com.gpudb.protocol

Class MatchGraphRequest.SolveMethod

java.lang.Object

com.gpudb.protocol.MatchGraphRequest.SolveMethod

Enclosing class:

MatchGraphRequest

public static final class MatchGraphRequest.SolveMethod
extends Object

The type of solver to use for graph matching. Supported values:

• 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. 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 samplePoints to find the most probable path between origin and destination pairs with cost constraints.
• MATCH_SUPPLY_DEMAND: Matches 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.
• MATCH_BATCH_SOLVES: Matches samplePoints source and destination pairs for the shortest path solves in batch mode.

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

Field Summary

Fields

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

Method Summary

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

MARKOV_CHAIN

public static final 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. 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.

See Also:

Constant Field Values

MATCH_OD_PAIRS

public static final String MATCH_OD_PAIRS

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

See Also:

Constant Field Values

MATCH_SUPPLY_DEMAND

public static final String MATCH_SUPPLY_DEMAND

Matches 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.

See Also:

Constant Field Values

MATCH_BATCH_SOLVES

public static final String MATCH_BATCH_SOLVES

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

See Also:

Constant Field Values