private Double getWeight1(long age) {
// Weight that will be used when status_cd = ACTIVE
if (age <= 0) {
return SystemDao.getDefaultWeight();
}
return Math.max(0.2, 1.0 / age);
}
public double getWeightedWeight1(long age, double defaultWeight) {
if (age <= 0) {
return defaultWeight;
} else {
return Math.max(getWeight1(age), defaultWeight * (1.0d / age));
}
}
private void initLearningMetrics() {
if (learningMetricsInitialized) {
return;
}
double defaultWeight = SystemDao.getDefaultWeight();
double lastWeekLift = getDemandUplift(SystemDao.getReviewCycleStartDate());
Sales beginOfRunCycleSales = getSales(SystemDao.getReviewCycleStartDate());
double beginOfRunCycleRcAvgSales = 0;
if (beginOfRunCycleSales != null) {
beginOfRunCycleRcAvgSales = beginOfRunCycleSales.getRcAvgSales();
}
rcAvgSales =
getWeightedWeight1(learningWeekCounter, defaultWeight) * epSales / lastWeekLift
+ (1 - getWeightedWeight1(learningWeekCounter, defaultWeight))
* beginOfRunCycleRcAvgSales;
// Tim's documentation states:
// Its important sales metrics are initialized to AVG_WEEKLY_SALES based on the initialization
// logic.
// This estimates initial values based on different combinations of the PLs product and location
// hierarchies dependent on the specific situation for that PL
rcAvgSalesActual = rcAvgSales;
rcAvgDemand = rcAvgSales;
rcOldAvgDemand = rcAvgSales;
rcAvgDemandActual = rcAvgSales;
epAvgInv = rcAvgSales;
rcWass2 = Math.pow(rcAvgSales, 2);
learningMetricsInitialized = true;
}
private void processInventory() {
LocalDate crc = SystemDao.getCrc();
if (isStockedOut) {
Demand d = getDemand(SystemDao.getCrc());
if (crc.getDayOfWeek() == DateTimeConstants.SUNDAY) {
d = getDemand(SystemDao.getReviewCycleStartDate());
}
int targetInv = (int) d.getRcAvgDemand() - inventory;
setInventory(targetInv > 0 ? targetInv : (int) d.getRcAvgDemand());
isStockedOut = false;
}
if (crc.getDayOfWeek() == DateTimeConstants.SUNDAY) {
rcBopInv = inventory;
}
// daily inventory updates
updateEpEopInv();
epEopInv = inventory;
rcInvOut += epInvOut;
rcInvIn += epInvIn;
ProductInventory p = getInventory(SystemDao.getReviewCycleStartDate());
double beginOfPeriodEpAvgInv = 0;
if (p != null) {
beginOfPeriodEpAvgInv = p.getEpAvgInv();
}
double weight_5 = SystemDao.getWeight_5();
epAvgInv =
weight_5 * ((epEopInv >= 0) ? epEopInv : 0) + (((1 - weight_5) * beginOfPeriodEpAvgInv));
epAvgInv = Math.max(0, epAvgInv);
}
// Hook: MSSalesOutlierCheckHook.java
public void performOutlierProcessing(String locId) {
// only apply constraint if we are not in a seasonal period
System.out.println(
"Starting the Outlier/Unreported Sales Calculation for product/location: " + locId);
int specialPuchaseOrderWassMult = SystemDao.getSpecialPurchaseOrderWassMultiplier();
int specialPuchaseOrderSizeMult = SystemDao.getSpecialPurchaseOrderSizeMultipler();
double rcWass2 = Math.pow(rcAvgSales, 2);
Double maxValue =
Math.max(
rcAvgSales + specialPuchaseOrderSizeMult * Math.sqrt(Math.max(0, rcWass2)),
specialPuchaseOrderWassMult * innerPackQty);
if (epSalesActual > maxValue && eventSeasonalIndicator == false) {
epSales = maxValue;
} else {
epSales = epSalesActual;
}
}
private double getLostSales() {
// lostSales = max(0, average sales - actual sales)
return Math.max(0, rcAvgDemand / 7 - epSalesActual);
}