Abstract: Method, apparatus and system for location evaluation and site selection, capable of effectively configuring the site network and evaluating the facility location by scientifically modeling and incorporating human knowledge are provided. In one aspect, geographic and demographic data associated with a plurality of locations and human knowledge comprising partial rating knowledge and pair-wise preference knowledge are used in a regression algorithm to construct a location evaluation model. The regression algorithm is further refined using active learning that identifies a plurality of pairs of locations to improve precision of the regression algorithm.

Abstract: A data integration module is operable to integrate a plurality of data sources, a customer preference module builds a model representing preference to different channels in merchandise category for each customer segment. A customer satisfaction module creates a model representing customer satisfaction metrics. A joint multi-channel optimization module is operable to use an optimization model that utilizes the customer preference model and the customer satisfaction model and maximize retailer's profit and customer satisfaction.

Abstract: A method of forecasting workforce demand, includes forecasting an ongoing engagements demand, forecasting an opportunities demand, forecasting a wedge engagements demand, representing a result of the forecasting the ongoing engagements demand as a first workforce demand statement, a result of the forecasting the opportunities demand as a second workforce demand statement, and a result of the forecasting the wedge engagements demand as third workforce demand statement, and integrating the first workforce demand statement, the second workforce demand statement and the third workforce demand statement to generate an overall workforce demand forecast.

Abstract: A method, and system employing the method, for service channel reconfiguration at a service outlet includes generating service transaction data of a service outlet, generating queue management system (QMS) data of the service outlet, and generating cost and profit data for the service outlet. Data is extracted from the service transaction data and the QMS data relating to specified parameters including customer experience data, and customer demand data. The service transaction data and the QMS data is integrated with the cost and profit data providing a unified objective function. Stochastic service processes and customer behavior data are modeled. The unified objective function is evaluated using the stochastic service processes and customer behavior data model, and the service channel function of the service outlet is reconfigured using the unified objective function.

Abstract: System, method and computer program product for adjusting a representation of a merchandise hierarchy associated with an entity such as a retailer or wholesaler of products. Product correlation information discovered in that entity's customers' shopping records are obtained and incorporated into an existing merchandise hierarchy with a constraint on the consistency with the existing hierarchy.

Abstract: A system and method of determining at least one location for a retail outlet in a region are described. The system and method use clustering technology for partitioning the region into a fixed number of sub-regions. Then, the system and method compute marginal increments from input data for each sub-region. The system and method choose a sub-region having a maximal marginal increment for a location of a first retail outlet.

Abstract: A method and system for customer segmentation using adaptive spectral clustering may include determining initial segmentation labels, determining new customer behavior data, formulating a single objective minimization function that integrates the initial segmentation labels with the new customer behavior data, and determining best fit to both the initial segmentation labels and the new customer behavior data simultaneously by minimizing the single objective minimization function.

Abstract: A method and structure for dynamic allocation of servers to customers in a server farm which supports a flexible contract structure such that the total revenue of the farm is maximized. The invention creates a resource allocation plan based on a long term forecast for the server farm, taking into account traffic, number of servers, customers' contracts and revenue optimization algorithms. The plan is then modified as indicated by short term forecasting using currently monitored load metrics to reallocate to maximize revenue for particular time periods.

Abstract: A method and structure for dynamic allocation of servers to customers in a server farm which supports a flexible contract structure such that the total revenue of the farm is maximized. The invention creates a resource allocation plan based on a long term forecast for the server farm, taking into account traffic, number of servers, customers' contracts and revenue optimization algorithms. The plan is then modified as indicated by short term forecasting using currently monitored load metrics to reallocate to maximize revenue for particular time periods.

Abstract: A method and system for integrating multiple factors into a unified optimization model for retail network configuration, in one aspect, obtains input data for modeling store configuration. The input data may include demand of each merchandise category from each customer segment in each facility, geographic distribution of stores in an area, current revenue of stores, and physical cost of reconfiguring stores. A trade area is generated as a function of store location, store format, and store capacity. The method and system also generates trade area demand summation representing predicted total demand of all stores for all merchandise categories for all customer segments in the trade area, as a function of store location, store format, store capacity, merchandise category, and customer segment associated with the trade area. An objective function is constructed as a function of said trade area demand summation, current revenue of stores, and physical cost of reconfiguring stores.

Abstract: Method, apparatus and system for location evaluation and site selection, capable of effectively configuring the site network and evaluating the facility location by scientifically modeling and incorporating human knowledge are provided. In one aspect, geographic and demographic data associated with a plurality of locations and human knowledge comprising partial rating knowledge and pair-wise preference knowledge are used in a regression algorithm to construct a location evaluation model. The regression algorithm is further refined using active learning that identifies a plurality of pairs of locations to improve precision of the regression algorithm.

Abstract: A method and apparatus for end-to-end retail store one-stop site configuration integrates multiple data sources, identifying key customers, forecasting merchandise demand. Site configuration is formulated as a mathematical optimization problem with both in-store and external data as input to the problem whose solution provides proper suggestions for retail store transformation.

Abstract: A method of analyzing a spectrum of one-dimensional or multi-dimensional signal X(t) requires a number of steps including deriving coefficients [AN(?), BN(?)] of an Lp-norm harmonic regression of tie signal with 0<p?? and p?2, squaring the coefficients, summing the squared coefficients, and scaling the summed, squared coefficients with a constant c to realize a periodogram of X(t) as LN(?)=c{[AN(?)]+[BN(?)]2}. The method may include receiving the signal X(t), storing the received signal X(t), and outputting the periodogram LN(?). The method may still further include scanning to maximize the periodogram LN(?) by identifying its largest peak(s) and comparing the amplitude of the identified largest peak(s) with a threshold to determine if the largest peak(s) is(are) attributable to a presence of a periodic signal. The coefficients are preferable derived from a time series signal X(t), t=1, 2, . . . , N, but may include receiving a continuous-time signal and converting it to the time series signal.

Abstract: A method of forecasting workforce demand, includes forecasting an ongoing engagements demand, forecasting an opportunities demand, forecasting a wedge engagements demand, representing a result of the forecasting the ongoing engagements demand as a first workforce demand statement, a result of the forecasting the opportunities demand as a second workforce demand statement, and a result of the forecasting the wedge engagements demand as third workforce demand statement, and integrating the first workforce demand statement, the second workforce demand statement and the third workforce demand statement to generate an overall workforce demand forecast.

Abstract: A method and apparatus are disclosed for determining the best cluster of computing resources to handle each of a plurality of workloads by optimally grouping multiple workloads and determining the best resource cluster to handle each group.

Abstract: A workforce management tool includes an input section that receives data from one or more data sources that together reflect data of substantially an entirety of a workforce of an organization. A plurality of service modules receive and process the data in accordance with requirements of different segments of the organization. The plurality of service modules are interconnected so that a user in a segment of the organization can selectively view any data of the workforce tool that is related to that segment.

Abstract: A method and apparatus are disclosed for determining the best cluster of computing resources to handle each of a plurality of workloads by optimally grouping multiple workloads and determining the best resource cluster to handle each group.

Abstract: A method and structure for calculating a risk exposure for a disaster recovery process, including loading a user interface into a memory, the user interface allowing control of an execution of one or more risk models. Each risk model is based on a specific disaster type, and each risk model addresses a recovery utilization of one or more specific assets identified as necessary for a recovery process of the disaster type. One of the risk models is executed at least one time.

Abstract: A method and structure for dynamic allocation of servers to customers in a server farm which supports a flexible contract structure such that the total revenue of the farm is maximized. The invention creates a resource allocation plan based on a long term forecast for the server farm, taking into account traffic, number of servers, customers' contracts and revenue optimization algorithms. The plan is then modified as indicated by short term forecasting using currently monitored load metrics to reallocate to maximize revenue for particular time periods.