| 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 | 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 | 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 (non-default), trucks do not
off-load 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 off-loading at multiple store (demand)
locations. | | false | No partial off-loading 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 additional weight over the
edges labeled 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 additional weight over the
edges labeled 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 additional weight over the
edges labeled 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 additional weight over the
edges labeled as 'sharp turn' or 'u-turn' 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 (non-default), 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 traveling 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
(non-default), 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 2-step-cycles (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 source-destination 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. |
| multi_step | For the match_supply_demand solver only.
Runs multiple supply demand solver repeatedly
in a multi step cycle by switching supplies to
demands until it reaches the main hub supply. The default value is false. The supported values are: |
| charging_capacity | For the match_charging_stations solver only.
This is the maximum ev-charging 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. |
| detour_mark_cost | For the match_route_detour solver only. Cost
along the route at which to search for nearby
stations If zero, it solves along the trip
sliding the 3 SSSP cycle kernel by radius
amount. The default value is 3600.0. |
| detour_reentry_factor | For the match_route_detour solver only.
Multiplier on detour_mark_cost to determine
the reentry point on the route (default 1.2
means 20% further along). The default value is 1.2. |
| detour_search_radius | For the match_route_detour solver only.
Search radius around the mark point for
finding nearby prospective stations (e.g.
cafes, pit stops, EV charging stations). The default value is 600.0. |
| detour_search_limit | For the match_route_detour solver only.
Maximum number of nearby stations to consider
within the search radius around the mark
point. The default value is 10. |
| 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 embeddings. 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 sub-feature 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. |
| optimization_sampling_size | For the match_embedding solver only. Sets
the number of random nodes from the graph for
solving the weights using stochastic gradient
descent. The default value is 1000. |
| optimization_max_iterations | For the match_embedding solver only. When
the iterations (epochs) for the convergence of
the stochastic gradient descent algorithm
reaches this number it bails out unless
relative error between consecutive iterations
is below the 'optimization_error_tolerance'
option. The default value is 1000. |
| optimization_error_tolerance | For the match_embedding solver only. When
the relative error between all of the weights'
consecutive iterations falls below this
threshold the optimization cycle is
interrupted unless the number of iterations
reaches the limit set by the option
'max_optimization_iterations'. The default value is 0.001. |
| optimization_iteration_rate | For the match_embedding solver only. It is
otherwise known as the learning rate, which is
the proportionality constant in front of the
gradient term in successive iterations. The default value is 0.3. |
| max_radius | For the match_isochrone solver only. Sets
the maximal reachability limit for computing
isochrones. Zero means no limit. The default value is 0.0. |
