Non-linear systems and methods for destination selection
First Claim
1. A method for machine-based dynamic reallocation of a plurality of resources among a plurality of destinations to globally optimize total cost in event planning, the method comprising:
- receiving from a user at an interactive user interface;
a selection of a plurality of geographically different resources; and
a specification of a number of destinations;
using a processor;
clustering the plurality of geographically different resources into a plurality of clusters of proximate resources, the number of clusters equal to the number of destinations;
calculating a cost of transporting each resource to each of the destinations and storing the costs in machine-readable memory, referenced by resource and destination;
mapping each cluster to a respective one of the destinations to determine, based at least in part on the costs of transporting the resources in the cluster to a destination, a total cost of transporting all of the resources in the plurality of clusters to the respective destinations, wherein the mapping of a cluster comprises mapping all of the resources included in the cluster to the same destination;
reallocating a resource included in a first cluster from a first destination to a second destination, wherein the remaining resources included in the first cluster are mapped to the first destination, the reallocating comprising;
accessing the mapping comprising the clusters, the resources and the destinations;
accessing the stored costs for transporting each resource to each destination;
ranking each resource within the first cluster based on a set of shadow costs, each shadow cost comprising a cost of remapping the resource to a next-more-costly destination, the cost of remapping the resource based at least in part on the stored costs for transporting the resource to each destination;
determining that a total number of resources in the first cluster exceeds a predetermined capacity of the first destination; and
based on the ranking, reallocating a resource that exceeds the predetermined capacity from the first destination to the second destination; and
at a display associated with the interactive user interface;
displaying the destinations to which clusters are mapped in a pictorial representation; and
displaying an assignment of all of the resources, including the reallocated resource, to the destinations for planning an event.
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Abstract
Apparatus and methods for machine-based planning. The apparatus may cluster a plurality of geographically different resources into a plurality of clusters of proximate resources. The apparatus may calculate a cost of transporting each resource to each of a plurality of destinations. The apparatus may map each cluster to one of the destinations to determine a sum of costs of transporting all of the resources to the destinations. The apparatus may assign to each of the plurality of destinations only resources: that are mapped to the destination; for which the destination has sufficient capacity to accommodate the resources; and whose assignment to the destination does not exclude from the destination, by filling the capacity, a different resource that is: mapped to the destination; and has a net cost that is higher than a net cost of the resource of the assignment.
49 Citations
32 Claims
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1. A method for machine-based dynamic reallocation of a plurality of resources among a plurality of destinations to globally optimize total cost in event planning, the method comprising:
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receiving from a user at an interactive user interface; a selection of a plurality of geographically different resources; and a specification of a number of destinations; using a processor; clustering the plurality of geographically different resources into a plurality of clusters of proximate resources, the number of clusters equal to the number of destinations; calculating a cost of transporting each resource to each of the destinations and storing the costs in machine-readable memory, referenced by resource and destination; mapping each cluster to a respective one of the destinations to determine, based at least in part on the costs of transporting the resources in the cluster to a destination, a total cost of transporting all of the resources in the plurality of clusters to the respective destinations, wherein the mapping of a cluster comprises mapping all of the resources included in the cluster to the same destination; reallocating a resource included in a first cluster from a first destination to a second destination, wherein the remaining resources included in the first cluster are mapped to the first destination, the reallocating comprising; accessing the mapping comprising the clusters, the resources and the destinations; accessing the stored costs for transporting each resource to each destination; ranking each resource within the first cluster based on a set of shadow costs, each shadow cost comprising a cost of remapping the resource to a next-more-costly destination, the cost of remapping the resource based at least in part on the stored costs for transporting the resource to each destination; determining that a total number of resources in the first cluster exceeds a predetermined capacity of the first destination; and based on the ranking, reallocating a resource that exceeds the predetermined capacity from the first destination to the second destination; and at a display associated with the interactive user interface; displaying the destinations to which clusters are mapped in a pictorial representation; and displaying an assignment of all of the resources, including the reallocated resource, to the destinations for planning an event. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A system for machine-based optimizing of assignment of a plurality of resources among a plurality of destinations in event planning, the system comprising:
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means for receiving from a system user; a selection of a plurality of geographically different resources; and a specification of a number of destinations; means for clustering the plurality of geographically different resources into a plurality of clusters of proximate resources, the number of clusters equal to the number of destinations; means for calculating a cost of transporting each resource to each of the plurality of destinations and storing the costs in machine-readable memory, referenced by resource and destination; and means for mapping each cluster to a respective one of the destinations to determine a total cost of transporting all of the resources in the plurality of clusters to the respective destinations, wherein mapping the cluster comprises mapping all of the resources in the cluster to the same destination; means for reallocating a resource included in a first cluster from a first destination to a second destination, wherein the remaining resources included in the first cluster are mapped to the first destination, the reallocating comprising; accessing the mapping comprising the clusters, the resources and the destinations; accessing the stored costs for transporting each resource to each destination; ranking each resource within the first cluster based on a set of shadow costs, each shadow cost comprising a cost of remapping the resource to a next-more-costly destination, the cost of remapping the resource based at least in part on the stored costs for transporting the resource to each destination; determining that a total number of resources in the first cluster exceeds a predetermined capacity of the first destination; and based on the ranking, for a resource that exceeds the predetermined capacity, reallocating the resource from the first destination to the second destination; and means for displaying to a user; a pictorial representation of the mapped destinations; and an assignment of all of the resources, including the reallocated resource, to the destinations for an event. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32)
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Specification