public static final class MatchGraphRequest.SolveMethod extends Object
MatchGraphRequest
parameter
solveMethod
.
The type of solver to use for graph matching.
Modifier and Type | Field and Description |
---|---|
static String |
MARKOV_CHAIN
Matches
samplePoints to the graph using
the Hidden Markov Model (HMM)-based method, which conducts a
range-tree closest-edge search to find the best combinations of
possible road segments (NUM_SEGMENTS )
for each sample point to create the best route. |
static String |
MATCH_BATCH_SOLVES
Matches
samplePoints source and
destination pairs for the shortest path solves in batch mode. |
static String |
MATCH_CHARGING_STATIONS
Matches an optimal path across a number of ev-charging stations
between source and target locations.
|
static String |
MATCH_CLUSTERS
Matches the graph nodes with a cluster index using Louvain
clustering algorithm
|
static String |
MATCH_EMBEDDING
Creates vector node embeddings
|
static String |
MATCH_ISOCHRONE
Solves for isochrones for a set of input sources
|
static String |
MATCH_LOOPS
Matches closed loops (Eulerian paths) originating and ending at each
graph node within min and max hops (levels).
|
static String |
MATCH_OD_PAIRS
Matches
samplePoints to find the most
probable path between origin and destination pairs with cost
constraints. |
static String |
MATCH_PATTERN
Matches a pattern in the graph
|
static String |
MATCH_PICKUP_DROPOFF
Matches the pickups and dropoffs by optimizing the total trip costs
|
static String |
MATCH_SIMILARITY
Matches the intersection set(s) by computing the Jaccard similarity
score between node pairs.
|
static String |
MATCH_SUPPLY_DEMAND
Matches
samplePoints to optimize
scheduling multiple supplies (trucks) with varying sizes to varying
demand sites with varying capacities per depot. |
public static final String MARKOV_CHAIN
samplePoints
to the graph using
the Hidden Markov Model (HMM)-based method, which conducts a
range-tree closest-edge search to find the best combinations of
possible road segments (NUM_SEGMENTS
)
for each sample point to create the best route. The route is secured
one point at a time while looking ahead CHAIN_WIDTH
number of points, so the prediction is corrected after
each point. This solution type is the most accurate but also the
most computationally intensive. Related options: NUM_SEGMENTS
and CHAIN_WIDTH
.public static final String MATCH_OD_PAIRS
samplePoints
to find the most
probable path between origin and destination pairs with cost
constraints.public static final String MATCH_SUPPLY_DEMAND
samplePoints
to optimize
scheduling multiple supplies (trucks) with varying sizes to varying
demand sites with varying capacities per depot. Related options:
PARTIAL_LOADING
and MAX_COMBINATIONS
.public static final String MATCH_BATCH_SOLVES
samplePoints
source and
destination pairs for the shortest path solves in batch mode.public static final String MATCH_LOOPS
public static final String MATCH_CHARGING_STATIONS
public static final String MATCH_SIMILARITY
public static final String MATCH_PICKUP_DROPOFF
public static final String MATCH_CLUSTERS
public static final String MATCH_PATTERN
public static final String MATCH_EMBEDDING
public static final String MATCH_ISOCHRONE
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