Simultaneous Criteria Improvement (ASCI). CGM starts from a given initial point, and approaches the Pareto frontier sequentially stepping into the ASCI area until a Pareto optimal point is obtained. PNM starts from a Pareto-optimal point, and steps along the Pareto surface in the direction that allows improving a subset of objective functions with higher priority. DIRSM creates local approximations based on automatically recognizing the most significant design variables. DIRSM works for optimization tasks with virtually any (small or large) number of design variables, and requires just 2-3 model evaluations per Pareto optimal point for the CGM and PNM algorithms.

The present invention relates in general to methods and systems for comparing and maximizing the optimal selection of a first set of one or more data objects to a set of second data objects. In one embodiment, the first set of data objects represent one or more tasks to be fulfilled by a set of capabilities represented by the second data objects. In one embodiment, methods and systems are provided that apply topic modeling and similarity metrics to determine the optimal selection. In one embodiment, methods and systems are provided to determine the appropriateness of a set of second data objects to satisfy the requirements of a first data object given interaction attributes. Embodiments may be used to compare mission requirements with potential team members to determine the appropriateness of team members and teams for a given mission based on interaction attributes of the team members and teams.

A method and associated system for multi-disciplinary optimization of various parameters associated with a space vehicle that experiences aerocapture and atmospheric entry in a specified atmosphere. In one embodiment, simultaneous maximization of a ratio of landed payload to vehicle atmospheric entry mass, maximization of fluid flow distance before flow separation from vehicle, and minimization of heat transfer to the vehicle are performed with respect to vehicle surface geometric parameters, and aerostructure and aerothermal vehicle response for the vehicle moving along a specified trajectory. A Pareto Optimal set of superior performance parameters is identified.