The type of solver to use for graph matching. More...

Public Attributes
const string	MARKOV_CHAIN = "markov_chain"
	Matches sample_points 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. More...

const string	MATCH_OD_PAIRS = "match_od_pairs"
	Matches sample_points to find the most probable path between origin and destination pairs with cost constraints. More...

const string	MATCH_SUPPLY_DEMAND = "match_supply_demand"
	Matches sample_points to optimize scheduling multiple supplies (trucks) with varying sizes to varying demand sites with varying capacities per depot. More...

const string	MATCH_BATCH_SOLVES = "match_batch_solves"
	Matches sample_points source and destination pairs for the shortest path solves in batch mode. More...

const string	MATCH_LOOPS = "match_loops"
	Matches closed loops (Eulerian paths) originating and ending at each graph node within min and max hops (levels). More...

const string	MATCH_CHARGING_STATIONS = "match_charging_stations"
	Matches an optimal path across a number of ev-charging stations between source and target locations. More...

const string	MATCH_SIMILARITY = "match_similarity"
	Matches the intersection set(s) by computing the Jaccard similarity score between node pairs. More...

const string	MATCH_PICKUP_DROPOFF = "match_pickup_dropoff"
	Matches the pickups and dropoffs by optimizing the total trip costs More...

const string	MATCH_CLUSTERS = "match_clusters"
	Matches the graph nodes with a cluster index using Louvain clustering algorithm More...

const string	MATCH_PATTERN = "match_pattern"
	Matches a pattern in the graph More...

Detailed Description

The type of solver to use for graph matching.

Supported values:

MARKOV_CHAIN: Matches 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.
MATCH_OD_PAIRS: Matches to find the most probable path between origin and destination pairs with cost constraints.
MATCH_SUPPLY_DEMAND: Matches 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.
MATCH_BATCH_SOLVES: Matches source and destination pairs for the shortest path solves in batch mode.
MATCH_LOOPS: Matches closed loops (Eulerian paths) originating and ending at each graph node within min and max hops (levels).
MATCH_CHARGING_STATIONS: Matches an optimal path across a number of ev-charging stations between source and target locations.
MATCH_SIMILARITY: Matches the intersection set(s) by computing the Jaccard similarity score between node pairs.
MATCH_PICKUP_DROPOFF: Matches the pickups and dropoffs by optimizing the total trip costs
MATCH_CLUSTERS: Matches the graph nodes with a cluster index using Louvain clustering algorithm
MATCH_PATTERN: Matches a pattern in the graph

The default value is MARKOV_CHAIN. A set of string constants for the parameter solve_method.

Definition at line 119 of file MatchGraph.cs.

Member Data Documentation

const string kinetica.MatchGraphRequest.SolveMethod.MARKOV_CHAIN = "markov_chain"

Matches sample_points 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.

Definition at line 132 of file MatchGraph.cs.

const string kinetica.MatchGraphRequest.SolveMethod.MATCH_BATCH_SOLVES = "match_batch_solves"

Matches sample_points source and destination pairs for the shortest path solves in batch mode.

Definition at line 149 of file MatchGraph.cs.

const string kinetica.MatchGraphRequest.SolveMethod.MATCH_CHARGING_STATIONS = "match_charging_stations"

Matches an optimal path across a number of ev-charging stations between source and target locations.

Definition at line 158 of file MatchGraph.cs.

const string kinetica.MatchGraphRequest.SolveMethod.MATCH_CLUSTERS = "match_clusters"

Matches the graph nodes with a cluster index using Louvain clustering algorithm

Definition at line 170 of file MatchGraph.cs.

const string kinetica.MatchGraphRequest.SolveMethod.MATCH_LOOPS = "match_loops"

Matches closed loops (Eulerian paths) originating and ending at each graph node within min and max hops (levels).

Definition at line 154 of file MatchGraph.cs.

const string kinetica.MatchGraphRequest.SolveMethod.MATCH_OD_PAIRS = "match_od_pairs"

Matches sample_points to find the most probable path between origin and destination pairs with cost constraints.

Definition at line 137 of file MatchGraph.cs.

const string kinetica.MatchGraphRequest.SolveMethod.MATCH_PATTERN = "match_pattern"

Matches a pattern in the graph

Definition at line 173 of file MatchGraph.cs.

const string kinetica.MatchGraphRequest.SolveMethod.MATCH_PICKUP_DROPOFF = "match_pickup_dropoff"

Matches the pickups and dropoffs by optimizing the total trip costs

Definition at line 166 of file MatchGraph.cs.

const string kinetica.MatchGraphRequest.SolveMethod.MATCH_SIMILARITY = "match_similarity"

Matches the intersection set(s) by computing the Jaccard similarity score between node pairs.

Definition at line 162 of file MatchGraph.cs.

const string kinetica.MatchGraphRequest.SolveMethod.MATCH_SUPPLY_DEMAND = "match_supply_demand"

Matches sample_points 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.

Definition at line 144 of file MatchGraph.cs.

The documentation for this struct was generated from the following file:

Kinetica/Protocol/MatchGraph.cs

Public Attributes

Detailed Description

Member Data Documentation