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kinetica.MatchGraphRequest.SolveMethod Struct Reference

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...
 

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.

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

Definition at line 82 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 95 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 112 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 100 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 107 of file MatchGraph.cs.

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