Cost and latency reductions through dynamic updates of order movement through a transportation network
First Claim
1. A method comprising:
- using a computing system having at least one processor to perform a process, the process comprising;
receiving a set of route data;
converting the set of route data from a first data format to a second data format to generate data suitable for processing by a clustering engine, the second data format comprising a graph of nodes and edges where the nodes represent locations and the edges represent travel between locations, wherein the edges are annotated with edge constraints describing parameters regarding travel between locations;
identifying a set of orders to be shipped from a source region to a destination region using a transportation network;
converting the set of orders into graph items, the graph items including at least a source node and a destination node, the graph items further comprising graph item constraints specifying conditions for using the edges of the graph of nodes, wherein the graph items are to be merged with the graph of nodes and edges as part of generating a plurality of multi-stop route plans;
generating relaxed constraints from the graph item constraints;
identifying candidate options for performing stops at locations corresponding to a subset of the nodes over possible routes represented by a plurality of the nodes and a plurality of the edges between the source region and the destination region, wherein the candidate options correspond to individual orders of the set of orders and satisfy the relaxed constraints, and the relaxed constraints increase the probability that the lowest cost route can be found;
performing clustering analysis upon the candidate options using the clustering engine by generating the plurality of multi-stop route plans that meet the edge constraints and the graph item constraints, at least some of the plurality of multi-stop route plans including at least a plurality of the candidate options, and generating the plurality of multi-stop route plans comprises at least a consolidation of two or more of the graph items with at least a subset of the graph of nodes and edges, wherein clustering analysis considers a plurality of order consolidation possibilities; and
generating a multi-stop route schedule for a selected multi-stop route plan for execution on the transportation network.
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Abstract
A method, system, and computer program product for shipping management. The computer implemented method commences upon identifying a set of orders to be shipped from a source region to a destination region using a transportation network, and determining candidate options for performing stops over possible routes between the source region and the destination region. A clustering analysis process is performed over the candidate options such that the clustering analysis considers many order consolidation possibilities while observing timing constraints. Low-cost options from among the candidate options are considered to identify one or more low-cost options, and a multi-stop route plan is generated to correspond to a selected low-cost option. The orders are shipped in accordance with the multi-stop route plan, and in accordance with the corresponding consolidation of the set of orders.
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Citations
20 Claims
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1. A method comprising:
using a computing system having at least one processor to perform a process, the process comprising; receiving a set of route data; converting the set of route data from a first data format to a second data format to generate data suitable for processing by a clustering engine, the second data format comprising a graph of nodes and edges where the nodes represent locations and the edges represent travel between locations, wherein the edges are annotated with edge constraints describing parameters regarding travel between locations; identifying a set of orders to be shipped from a source region to a destination region using a transportation network; converting the set of orders into graph items, the graph items including at least a source node and a destination node, the graph items further comprising graph item constraints specifying conditions for using the edges of the graph of nodes, wherein the graph items are to be merged with the graph of nodes and edges as part of generating a plurality of multi-stop route plans; generating relaxed constraints from the graph item constraints; identifying candidate options for performing stops at locations corresponding to a subset of the nodes over possible routes represented by a plurality of the nodes and a plurality of the edges between the source region and the destination region, wherein the candidate options correspond to individual orders of the set of orders and satisfy the relaxed constraints, and the relaxed constraints increase the probability that the lowest cost route can be found; performing clustering analysis upon the candidate options using the clustering engine by generating the plurality of multi-stop route plans that meet the edge constraints and the graph item constraints, at least some of the plurality of multi-stop route plans including at least a plurality of the candidate options, and generating the plurality of multi-stop route plans comprises at least a consolidation of two or more of the graph items with at least a subset of the graph of nodes and edges, wherein clustering analysis considers a plurality of order consolidation possibilities; and generating a multi-stop route schedule for a selected multi-stop route plan for execution on the transportation network. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process, the process comprising:
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receiving a set of route data; converting the set of route data from a first data format to a second data format to generate data suitable for processing by a clustering engine, the second data format comprising a graph of nodes and edges where the nodes represent locations and the edges represent travel between locations, wherein the edges are annotated with edge constraints describing parameters regarding travel between locations; identifying a set of orders to be shipped from a source region to a destination region using a transportation network; converting the set of orders into graph items, the graph items including at least a source node and a destination node, the graph items further comprising graph item constraints specifying conditions for using the edges of the graph of nodes, wherein the graph items are to be merged with the graph of nodes and edges as part of generating a plurality of multi-stop route plans; generating relaxed constraints from the graph item constraints; identifying candidate options for performing stops at locations corresponding to a subset of the nodes over possible routes represented by a plurality of the nodes and a plurality of the edges between the source region and the destination region, wherein the candidate options correspond to individual orders of the set of orders and satisfy the relaxed constraints, and the relaxed constraints increase the probability that the lowest cost route can be found; performing clustering analysis upon the candidate options using the clustering engine by generating the plurality of multi-stop route plans that meet the edge constraints and the graph item constraints, at least some of the plurality of multi-stop route plans including at least a plurality of the candidate options, and generating the plurality of multi-stop route plans comprises at least a consolidation of two or more of the graph items with at least a subset of the graph of nodes and edges, wherein clustering analysis considers a plurality of order consolidation possibilities; and generating a multi-stop route schedule for a selected multi-stop route plan for execution on the transportation network. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A computer system comprising:
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a memory for storing instructions; and a processor which performs the following actions when executing instructions; receiving a set of route data; converting the set of route data from a first data format to a second data format to generate data suitable for processing by a clustering engine, the second data format comprising a graph of nodes and edges where the nodes represent locations and the edges represent travel between locations, wherein the edges are annotated with edge constraints describing parameters regarding travel between locations; identifying a set of orders to be shipped from a source region to a destination region using a transportation network; converting the set of orders into graph items, the graph items including at least a source node and a destination node, the graph items further comprising graph item constraints specifying conditions for using the edges of the graph of nodes, wherein the graph items are to be merged with the graph of nodes and edges as part of generating a plurality of multi-stop route plans; generating relaxed constraints from the graph item constraints; identifying candidate options for performing stops at locations corresponding to a subset of the nodes over possible routes represented by a plurality of the nodes and a plurality of the edges between the source region and the destination region, wherein the candidate options correspond to individual orders of the set of orders and satisfy the relaxed constraints, and the relaxed constraints increase the probability that the lowest cost route can be found; performing clustering analysis upon the candidate options using the clustering engine by generating the plurality of multi-stop route plans that meet the edge constraints and the graph item constraints, at least some of the plurality of multi-stop route plans including at least a plurality of the candidate options, and generating the plurality of multi-stop route plans comprises at least a consolidation of two or more of the graph items with at least a subset of the graph of nodes and edges, wherein clustering analysis considers a plurality of order consolidation possibilities; and generating a multi-stop route schedule for a selected multi-stop route plan for execution on the transportation network. - View Dependent Claims (20)
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Specification