Abstract: According to one embodiment, a method, computer system, and computer program product for probabilistic inference from imprecise knowledge is provided. The embodiment may include identifying a knowledge base of one or more statements and first probability distributions corresponding to each of the one or more statements. The embodiment may also include identifying one or more queries. The embodiment may further include determining logical inferences about and second probability distributions for queries from the one or more queries or statements from the one or more statements based on information in the knowledge base.

Abstract: A system for configuring and using a logical neural network including a graph syntax tree of formulae in a represented knowledgebase connected to each other via nodes representing each proposition. One neuron exists for each logical connective occurring in each formula and, additionally, one neuron for each unique proposition occurring in any formula. All neurons return pairs of values representing upper and lower bounds on truth values of their corresponding subformulae and propositions. Neurons corresponding to logical connectives accept as input the output of neurons corresponding to their operands and have activation functions configured to match the connectives' truth functions. Neurons corresponding to propositions accept as input the output of neurons established as proofs of bounds on the propositions' truth values and have activation functions configured to aggregate the tightest such bounds.

Abstract: Methods, systems and computer program products for resource position planning are provided herein. A computer-implemented method includes generating a multi-commodity flow network for locations of a distributed service network over a planning horizon. The method also includes obtaining a set of candidate outage scenarios for the distributed service network, each of the set of candidate outage scenarios being associated with a corresponding probability of occurrence. The method also includes generating a resource positioning configuration for resources in the multi-commodity flow network utilizing an optimization model that reduces unmet demand for each of the set of candidate outage scenarios based at least in part on the probability of occurrence of each of the set of candidate outage scenarios.

Abstract: Methods, systems and computer program products for resource position planning are provided herein. A computer-implemented method includes generating a multi-commodity flow network for locations of a distributed service network over a planning horizon. The method also includes obtaining a set of candidate outage scenarios for the distributed service network, each of the set of candidate outage scenarios being associated with a corresponding probability of occurrence. The method also includes generating a resource positioning configuration for resources in the multi-commodity flow network utilizing an optimization model that reduces unmet demand for each of the set of candidate outage scenarios based at least in part on the probability of occurrence of each of the set of candidate outage scenarios.

Abstract: Booking information including destination and origin and specifying a desired multi-modal freight shipment is obtained from a user; based on same and on route information from a carrier database, a plurality of feasible multi-modal routes for the desired freight shipment are generated with a route enumeration module. Based on cost information from the carrier database, cost for each of the feasible multi-modal routes is computed with a cost estimation sub-module of a metric computation module. Based on transit time information from the carrier database, transit time for each of the feasible multi-modal routes is computed with a transit time estimation sub-module of the metric computation module. Based on the cost for each of the feasible multi-modal routes and the transit time for each of the feasible multi-modal routes, multi-objective optimization under uncertainty is carried out with an optimization module, to obtain one or more preferred feasible multi-modal routes.

Abstract: Booking information including destination and origin and specifying a desired multi-modal freight shipment is obtained from a user; based on same and on route information from a carrier database, a plurality of feasible multi-modal routes for the desired freight shipment are generated with a route enumeration module. Based on cost information from the carrier database, cost for each of the feasible multi-modal routes is computed with a cost estimation sub-module of a metric computation module. Based on transit time information from the carrier database, transit time for each of the feasible multi-modal routes is computed with a transit time estimation sub-module of the metric computation module. Based on the cost for each of the feasible multi-modal routes and the transit time for each of the feasible multi-modal routes, multi-objective optimization under uncertainty is carried out with an optimization module, to obtain one or more preferred feasible multi-modal routes.

Abstract: Determining a routing of vehicles for pickup and delivery in a supply chain network, in one aspect, may include generating a plurality of candidate set of routes for vehicles for pickup and delivery to meet demand at multiple target locations. Unsatisfied demand at said multiple target locations resulting from completing pickup and delivery according to the generated plurality of candidate set of routes may be determined. A set of vehicles routes are selected from said plurality of candidate set of routes that minimizes said unsatisfied demand across all said multiple target locations by applying an optimization function.

Abstract: A method for obtaining mask and source patterns for printing integrated circuit patterns includes providing initial representations of a plurality of mask and source patterns. The method identifies long-range and short-range factors in the representations of the plurality of mask and source patterns, and provides a plurality of clips including a specified number of mask patterns. Short-range factors having overlapping ranges for each of the clips are specified. The method includes determining an initial processing priority for the plurality of clips, and determining a patterning relationship between integrated circuit patterns and the mask and source patterns. A primary objective is determined which expresses the printability of the integrated circuit patterns in terms of the patterning relationship.

Abstract: A method for obtaining mask and source patterns for printing integrated circuit patterns includes providing initial representations of a plurality of mask and source patterns. The method identifies long-range and short-range factors in the representations of the plurality of mask and source patterns, and provides a plurality of clips including a specified number of mask patterns. Short-range factors having overlapping ranges for each of the clips are specified. The method includes determining an initial processing priority for the plurality of clips, and determining a patterning relationship between integrated circuit patterns and the mask and source patterns. A primary objective is determined which expresses the printability of the integrated circuit patterns in terms of the patterning relationship.

Abstract: A method of scheduling delivery of at least one of goods (e.g., repair parts) and services (e.g., repair services) includes inputting a performance objective (e.g., a plurality of performance objectives), and network data pertaining to a network of mobile points, and generating (e.g., by utilizing the input network data and the performance objective) a delivery schedule for a delivery vehicle (e.g., one or more delivery vehicles) to deliver the at least one of the goods and services.

Abstract: A method for finding fast approximations to an optimal operational state of a physical system, using an iterative procedure for converging to a solution of a Linear Program and yielding, in addition to a lower bound for an optimal cost and an approximation to the dual variables, a value representing an optimal allocation of system resources.