System and method for intermodal dual-stream-based resource optimization

A system configured to optimize utilization of resources in a hub, comprising:

• at least one processor;
• and
• a memory operably coupled to the at least one processor and storing processor-readable code that, when executed by the at least one processor, is configured to perform operations including:
• representing a first flow of units through the hub as a consolidation stream including a plurality of consolidation stages, wherein units flowing through the consolidation stream are consolidated into one or more departing trains based, at least in part, on a destination of each of the units flowing through the consolidation stream, wherein representing the first flow of units through the hub as a consolidation stream includes generating a first time-space network based on the consolidation stream over a planning horizon timeframe, wherein each node of the first time-space network represents a respective stage of the plurality of consolidation stages, each stage of the plurality of consolidation stages configured to facilitate the loading of the units onto the one or more departing trains within the hub, and wherein an edge between two nodes of the first time-space network represents a resource capacity between the two nodes of the first time-space network;
• representing a second flow of units through the hub as a deconsolidation stream including a plurality of deconsolidation stages, wherein units flowing through the deconsolidation stream are deconsolidated from one or more arriving trains based, at least in part, on a destination of each of the units flowing through the deconsolidation stream, wherein representing the second flow of units through the hub as a deconsolidation stream includes generating a second time-space network based on the deconsolidation over the planning horizon timeframe, wherein each node of the second time-space network represents a respective stage of the plurality of deconsolidation stages, each stage of the plurality of deconsolidation stages configured to facilitate the unloading of the units from the one or more arriving trains within the hub, and an edge between two nodes of the second time-space network represents a resource capacity between the two nodes of the second time-space network;
• obtaining first data associated with a first set of units flowing through the consolidation stream over the planning horizon timeframe, wherein the first data includes:
• a dwell time associated with each unit in the first set of units indicating a duration of time that each unit dwells within the hub, and a prediction of a volume of units in the first set of units using a first prediction model;
• obtaining second data associated with a second set of units flowing through the deconsolidation stream over the planning horizon timeframe, wherein the second data includes:
• a volume of units in the second set of units, and a prediction of a dwell time associated with each unit in the second set of units indicating a duration of time that each unit dwells within the hub using a second prediction model;
• generating, using a dual-stream optimization model, based on the first data and the second data, an optimized operating schedule configured to optimize at least one resource of the hub for the consolidation stream and the deconsolidation stream over the planning horizon timeframe, wherein generating the optimized operating schedule includes layering the first time-space network and the second time-space network together to align nodes of the first time-space network to nodes of the second time-space network at each time increment of the planning horizon timeframe such that a status of a resource of the hub affects both the consolidation stream and the deconsolidation stream;
• generating a signal indicating one or more actions to be performed based on the optimized operating schedule;
• and
• sending a control signal, in response to a generation of the signal, to at least one physical resource of the hub to cause the at least one physical resource to physically reposition from a first location to a second location to enable the optimized operating schedule.

A computer-based tool for optimizing utilization of resources in a hub, the computer-based tool including non-transitory computer readable media having stored thereon computer code which, when executed by a processor, causes a computing device to perform operations comprising:

• representing a first flow of units through the hub as a consolidation stream including a plurality of consolidation stages, wherein units flowing through the consolidation stream are consolidated into one or more departing trains based, at least in part, on a destination of each of the units flowing through the consolidation stream, wherein representing the first flow of units through the hub as a consolidation stream includes generating a first time-space network based on the consolidation stream over a planning horizon timeframe, wherein each node of the first time-space network represents a respective stage of the plurality of consolidation stages, each stage of the plurality of consolidation stages configured to facilitate the loading of the units onto the one or more departing trains within the hub, and wherein an edge between two nodes of the first time-space network represents a resource capacity between the two nodes of the first time-space network;
• representing a second flow of units through the hub as a deconsolidation stream including a plurality of deconsolidation stages, wherein units flowing through the deconsolidation stream are deconsolidated from one or more arriving trains based, at least in part, on a destination of each of the units flowing through the deconsolidation stream, wherein representing the second flow of units through the hub as a deconsolidation stream includes generating a second time-space network based on the deconsolidation over the planning horizon timeframe, wherein each node of the second time-space network represents a respective stage of the plurality of deconsolidation stages, each stage of the plurality of deconsolidation stages configured to facilitate the unloading of the units from the one or more arriving trains within the hub, and an edge between two nodes of the second time-space network represents a resource capacity between the two nodes of the second time-space network;
• obtaining first data associated with a first set of units flowing through the consolidation stream over the planning horizon timeframe, wherein the first data includes:
• a dwell time associated with each unit in the first set of units indicating a duration of time that each unit dwells within the hub, and a prediction of a volume of units in the first set of units using a first prediction model;
• obtaining second data associated with a second set of units flowing through the deconsolidation stream over the planning horizon timeframe, wherein the second data includes:
• a volume of units in the second set of units, and a prediction of a dwell fime associated with each unit in the second set of units indicating a duration of time that each unit dwells within the hub using a second prediction model;
• generating, using a dual-stream optimization model, based on the first data and the second data, an optimized operating schedule configured to optimize at least one resource of the hub for the consolidation stream and the deconsolidation stream over the planning horizon timeframe, wherein generating the optimized operating schedule includes layering the first time-space network and the second time-space network together to align nodes of the first time-space network to nodes of the second time-space network at each time increment of the planning horizon timeframe such that a status of a resource of the hub affects both the consolidation stream and the deconsolidation stream;
• and
• generating a signal indicating one or more actions to be performed based on the optimized operating schedule;
• and
• sending a control signal, in response to a generation of the signal, to at least one physical resource of the hub to cause the at least one physical resource to physically reposition from a first location to a second location to enable the optimized operating schedule.