Abstract: Example implementations relate to virtualized network function (VNF) placements. For example, VNF placements may include generating an initial mapping of a plurality of VNFs among a plurality of nodes of a network infrastructure, wherein the initial VNF mapping distributes each of a plurality of service chains associated with the plurality of VNFs to different top-of-rack switches. VNF placement may include generating an alternate VNF mapping of the plurality of VNFs among a portion of the plurality of nodes, wherein the alternate VNF mapping corresponds to a metric associated with node resource utilization and a particular amount of servers utilized by distributing the plurality of service chains according to the alternate VNF mapping. VNF placement may include placing the plurality of VNFs according to a selected placement from the initial VNF mapping and the alternate VNF mapping.

Abstract: Example implementations relate to virtualized network function (VNF) placements. For example, VNF placements may include generating an initial mapping of a plurality of VNFs among a plurality of nodes of a network infrastructure, wherein the initial VNF mapping distributes each of a plurality of service chains associated with the plurality of VNFs to different top-of-rack switches. VNF placement may include generating an alternate VNF mapping of the plurality of VNFs among a portion of the plurality of nodes, wherein the alternate VNF mapping corresponds to a metric associated with node resource utilization and a particular amount of servers utilized by distributing the plurality of service chains according to the alternate VNF mapping. VNF placement may include placing the plurality of VNFs according to a selected placement from the initial VNF mapping and the alternate VNF mapping.

Abstract: Examples of providing completion contracts are included. Completion contracts are offered for a request for cloud services. The completion contracts are continuous-decision based and have different prices and different durations to complete the request for cloud services.

Abstract: Example embodiments relate to net utility determinations based on product replacement and coverage decisions of a customer. In example embodiments, a number of net utility values corresponding to each possible product replacement decision and each possible coverage decision in each of a plurality of time periods is determined. An expected net utility attributable to the customer over the plurality of time periods is then determined based on the determined utility values.

Abstract: Link used variables are defined for links related to an interconnection fabric. The links used variables are representative of whether or not a link is used for handling flows between a plurality of hosts and devices. Constraints for links, and hop counts or port counts are also defined. An objective function is used by an integer programming solver to determine connections as a function of the definitions.

Abstract: A method performed by at least one processing system includes detecting that a purchaser of an item with a trade-in option has performed an action corresponding to the trade-in option using the processing system and modifying a trade-in option level of the purchaser using the processing system based on the action.

Abstract: As part of a sampling process, entities of a population are selected, where the population includes plural types of entities. Selecting the entities includes iteratively indicating in each of successive steps of the sampling process a corresponding type of the plural types of entities to select.

Abstract: Embodiments of the present invention are directed to selecting a portfolio. One embodiment of the present invention includes identifying a network comprising a source node, a target node, a first set of intermediate nodes that correspond to a set of objects from which a portfolio is selected, a second set of intermediate nodes, and a plurality of directed links. Also, the embodiment comprises initializing a network flow through the directed links and redistributing the flow through a subset of the plurality of directed links including directed links extending between the source node and the first set of intermediate nodes, between the first set of intermediate nodes and the second set of intermediate nodes. Further, the embodiment includes identifying members of the portfolio by determining which nodes of the first set of intermediate nodes have a network flow from the source node equal to or greater than a threshold value.

Abstract: Survey responses are received regarding user interest in offerings of plural different types based on proposed incentives for the offerings of the plural different types. An analysis of the survey responses is performed. The analysis includes deriving measures based on the survey responses regarding user interest in the offerings of the plural different types, and computing, based on the measures, an indication of profitability regarding a particular one of the plural different types of offerings. The indication of profitability to allow for a determination of whether to launch the particular type of offering.

Abstract: Systems, methods, and machine-readable and executable instructions are provided for profit comparison. Profit comparison can include determining a first profitability function of a flexible duration extended warranty offering with respect to a first plurality of warranty parameters and determining a second profitability function of a fixed duration extended warranty offering with respect to a second plurality of warranty parameters. Profit comparison can also include comparing the first function and the second function for at least one level of at least one of profit lift and flexible duration warranty offering coverage duration. Presenting results of the comparison for a range of values of the first and second plurality of warranty parameters can also be included in profit comparison.

Abstract: Systems, methods, and computer-readable and executable instructions are provided for pricing open-list warranties. Pricing open-list warranties can include determining an expected product support cost of a provider of an open-list warranty to a customer over a time period, determining an expected product repair cost of the customer over the time period, and pricing the open-list warranty for the time period based on the expected product support cost and the expected product repair cost.

Abstract: A maximum expected value of a residual value warranty for a product to a customer is determined. An expected cost to a provider to support the residual value warranty for the customer is determined, based on the maximum expected value of the candidate residual value warranty to the customer. The expected profitability of the candidate residual value warranty is determined based on the expected cost.

Abstract: Each product of a number of products is assigned to one of a number of popularity tiers. The popularity tiers are ordered from a most popular tier to a least popular tier. The popularity tiers indicate how popular the products are expected to be among consumers. Each product is assigned to one of a number of margin tiers. The margin tiers are ordered from a highest margin tier to a lowest margin tier. The margin tiers indicate how much money a retailer makes in selling the products to the consumers. Which of the products to offer for sale by the retailer to the consumers are selected by applying decision rules to the products as have been assigned to the popularity tiers and to the margin tiers.

Abstract: Systems, methods, and machine-readable and executable instructions are provided for making an extended warranty coverage. Making an extended warranty decision can include determining by a computer, a customer's expected cost of terminating the extended warranty coverage, determining, by the computer, the customer's expected cost of continuing the extended warranty coverage, and comparing, by the computer, the expected cost of terminating the extended warranty coverage and the expected cost of continuing the extended warranty coverage. Making an extended warranty decision can also include determining, by the computer, the extended warranty coverage decision based on the comparison.

Abstract: Systems, methods, and machine-readable and executable instructions are provided for profit comparison. Profit comparison can include determining a first profitability function of a flexible duration extended warranty offering with respect to a first plurality of warranty parameters and determining a second profitability function of a fixed duration extended warranty offering with respect to a second plurality of warranty parameters. Profit comparison can also include comparing the first function and the second function for at least one level of at least one of profit lift and flexible duration warranty offering coverage duration. Presenting results of the comparison for a range of values of the first and second plurality of warranty parameters can also be included in profit comparison.

Abstract: Link used variables are defined for links related to an interconnection fabric. The links used variables are representative of whether or not a link is used for handling flows between a plurality of hosts and devices. Constraints for links, and hop counts or port counts are also defined. An objective function is used by an integer programming solver to determine connections as a function of the definitions.

Abstract: Link used variables are defined for links related to an interconnection fabric. The links used variables are representative of whether or not a link is used for handling flows between a plurality of hosts and devices. Constraints for links, and hop counts or port counts are also defined. An objective function is used by an integer programming solver to determine connections as a function of the definitions.

Abstract: Systems, methods, and computer-readable and executable instructions are provided for designing warranty bonuses. Designing warranty bonuses can include determining, for a customer base of a product, a first probability that a customer will replace the product with a different product. Designing warranty bonuses may also include determining, for the customer base, a marginal contribution to the first probability for a plurality of warranty bonus sizes and a plurality of warranty bonus types. Designing warranty bonus can include determining, for the customer base, a second probability that the customer will purchase a warranty for the plurality of warranty bonus sizes and the plurality of warranty bonus types. Designing warranty bonuses may also include bundling the product and the warranty, and assigning a number of the plurality of warranty bonus sizes and a number of the plurality of warranty bonus types to the product-warranty bundle based on the first and second probabilities and the marginal contribution.

Abstract: Example embodiments relate to net utility determinations based on product replacement and coverage decisions of a customer. In example embodiments, a number of net utility values corresponding to each possible product replacement decision and each possible coverage decision in each of a plurality of time periods is determined. An expected net utility attributable to the customer over the plurality of time periods is then determined based on the determined utility values.

Abstract: A method (200) of eliciting customer preference from purchasing behavior surveys clusters (210) survey respondents into two or more clusters according to a data pattern identified in a dataset (330) of responses to survey questions that include a question regarding a product purchasing decision, and questions regarding respondent attributes (such as behavioral questions) and product attributes. Clustering (210) may be performed based on responses to behavioral questions that are not endogenously linked to any control variables. A model for each cluster, relating purchasing decision responses to product attribute responses, is produced (220), and each model is used to generate (230) projected purchasing decision responses for each cluster by replacing a value relating to a response to a selected product attribute question, which may be a control variable, with an alternative value. The dataset is transformed (240) by replacing purchasing decision responses with the projected responses.