Parameter
Global settings and parameters are stored in a specific table.
Some of these parameters are used by the planning algorithm, others are used by the web application. Extension modules also add additional configuration parameters to this table.
Fields
Field 
Type 
Description 

name 
string 
Unique name of the parameter. 
value 
string 
Value of the parameter. 
description 
string 
Description of the parameter. 
Standard parameters
The table below shows the parameters that are recognized by the standard application.
Parameter 
Description 

currentdate 
Current date of the plan, formatted as YYYYMMDD HH:MM:SS.
If the parameter is missing or empty the system time is used as current date.

currency 
Currency symbol.
This parameter may be only set on the default database and will be
globally applied, including in all the scenarios.
If the parameter is missing or empty the currency symbol will be the $.
By default the symbol will show after the value, i.e. 123 $.
For the symbol to show before the value a , should be added after the
symbol, i.e. $,, resulting in $ 123.

loading_time_units 
Time units to be used for the resource report.
Accepted values are: hours, days, weeks.

plan.administrativeLeadtime 
Specifies an administrative lead time in days.
FrePPLe will plan the sales orders one administrative lead time ahead of the due date.
Accepted values : Any positive decimal number.

plan.autoFenceOperations 
The number of days the solver should wait for a confirmed
replenishment before generating a proposed order.
Default:0 (deactivated).

plan.calendar 
Name of a calendar to align new operationplans with.
When this parameter is used, the plan results are effectively grouped
in the time buckets defined in this calendar.
This feature is typically used for medium and long term plans.
Such plans are reviewed in monthly or weekly buckets rather than at individual dates.

plan.loglevel 
Controls the verbosity of the planning log file.
Accepted values are 0 (silent – default), 1 (minimal)
and 2 (verbose).

plan.planSafetyStockFirst 
Controls whether safety stock is planned before or after the demand.
Accepted values are false (default) and true.

plan.rotateResources 
When set to true, the algorithm will better distribute
the demand across alternate suboperations instead of using
the preferred operation.

plan.webservice 
Specifies whether to use the web service or not.
Accepted values are false (default) and true.

Extension modules parameters
The table below shows the parameters that are regognized by all the extension modules and therefore only available on the Enterprise edition. By convention, these parameters are formatted module.name to clearly state to which module they apply.
Parameter 
Description 

forecast.calendar 
Name of a calendar model to define the granularity of the time buckets for forecasting. 
forecast.Croston_initialAlfa 
Initial parameter for the Croston forecast method. 
forecast.Croston_maxAlfa 
Maximum parameter for the Croston forecast method. 
forecast.Croston_minAlfa 
Minimum parameter for the Croston forecast method. 
forecast.Croston_minIntermittence 
Minimum intermittence (defined as the percentage of zero demand buckets) before the Croston method is applied. 
forecast.DeadAfterInactivity 
Number of days of inactivity before a forecast is marked dead and it’s baseline forecast will be 0. Default is 365. 
forecast.DoubleExponential_dampenTrend 
Dampening factor applied to the trend in future periods. 
forecast.DoubleExponential_initialAlfa 
Initial smoothing constant. 
forecast.DoubleExponential_initialGamma 
Initial trend smoothing constant. 
forecast.DoubleExponential_maxAlfa 
Maximum smoothing constant. 
forecast.DoubleExponential_maxGamma 
Maximum trend smoothing constant. 
forecast.DoubleExponential_minAlfa 
Minimum smoothing constant. 
forecast.DoubleExponential_minGamma 
Minimum trend smoothing constant. 
forecast.DueWithinBucket 
Specifies whether forecasted demand is due at the ‘start’, ‘middle’ or ‘end’ of the bucket. 
forecast.Horizon_future 
Specifies the number of days in the future we generate a forecast for. 
forecast.Horizon_history 
Specifies the number of days in the past we use to compute a statistical forecast. 
forecast.Iterations 
Specifies the maximum number of iterations allowed for a forecast method to tune its parameters. 
forecast.loglevel 
Verbosity of the forecast solver 
forecast.MovingAverage_order 
This parameter controls the number of buckets to be averaged by the moving average forecast method. 
forecast.Net_CustomerThenItemHierarchy 
This flag allows us to control whether we first search the customer hierarchy and then the item hierarchy, or the other way around. 
forecast.Net_MatchUsingDeliveryOperation 
Specifies whether or not a demand and a forecast require to have the same delivery operation to be a match. 
forecast.Net_NetEarly 
Defines how much time (expressed in seconds) before the due date of an order we are allowed to search for a forecast bucket to net from. 
forecast.Net_NetLate 
Defines how much time (expressed in seconds) after the due date of an order we are allowed to search for a forecast bucket to net from. 
forecast.Outlier_maxDeviation 
Multiple of the standard deviation used to detect outliers 
forecast.populateForecastTable 
Populates automatically the forecast table based on the item/location combinations found in the demand table using parent customer when available. Default : true 
forecast.Seasonal_dampenTrend 
Dampening factor applied to the trend in future periods. 
forecast.Seasonal_gamma 
Value of the seasonal parameter 
forecast.Seasonal_initialAlfa 
Initial value for the constant parameter 
forecast.Seasonal_initialBeta 
Initial value for the trend parameter 
forecast.Seasonal_maxAlfa 
Maximum value for the constant parameter 
forecast.Seasonal_maxBeta 
Maximum value for the trend parameter 
forecast.Seasonal_maxPeriod 
Maximum seasonal cycle to be checked. 
forecast.Seasonal_minAlfa 
Minimum value for the constant parameter 
forecast.Seasonal_minBeta 
Initial value for the trend parameter 
forecast.Seasonal_minPeriod 
Minimum seasonal cycle to be checked. 
forecast.Seasonal_minAutocorrelation 
Minimum autocorrelation below which the seasonal forecast method is never selected. 
forecast.Seasonal_maxAutocorrelation 
Maximum autocorrelation above which the seasonal forecast method is always selected. 
forecast.SingleExponential_initialAlfa 
Initial smoothing constant. 
forecast.SingleExponential_maxAlfa 
Maximum smoothing constant. 
forecast.SingleExponential_minAlfa 
Minimum smoothing constant. 
forecast.Skip 
Specifies the number of time series values used to initialize the forecasting method. The forecast error in these bucket isn’t counted. 
forecast.SmapeAlfa 
Specifies how the sMAPE forecast error is weighted for different time buckets. 
inventoryplanning.average_window_duration 
The number of days used to average the demand to limit ROQ and safety stock variability over periods. Default value : 180 
inventoryplanning.calendar 
Name of a calendar model to define the granularity of the time buckets for inventory planning. 
inventoryplanning.fixed_order_cost 
Holding cost percentage to compute economic reorder quantity. Default value: 20 
inventoryplanning.holding_cost 
Fixed order cost to compute the economic reorder quantity. Default value: 0.05 
inventoryplanning.horizon_end 
Specifies the number of days in the future for which we generate safety stock and reorder quantity values. Default: 365 
inventoryplanning.horizon_start 
Specifies the number of days in the past for which we generate safety stock and reorder quantity values. Default: 0 
inventoryplanning.loglevel 
Controls the verbosity of the inventory planning solver. Accepted values are 0(silent  default), 1 and 2 (verbose) 
inventoryplanning.rebalancing_burnout_threshold 
The minimum time to burn up excess inventory (compared to forecast) that can be rebalanced (in periods). If the burn out period (Excess Quantity/Forecast) is less than the threshold, the rebalancing will not occur. Default value: 0 
inventoryplanning.rebalancing_part_cost_threshold 
The minimum part cost threshold used to trigger a rebalancing. Parts with cost below the threshold will not be rebalanced. Default value: 0 
inventoryplanning.rebalancing_total_cost_threshold 
The minimum total cost threshold to trigger a rebalancing (equals to rebalanced qty multiplied by item cost). Rebalancing requests with total cost below the threshold will not be created. Default value: 0 
inventoryplanning.service_level_on_average_inventory 
Flag whether the service level is computed based on the expected average inventory. When set to false the service level estimation is based only on the safety stock. Default value: false 