SOLVERS FOR INFRASTRUCTURE DESIGN AND OPTIMIZATION
A computer-implemented method for optimizing an alignment between two points includes receiving a map of an area. The method also includes selecting a first solver from a group of solvers for optimizing an alignment between the two points in the map, each of the group of solvers is a machine learning solver. The method further includes generating a first optimal alignment between the two points based on the first solver minimizing a cost function associated with the two points.
1 . A computer-implemented method for optimizing an alignment between two points, the method comprising:
receiving a map of an area;
selecting a first solver from a group of solvers for optimizing an alignment between the two points in the map, each of the group of solvers is a machine learning solver; and
generating a first optimal alignment between the two points based on the first solver minimizing a cost function associated with the two points.
2 . The computer-implemented method of claim 1 , the method further comprising:
benchmarking the first solver to generate benchmarking data; and
logging the benchmarking data.
3 . The computer-implemented method of claim 1 , the method further comprising:
selecting one or more second solvers from the group of solvers to optimize the first alignment by minimizing the cost function; and
generating based on the one or more second solvers a second optimized alignment.
4 . The computer-implemented method of claim 1 , wherein:
one or more locations in the map are associated with a respective cost; and
the first solver minimizes the cost function based on the respective cost of each location corresponding to a path between the two points.
5 . The computer-implemented method of claim 1 , wherein:
the map includes an initial alignment between the two points; and
the first optimal alignment optimizes the initial alignment.
6 . The computer-implemented method of claim 1 , further comprising pre-processing the map.
7 . An apparatus for optimizing an alignment between two points comprising:
one or more processors; and
one or more memories coupled with the one or more processors and storing processor-executable code that, when executed by the one or more processors, is configured to cause the apparatus to:
receive a map of an area;
select a first solver from a group of solvers for optimizing an alignment between the two points in the map, each of the group of solvers is a machine learning solver; and
generate a first optimal alignment between the two points based on the first solver minimizing a cost function associated with the two points.
8 . The apparatus of claim 7 , wherein execution of the processor-executable code further causes the apparatus to:
benchmark the first solver to generate benchmarking data; and
log the benchmarking data.
9 . The apparatus of claim 7 , wherein execution of the processor-executable code further causes the apparatus to:
select one or more second solvers from the group of solvers to optimize the first alignment by minimizing the cost function; and
generate based on the one or more second solvers a second optimized alignment.
10 . The apparatus of claim 7 , wherein:
one or more locations in the map are associated with a respective cost; and
the first solver minimizes the cost function based on the respective cost of each location corresponding to a path between the two points.
11 . The apparatus of claim 7 , wherein:
the map includes an initial alignment between the two points; and
the first optimal alignment optimizes the initial alignment.
12 . The apparatus of claim 7 , wherein execution of the processor-executable code further causes the apparatus to pre-process the map.
13 . A non-transitory computer-readable medium having program code recorded thereon for optimizing an alignment between two points, the program code executed by one or more processors and comprising:
program code to receive a map of an area;
program code to select a first solver from a group of solvers for optimizing an alignment between the two points in the map, each of the group of solvers is a machine learning solver; and
program code to generate a first optimal alignment between the two points based on the first solver minimizing a cost function associated with the two points.
14 . The non-transitory computer-readable of claim 13 , wherein the program code further comprises:
program code to benchmark the first solver to generate benchmarking data; and
program code to log the benchmarking data.
15 . The non-transitory computer-readable of claim 13 , wherein the program code further comprises:
program code to select one or more second solvers from the group of solvers to optimize the first alignment by minimizing the cost function; and
program code to generate based on the one or more second solvers a second optimized alignment.
16 . The non-transitory computer-readable of claim 13 , wherein:
one or more locations in the map are associated with a respective cost; and
the first solver minimizes the cost function based on the respective cost of each location corresponding to a path between the two points.
17 . The non-transitory computer-readable of claim 13 , wherein:
the map includes an initial alignment between the two points; and
the first optimal alignment optimizes the initial alignment.
18 . The non-transitory computer-readable of claim 13 , wherein the program code further comprises program code to pre-process the map.