Abstract: Assignment scheduling for service projects, in one aspect, may comprise preparing input parameter data for servicing a client service request; generating a schedule for servicing the client service request by executing an optimization algorithm with the input parameter data; determining whether the schedule is acceptable by the client; and repeating automatically the preparing, the generating, the transmitting and the determining until it is determined that the schedule is acceptable by the client, wherein each iteration automatically prepares different input parameter data for inputting to the optimization algorithm and generates a different schedule based on the different input parameter data.

Abstract: A method and apparatus to determine: (a) the likelihood and timing for a sales opportunity to become a sale based on analytical models that incorporate the history of sales stage evolution and other covariates; and (b) the expected number of sales from invisible opportunities prior to a target date. Additionally, the method and apparatus is configured to predict an expected amount of revenue and/or an amount of resources given a current sales history.

Abstract: A computer searching technique identifies high quantitative patterns in data. A spatial indexing technique, such as an R-tree is used to represent the data. Then a pattern searching algorithm is used to identify anchor points that define the componentwise minimum patterns. High quantitative patterns are found responsive to the componentwise minimum patterns. The search strategy is demonstrated relevant to the problem of finding suitable locations for a retail business with reference to environments of prior successful retail businesses.

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: An embodiment of the invention provides a method for service management, wherein resources that have performed tasks in at least two of a first category, a second category, and at least one additional category are identified. A plurality of correlation sums are determined where the correlation sum includes at least two categories, wherein the correlation sums are added together to produce a correlation value. A correlation product for each correlation sum is calculated based on the respective correlation sum and the number of resources that have performed tasks with respect to the correlation sum. A quotient is calculated for each correlation sum based on the respective correlation product and the correlation value. The categories are grouped into clusters with a clustering module based on the quotients; and, resources are associated with the clusters based on task performance history of the resources.

Abstract: An embodiment of the invention provides a method for service management, wherein resources that have performed tasks in at least two of a first category, a second category, and at least one additional category are identified. A plurality of correlation sums are determined where the correlation sum includes at least two categories, wherein the correlation sums are added together to produce a correlation value. A correlation product for each correlation sum is calculated based on the respective correlation sum and the number of resources that have performed tasks with respect to the correlation sum. A quotient is calculated for each correlation sum based on the respective correlation product and the correlation value. The categories are grouped into clusters with a clustering module based on the quotients; and, resources are associated with the clusters based on task performance history of the resources.

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: 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 the 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(?)]2+[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.

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 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 the 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(?)]2+[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.

Abstract: A system, method and computer program product for providing the ability for retailers to devise a current channel strategy (e.g., adaptive price setting) that considers competitors in a dynamic competing environment, and that enables computing a competitive advantage of a channel. To estimate a price for selling a product j in a commerce channel comprises: a) receiving, at a processor device, real market data including sales and price history data of a product j sold by one or more retailers over one or alternate sales channels t; generating, by the processor device, a competitive advantage parameter value based on the sales and price history data; and, computing, utilizing the competitive advantage parameter value, an optimum price for a particular product to be marketed in one of the one or alternate sales channel.

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 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 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 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: 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 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 for predicting sales for a new store in a certain geographical area is disclosed, the method comprising geographic and non-geographic information and customer segmentation in the area to estimate sales and optionally the impact on existing competitor stores.

Abstract: A computer searching technique identifies high quantitative patterns in data. A spatial indexing technique, such as an R-tree is used to represent the data. Then a pattern searching algorithm is used to identify anchor points that define the componentwise minimum patterns. High quantitative patterns are found responsive to the componentwise minimum patterns. The search strategy is demonstrated relevant to the problem of finding suitable locations for a retail business with reference to environments of prior successful retail businesses.

Abstract: A system, method and computer program product for providing the ability for retailers to devise a current channel strategy (e.g., adaptive price setting) that considers competitors in a dynamic competing environment, and that enables computing a competitive advantage of a channel. To estimate a price for selling a product j in a commerce channel comprises: a) receiving, at a processor device, real market data including sales and price history data of a product j sold by one or more retailers over one or alternate sales channels t; generating, by the processor device, a competitive advantage parameter value based on the sales and price history data; and, computing, utilizing the competitive advantage parameter value, an optimum price for a particular product to be marketed in one of the one or alternate sales channel.