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: A method includes obtaining a demand specification specifying a plurality of multi-modal freight shipment scenarios, each of the multi-modal freight shipment scenarios including at least a destination and an origin, generating, with a booking tool, a plurality of feasible multi-modal routes for each of the multi-modal freight shipment scenarios using route information from a carrier database, determining a plurality of business compliant routes among the plurality of feasible multi-modal routes for each of the multi-modal freight shipment scenarios using a rules specification specifying different business rules for each of the multi-modal freight shipment scenarios, comparing the multi-modal freight shipment scenarios by the business compliant routes determined for each respective one of the multi-modal freight shipment scenarios, and identifying at least one business rule, among the different business rules, affecting an aggregate cost-savings using the comparison of the multi-modal freight shipment scenario

Abstract: A method includes obtaining a demand specification specifying a plurality of multi-modal freight shipment scenarios, each of the multi-modal freight shipment scenarios including at least a destination and an origin, generating, with a booking tool, a plurality of feasible multi-modal routes for each of the multi-modal freight shipment scenarios using route information from a carrier database, determining a plurality of business compliant routes among the plurality of feasible multi-modal routes for each of the multi-modal freight shipment scenarios using a rules specification specifying different business rules for each of the multi-modal freight shipment scenarios, comparing the multi-modal freight shipment scenarios by the business compliant routes determined for each respective one of the multi-modal freight shipment scenarios, and identifying at least one business rule, among the different business rules, affecting an aggregate cost-savings using the comparison of the multi-modal freight shipment scenario

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.