摘要:
A maintenance data collector may be used to collect maintenance data characterizing maintenance events associated with maintaining operations of a plurality of components, and a critical component identifier may be used to identify, from the plurality of components and based on the maintenance data, critical components that contribute disproportionately to production losses caused by the maintenance events. A causality analyzer may then determine causal connections between the maintenance events, based on operational dependencies between pairs of the plurality of components, and a maintenance policy generator may generate a maintenance policy governing future maintenance events for the plurality of components, based on the identified critical components and the causal connections.
摘要:
Disclosed herein are technologies related to infrastructure investment planning for short-term and long-term capacity demands. One or more of the described technologies involve solving rent-or-buy optimization for real world infrastructure investment planning. Such technologies utilize forecasting, predictive analysis and dynamic programming. This Abstract is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims.
摘要:
Disclosed herein are technologies for providing recommendations as to particular products and/or services that are customer specific and general, based on customer preference and inquiry. The recommendations are provided as part of an online shopping system. In accordance with one aspect, an item query is received from a customer, and analyzed by a query analyzer to determine if the query is a general item query or a specific item query. A search may be performed for items based on the item query in an items database listing items offered for purchase. If the query is the general item query, customer preference is determined from results of the search. If the query is the specific item query, the items from the results of the search are grouped based on cost performance. The items of the search result are ranked and provided to the customer.
摘要:
Disclosed herein are technologies for demand management by providing a real time prediction model, using an elasticity matrix to quantify price change and demand, group customers based on their demand, set pricing per each group of customers, and optimize distribution. This Abstract is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims.
摘要:
Disclosed herein are technologies related to an optimization of project resource management of projects having multiple resource types and cost structures. One or more the technologies involves optimizing a project based, at least in part, on project data and related resource data using successive genetic operations and evaluations and further producing a resource-acquisition plan for the optimized project.
摘要:
According to an aspect, a system includes transportation module configured to generate a transportation plan for packages scheduled to be routed through a regional logistics network such that the transportation plan minimizes transportation costs. The transportation module may include a pickup plan module, a depot-to-depot plan module, and a delivery plan module. The pickup plan module may be configured to compute a pickup transportation plan for packages to be picked-up from the customers in the customer area of an origin depot. The depot-to-depot plan module may be configured to compute a depot-to-depot transportation plan for packages transferred between the origin depot and a destination depot. The delivery plan module may be configured to compute a delivery transportation plan for delivering packages from the destination depot to the customers within the customer area of the destination depot.
摘要:
Disclosed herein are technologies for facilitating placement of charging stations. In accordance with one aspect, sensor data of electric vehicles is received. A charging demand distribution over a set of locations is determined based on the sensor data. Candidate locations are selected from the set of locations based on the charging demand distribution. Placement of charging stations at one or more of the candidate locations is then optimized.