gps_noise  GPS noise value (in meters) to remove redundant sample points. Use 1 to disable noise reduction. The default value accounts for 95% of point variation (+ or 5 meters). The default value is '5.0'. 
num_segments  Maximum number of potentially matching road segments for each sample point. For the markov_chain solver, the default is 3. The default value is '3'. 
search_radius  Maximum search radius used when snapping sample points onto potentially matching surrounding segments. The default value corresponds to approximately 100 meters. The default value is '0.001'. 
chain_width  For the markov_chain solver only. Length of the sample points lookahead window within the Markov kernel; the larger the number, the more accurate the solution. The default value is '9'. 
source  Optional WKT starting point from input parameter sample_points for the solver. The default behavior for the endpoint is to use time to determine the starting point. The default value is 'POINT NULL'. 
destination  Optional WKT ending point from input parameter sample_points for the solver. The default behavior for the endpoint is to use time to determine the destination point. The default value is 'POINT NULL'. 
partial_loading  For the match_supply_demand solver only. When false (nondefault), trucks do not offload at the demand (store) side if the remainder is less than the store's need The default value is true. Supported
Values  Description 

true  Partial offloading at multiple store (demand) locations  false  No partial offloading allowed if supply is less than the store's demand. 

max_combinations  For the match_supply_demand solver only. This is the cutoff for the number of generated combinations for sequencing the demand locations  can increase this up to 2M. The default value is '10000'. 
max_supply_combinations  For the match_supply_demand solver only. This is the cutoff for the number of generated combinations for sequencing the supply locations if/when 'permute_supplies' is true. The default value is '10000'. 
left_turn_penalty  This will add an additonal weight over the edges labelled as 'left turn' if the 'add_turn' option parameter of the
Create Graph
was invoked at graph creation. The default value is '0.0'. 
right_turn_penalty  This will add an additonal weight over the edges labelled as' right turn' if the 'add_turn' option parameter of the
Create Graph
was invoked at graph creation. The default value is '0.0'. 
intersection_penalty  This will add an additonal weight over the edges labelled as 'intersection' if the 'add_turn' option parameter of the
Create Graph
was invoked at graph creation. The default value is '0.0'. 
sharp_turn_penalty  This will add an additonal weight over the edges labelled as 'sharp turn' or 'uturn' if the 'add_turn' option parameter of the
Create Graph
was invoked at graph creation. The default value is '0.0'. 
aggregated_output  For the match_supply_demand solver only. When it is true (default), each record in the output table shows a particular truck's scheduled cumulative round trip path (MULTILINESTRING) and the corresponding aggregated cost. Otherwise, each record shows a single scheduled truck route (LINESTRING) towards a particular demand location (store id) with its corresponding cost. The default value is 'true'. 
output_tracks  For the match_supply_demand solver only. When it is true (nondefault), the output will be in tracks format for all the round trips of each truck in which the timestamps are populated directly from the edge weights starting from their originating depots. The default value is 'false'. 
max_trip_cost  For the match_supply_demand and match_pickup_dropoff solvers only. If this constraint is greater than zero (default) then the trucks/rides will skip travelling from one demand/pick location to another if the cost between them is greater than this number (distance or time). Zero (default) value means no check is performed. The default value is '0.0'. 
filter_folding_paths  For the markov_chain solver only. When true (nondefault), the paths per sequence combination is checked for folding over patterns and can significantly increase the execution time depending on the chain width and the number of gps samples. The default value is false. Supported
Values  Description 

true  Filter out the folded paths.  false  Do not filter out the folded paths 

unit_unloading_cost  For the match_supply_demand solver only. The unit cost per load amount to be delivered. If this value is greater than zero (default) then the additional cost of this unit load multiplied by the total dropped load will be added over to the trip cost to the demand location. The default value is '0.0'. 
max_num_threads  For the markov_chain solver only. If specified (greater than zero), the maximum number of threads will not be greater than the specified value. It can be lower due to the memory and the number cores available. Default value of zero allows the algorithm to set the maximal number of threads within these constraints. The default value is '0'. 
service_limit  For the match_supply_demand solver only. If specified (greater than zero), any supply actor's total service cost (distance or time) will be limited by the specified value including multiple rounds (if set). The default value is '0.0'. 
enable_reuse  For the match_supply_demand solver only. If specified (true), all supply actors can be scheduled for second rounds from their originating depots. The default value is false. Supported
Values  Description 

true  Allows reusing supply actors (trucks, e.g.) for scheduling again.  false  Supply actors are scheduled only once from their depots. 

max_stops  For the match_supply_demand solver only. If specified (greater than zero), a supply actor (truck) can at most have this many stops (demand locations) in one round trip. Otherwise, it is unlimited. If 'enable_truck_reuse' is on, this condition will be applied separately at each round trip use of the same truck. The default value is '0'. 
service_radius  For the match_supply_demand and match_pickup_dropoff solvers only. If specified (greater than zero), it filters the demands/picks outside this radius centered around the supply actor/ride's originating location (distance or time). The default value is '0.0'. 
permute_supplies  For the match_supply_demand solver only. If specified (true), supply side actors are permuted for the demand combinations during msdo optimization  note that this option increases optimization time significantly  use of 'max_combinations' option is recommended to prevent prohibitively long runs The default value is true. Supported
Values  Description 

true  Generates sequences over supply side permutations if total supply is less than twice the total demand  false  Permutations are not performed, rather a specific order of supplies based on capacity is computed 

batch_tsm_mode  For the match_supply_demand solver only. When enabled, it sets the number of visits on each demand location by a single salesman at each trip is considered to be (one) 1, otherwise there is no bound. The default value is false. Supported
Values  Description 

true  Sets only one visit per demand location by a salesman (tsm mode)  false  No preset limit (usual msdo mode) 

round_trip  For the match_supply_demand solver only. When enabled, the supply will have to return back to the origination location. The default value is true. Supported
Values  Description 

true  The optimization is done for trips in round trip manner always returning to originating locations  false  Supplies do not have to come back to their originating locations in their routes. The routes are considered finished at the final dropoff. 

num_cycles  For the match_clusters solver only. Terminates the cluster exchange iterations across 2stepcycles (outer loop) when quality does not improve during iterations. The default value is '10'. 
num_loops_per_cycle  For the match_clusters and match_embedding solvers only. Terminates the cluster exchanges within the first step iterations of a cycle (inner loop) unless convergence is reached. The default value is '10'. 
num_output_clusters  For the match_clusters solver only. Limits the output to the top 'num_output_clusters' clusters based on density. Default value of zero outputs all clusters. The default value is '0'. 
max_num_clusters  For the match_clusters and match_embedding solvers only. If set (value greater than zero), it terminates when the number of clusters goes below than this number. For embedding solver the default is 8. The default value is '0'. 
cluster_quality_metric  For the match_clusters solver only. The quality metric for Louvain modularity optimization solver. The default value is girvan. Supported
Values  Description 

girvan  Uses the Newman Girvan quality metric for cluster solver  spectral  Applies recursive spectral bisection (RSB) partitioning solver 

restricted_type  For the match_supply_demand solver only. Optimization is performed by restricting routes labeled by 'MSDO_ODDEVEN_RESTRICTED' only for this supply actor (truck) type The default value is none. Supported
Values  Description 

odd  Applies odd/even rule restrictions to odd tagged vehicles.  even  Applies odd/even rule restrictions to even tagged vehicles.  none  Does not apply odd/even rule restrictions to any vehicles. 

server_id  Indicates which graph server(s) to send the request to. Default is to send to the server, amongst those containing the corresponding graph, that has the most computational bandwidth. The default value is ''. 
inverse_solve  For the match_batch_solves solver only. Solves sourcedestination pairs using inverse shortest path solver. The default value is false. Supported
Values  Description 

true  Solves using inverse shortest path solver.  false  Solves using direct shortest path solver. 

min_loop_level  For the match_loops solver only. Finds closed loops around each node deducible not less than this minimal hop (level) deep. The default value is '0'. 
max_loop_level  For the match_loops solver only. Finds closed loops around each node deducible not more than this maximal hop (level) deep. The default value is '5'. 
search_limit  For the match_loops solver only. Searches within this limit of nodes per vertex to detect loops. The value zero means there is no limit. The default value is '10000'. 
output_batch_size  For the match_loops solver only. Uses this value as the batch size of the number of loops in flushing(inserting) to the output table. The default value is '1000'. 
charging_capacity  For the match_charging_stations solver only. This is the maximum evcharging capacity of a vehicle (distance in meters or time in seconds depending on the unit of the graph weights). The default value is '300000.0'. 
charging_candidates  For the match_charging_stations solver only. Solver searches for this many number of stations closest around each base charging location found by capacity. The default value is '10'. 
charging_penalty  For the match_charging_stations solver only. This is the penalty for full charging. The default value is '30000.0'. 
max_hops  For the match_similarity and match_embedding solvers only. Searches within this maximum hops for source and target node pairs to compute the Jaccard scores. The default value is '3'. 
traversal_node_limit  For the match_similarity solver only. Limits the traversal depth if it reaches this many number of nodes. The default value is '1000'. 
paired_similarity  For the match_similarity solver only. If true, it computes Jaccard score between each pair, otherwise it will compute Jaccard from the intersection set between the source and target nodes The default value is true. The supported values are: 
force_undirected  For the match_pattern and match_embedding solvers only. Pattern matching will be using both pattern and graph as undirected if set to true. The default value is false. The supported values are: 
max_vector_dimension  For the match_embedding solver only. Limits the number of dimensions in node vector embeddings. The default value is '1000'. 
optimize_embedding_weights  For the match_embedding solvers only. Solves to find the optimal weights per sub feature in vector emdeddings. The default value is false. The supported values are: 
embedding_weights  For the match_embedding solver only. User specified weights per sub feature in vector embeddings. The string contains the comma separated float values for each subfeature in the vector space. These values will ONLY be used if 'optimize_embedding_weights' is false. The default value is '1.0,1.0,1.0,1.0'. 